Is our data safe? Can we self-host AI?

Yes. VYROX deploys open-weight models (Llama 3.3, Mistral, Qwen 2.5, Hermes) on your own GPUs or private cloud for sensitive workloads. PDPA and ISO 27001 documentation provided.

What does an AI project cost?

Pilots typically RM 25,000 to RM 80,000. Production deployments RM 80,000 to RM 280,000. Platform rollouts RM 280,000 to RM 500,000 or more. Customer should never spend more than one third of expected year-one savings.

How do you stop AI hallucinations in production?

Retrieval-grounded answers with citations. Schema-validated outputs. Eval harnesses on golden datasets. Confidence thresholds. Human approval gates on irreversible actions. We track hallucination rate as a hard KPI.

Can AI automate legacy software that has no API?

Yes. Using Computer Use (Anthropic) and Browser Use, the agent literally sees the screen, moves the mouse, types, and clicks like a human, but faster, 24/7, with full audit logs. We have deployed this on AutoCount, MyInvois, SST portal, legacy Windows ERPs, and dozens of vendor portals.

How fast can we see a working AI demo?

For most use cases, 5 to 15 working days from kick-off. Pilot delivery in 4 weeks. Production in 10 weeks.

What is the typical payback period?

VYROX's median customer payback is 4.7 months. Year-one operating-cost reduction averages 38 percent on automated cost centres.

Do you offer outcome-based pricing?

Yes. For platform-tier engagements (RM 280k+), VYROX offers gain-share contracts where part of the fee is tied to measured year-one savings. We win when you win, written into the contract.

Which AI models does VYROX deploy?

Cloud: Claude Opus 4.7, Claude Sonnet 4.6, Claude Haiku 4.5, GPT-4o, GPT-4.1, Gemini 2.5 Pro. On-prem: Llama 3.3 70B, Mistral, Qwen 2.5, DeepSeek, Hermes. Vision: GPT-4o Vision, Claude Vision, Qwen2.5-VL, LLaVA, YOLO v11, SAM 2. Selected per workload — never locked to one vendor.

Do you handle hardware (cameras, edge GPUs, sensors, robotics)?

Yes. NVIDIA Jetson Orin, IP cameras, IoT gateways, PLCs, robotic arms, ROS 2 integration. Sourcing, integration, on-site commissioning, end-to-end delivery across Southeast Asia.

What industries has VYROX shipped to?

Manufacturing and electronics, property and real estate, retail and e-commerce, hospitality and F&B, automotive, healthcare clinics, professional services, finance and accounting, education, sports and recreation clubs, government adjacents, and software-as-a-service operators.

Where is VYROX based?

Kuala Lumpur, Malaysia. We serve customers across Malaysia, Singapore, Thailand, Indonesia, Philippines, Vietnam, and Brunei. On-site engineering in-region, same time zone, English/Bahasa/Chinese capable.

VYROX.AI | The AI engineering partner for business and industry

Q: Will AI replace my staff?

It will replace specific tasks: the repetitive ones. People get redeployed to higher-value work. Most VYROX clients reduce hiring rather than firing.

Q: What is MCP (Model Context Protocol)?

MCP is an open standard, created by Anthropic and now adopted by OpenAI, Google, Microsoft, Cursor, and the broader industry, that lets AI agents securely connect to any tool, database, or API. It eliminates vendor lock-in: swapping Claude for GPT-4o or Llama becomes a config change, not a rebuild.

Why this matters now

Your business is leaking money on work AI was built to handle.

The technology that powers ChatGPT became a real, production-grade tool roughly 18 months ago. Companies that moved first are already 30 to 45 percent leaner on operations. The window to catch up is now, not when your competitor has already done it.

"I'm paying salaries for work nobody enjoys."

Data entry, copy-paste between systems, the same WhatsApp reply 50 times a day. Good people stuck doing robot work.

"Everything takes 3× longer than it should."

Quotes take days. Invoices pile up. Reports are always late. Customers churn while we're getting back to them.

"We sleep. Our competitors don't."

2am orders go unanswered. Overseas customers wait 12 hours. Cameras record incidents nobody is watching.

"Margins are squeezed every quarter."

Wages up. Utilities up. Suppliers up. You can't keep raising prices; you need to drop costs without dropping quality.

"Hiring good people is brutal."

High turnover, training cost, MC, EPF, payroll headaches. You'd rather grow output without growing headcount.

"I know AI is coming. I just don't know where to start."

You've seen the demos. You've read the headlines. But what specifically does this do for my business?

What AI can do, in plain English

Four capabilities. One stack. Yours.

Modern AI is not one thing. It is four distinct capabilities, and the compound effect happens when we combine them inside your workflows. Think of it as hiring four different specialists who never sleep, never quit, and learn faster than any employee you've ever trained.

01 / Language AI (LLM)

A digital employee who has read every document you own.

It reads, writes, answers, summarises, and decides at machine speed. Speaks English, Bahasa Malaysia, Chinese, and more. Never forgets a policy. Never has a bad day.

Built on: Claude Opus 4.7 · GPT-4o · Gemini 2.5 · Llama 3.3 · Mistral · Qwen · DeepSeek

Replaces work like

Answering customer questions on WhatsApp, phone, chat
Reading and summarising contracts, tenders, and reports
Writing sales emails, proposals, follow-ups
Looking things up across SharePoint, email, ERP
Report and proposal generation in your brand voice
Compliance and policy Q&A with audit-friendly citations

02 / Vision AI (VLM)

Eyes that understand what they see, not just record.

Watching every camera, reading every document, inspecting every part. At 30 frames per second, 24 hours a day, without ever getting tired.

Built on: GPT-4o Vision · Claude Vision · Qwen2.5-VL · LLaVA · YOLO v11 · SAM 2

Replaces work like

Inspecting products on a production line
Watching CCTV for safety, theft, or incidents
Reading invoices, receipts, DOs, ICs into your ERP
Counting stock, checking shelves, measuring queues
Medical image triage assistance
License plate and vehicle analytics

03 / Agentic AI

Workers that act, not just answer.

A chatbot replies. An agent acts. It logs into your systems, calls suppliers, books meetings, updates databases, drives a browser, controls a desktop, and reports back, like a junior employee but in seconds.

Built on: Claude Agent SDK · MCP · Computer Use · Browser Use · AI Skills · LangGraph

Replaces work like

Procurement: RFQ to PO, supplier to invoice
Finance: reconciliation, month-end close
Recruiting: source, screen, schedule, interview
Marketing: brief, create, schedule, measure, repeat
Software engineering: write, refactor, test, deploy
Driving any browser or desktop app that has no API

04 / Physical AI

Intelligence that moves atoms, not just bits.

Running on cameras, sensors, robots, and tiny computers right inside your factory, building, or vehicle. Making decisions in milliseconds without depending on the internet.

Built on: NVIDIA Jetson · Google Coral · Hailo-8 · ROS 2 · NVIDIA Isaac · Modbus · MQTT

Replaces work like

Building automation: HVAC, lighting, lifts, access
Drone inspection of solar farms, warehouses, pipelines
Robotic picking, packing, sorting, palletising
Predicting equipment failure 7 to 14 days early
AGV/AMR fleet orchestration
Edge voice kiosk and drive-thru AI

The compound effect

All four working together is where the magic happens.

A camera sees a defect. An agent opens a ticket and emails the supplier. The LLM drafts the report. A robotic arm ejects the unit. Four pillars, one workflow, zero humans in the loop. That's what we engineer for you.

For professionals · your daily work, automated

AI doesn't replace your judgement. It removes the work that gets in the way of it.

An auditor still signs the opinion. An architect still picks the form. A designer still chooses the palette. What VYROX builds is the layer underneath — the rote work, the documentation, the formatting, the chasing — that eats 40–60% of your week and pays nothing.

Accountants

SST · LHDN · MyInvois · IFRS

Bank statement reconciliation: agent matches statement lines to ledger, flags only true exceptions
PDF invoice & receipt posting into AutoCount, QuickBooks, SAP — 30s per document, <0.5% error
LHDN e-Invoice (MyInvois) submission via Computer Use — even if your ERP has no API yet
SST returns drafted from transaction data, pre-checked for common errors
AR chasing agent: WhatsApps customers, escalates politely, books a payment-plan if needed
Month-end close compressed from 11 days to 3

~22h/week back

computer-use · autocount
myinvois · vision-ocr

Auditors

ISA-aligned · MIA approved trail

Population sampling: agent pulls the right strata from the client's GL, exports working-paper-ready
Vouching automation: invoice ↔ GL ↔ payment ↔ delivery — three-way match across PDFs
Lead schedule generation from trial balance — drafted in minutes, you only review
Confirmation letters: drafted, sent, tracked, chased automatically
Going-concern narrative pre-drafted from cash flow + bank confirms
Walk-through documentation auto-generated from interview transcript

~30h/week back

claude-opus · pdf · vision
excel · word

Engineers (M&E, civil, structural)

UBBL · BS · EN · MS · IEM

Drawing markup & compliance checks against UBBL, MS-1525, fire codes — page by page
Specification & BOQ generation from project brief — quantities, materials, codes referenced
Calculation verification: agent re-runs your spreadsheet with formula audit and unit checks
Site report drafting from photos: defects classified, severity scored, location pinned
Submission package preparation (drawings + forms + endorsements) for DBKL, MBPJ, JBPM, ST
Variation order tracking with auto-cost-impact analysis

~18h/week back

vision · cad-mcp
excel · word

Architects

UBBL · OKU · GBI · LAM

Programming brief synthesis from client interviews — adjacency matrix, area schedule, must-haves
UBBL, fire (JBPM), OKU and GBI compliance pre-checks on schematic plans
Submission packages for DBKL, MBPJ, MBSA, MBSJ — forms, endorsements, RTO docs auto-filled
Concept narrative drafting — design statement, sustainability statement, planning rationale
Sun-shadow & massing-option exploration scripted into your BIM workflow
Coordination meeting minutes + action tracking, automatic

~16h/week back

claude-opus · vision
revit-mcp · word

Interior designers

FF&E · BoQ · client decks

Mood-board generation from a written brief — palette, materials, style references, sourced
Photoreal concept renders from rough sketches via image-gen models, on-brand
FF&E spec sheets with live prices from your preferred suppliers
BoQ generation from a CAD layout: linear-metre, square-metre, piece counts
Site condition assessment from walkthrough photos — defect log + repair scope
Client presentation deck drafted from project notes; you tweak visuals, not slides

~14h/week back

flux · sdxl · claude-vision
excel · pptx

Designers (graphic, brand, product)

Figma · Adobe · Flux · SDXL

Brand-consistent asset generation: web banners, social posts, ad variants — all locked to your tokens
Copy-pair drafting: agent writes headline / sub / CTA permutations for A/B tests
Image clean-up at scale: background removal, upscaling, retouching — batch jobs overnight
Design-system audits: which components are stale, which are inconsistent, what's missing
Client-feedback parsing: agent reads the email, drafts the revision list with priorities
Asset hand-off packaging: exports, naming conventions, dev-ready specs

~12h/week back

flux · sdxl · figma-mcp
claude-sonnet

Programmers

Claude Code · Codex · OpenHands

Feature delivery 5–10× faster with Claude Code: spec → branch → tests → PR, all from chat
Background agents tackle the bug backlog overnight; you review the PRs over coffee
Test generation, regression coverage, mutation testing — non-negotiable, automated
Code review at scale: agents check architectural drift, security, perf regressions per PR
Migration agents: Java → Kotlin, JavaScript → TypeScript, on-prem → cloud — supervised
Documentation generated from source, kept in sync — no more stale READMEs

~28h/week back

claude-code · codex
openhands · mcp

Lawyers & paralegals

Bar-aligned · privileged-context

Contract review: agent reads the SPA / MoU / NDA, flags risky clauses against your firm's playbook
Due-diligence document indexing: thousands of PDFs categorised, summarised, made searchable
Litigation-bundle preparation: pleadings, exhibits, chronology, all paginated and indexed
Deposition transcript summarisation with citation back to timestamp
Conveyancing & sale-and-purchase docs drafted from a 4-field intake form
On-prem deployment available for privilege-sensitive matters

~24h/week back

claude-opus · on-prem
vector-search · word

Doctors & clinicians

MOH-aligned · PDPA · on-prem

Clinical-note dictation: scribed during consult, drafted into EMR-ready SOAP format
Referral-letter drafting from patient history; you review and sign
Insurance / panel claim drafting with the right diagnosis codes
No-show follow-up agent: reactivates 30–40% of dropped appointments
Medical-imaging triage assistance (radiologist still signs off)
PDPA-aligned on-prem deployment for sensitive workloads

~15h/week back

whisper · claude-opus
on-prem · llama-3

Your profession not listed?

If you do work, AI can help you do less of it.

Tell us what your week looks like. We'll come back within 48 hours with the top three workflows that AI could lift off your desk — with realistic numbers and a plan.

Tell us your day →

The toolkit behind your AI

Built on the same agent stack Anthropic, OpenAI, and Google ship.

The AI revolution of 2024 to 2026 isn't just about smarter models. It's about a new layer of agent tools, protocols, and connectors that let AI do things: read your codebase, drive your browser, control a desktop app, plug into Slack, write to your database. VYROX uses every piece of this stack so we can ship results in weeks, not years.

Layer 01

AI coding agents

A new generation of agents that reads your entire codebase, writes new features, fixes bugs, runs tests, and opens pull requests. We use these every day to ship your AI systems 5 to 10 times faster than a traditional development team.

Claude Code

Anthropic

Official CLI coding agent. Opus 4.7. 1M context. Sub-agents. Lives in your terminal, reads the whole repo, writes the change, runs tests, opens the PR.

Codex / Codex CLI

OpenAI

Autonomous coding agent. Cloud or local. Sandboxed. GPT-5 / o3. Run alongside Claude Code for cross-vendor redundancy.

OpenHands

Open source · Apache 2.0

Self-hostable AI software engineer (formerly OpenDevin). Used when source code can never leave the customer perimeter: defence, banking, government.

Hermes

Nous Research

Open-weight LLM family tuned for tool-use and function calling. Drop-in replacement for closed APIs when you need fully on-prem agent behaviour.

Layer 02

New agent capabilities

Breakthroughs from 2024 to 2025 that turned AI from a clever assistant into a real digital worker. We deploy all of them.

Computer Use

Anthropic's breakthrough. Claude sees your screen, moves the mouse, clicks buttons, types, and navigates any desktop application. The unlock: automating legacy software that has no API.

Drives SAP, AutoCount, MyEG, customs portals
Works on Windows apps from the 2000s
Logs every action for full audit trail

Browser Use / Claude in Chrome

Agents that drive a real Chrome or Edge browser. Anything a human does in a browser, automated end-to-end.

Vendor portals, banking, e-invoicing, LHDN, SSM
Multi-step form workflows with validations
Headless or visible, your choice

AI Skills

Specialised capability packs Claude invokes on demand. We bundle your SOPs as custom skills, so your tribal knowledge becomes an invokable AI tool.

Out-of-box: PDF, Word, Excel, PowerPoint, Canvas
Custom: your billing logic, your QA checklist
Versioned, tested, swappable

MCP (Model Context Protocol)

The open standard, created by Anthropic and now adopted by OpenAI, Google, Cursor, and the whole industry, that lets AI agents securely connect to any tool, database, or API.

Open standard, vendor-neutral
Secure by design: per-tool permissions
Future-proof: works with next year's models too

MCP Connectors

Pre-built MCP servers for the tools you already use. Hours of integration instead of months of API plumbing.

Slack · Teams · Notion · Linear · Jira · GitHub · Google Drive · Gmail · Salesforce · HubSpot · Stripe · Xero · SAP · Postgres · MySQL · MongoDB · WhatsApp Business · Shopify · Calendly · Zoom · DocuSign.

Sub-agents and crews

Complex jobs decomposed across a team of specialised agents. A Researcher feeds a Writer feeds a Reviewer. Each small, focused, testable, and replaceable.

LangGraph, CrewAI, Claude Agent SDK
Parallelised for speed
Full trace and replay for debugging

What this means for your business

You don't need to learn any of this. You just need to know we already have.

When you hire VYROX, you're not buying "ChatGPT for your company." You're getting a full-stack engineering team that:

Uses Claude Code and Codex to ship features 5 to 10 times faster than traditional dev houses
Deploys Computer Use and Browser Use to automate the legacy systems other vendors say can't be done
Bundles your SOPs as AI Skills, turning tribal knowledge into reusable, versioned, audit-friendly tools
Connects to your existing stack via MCP, so adding new tools later is a configuration, not a project
Self-hosts open agents (OpenHands, Hermes) when your data must stay on-prem

Frontier-model stack

The same tools Anthropic, OpenAI & NVIDIA ship on. Wired into your business.

Vendor-agnostic by design. Built on Model Context Protocol (MCP), so swapping models is a config change, not a rebuild. Today Claude Opus 4.7 for reasoning, GPT-4o for vision, Llama on-prem for sensitive workloads, tomorrow whatever wins the benchmarks.

Models & reasoning

Claude Opus 4.7

Anthropic · 1M context

Claude Sonnet 4.6

Anthropic · agent-default

Claude Haiku 4.5

Anthropic · low-latency

GPT-4o · GPT-4.1

OpenAI · multimodal

Gemini 2.5 Pro

Google · long context

Llama 3.3 / 4

Meta · open weights

Mistral · Qwen

Open · multilingual

DeepSeek · Hermes

Specialised reasoning

Agentic & coding frameworks

Claude Code

Anthropic · CLI agent

Claude Agent SDK

Custom agents

OpenAI Codex

Coding agent

OpenHands

Open-source · self-host

Computer Use

Anthropic · desktop control

Browser Use

Web automation

LangGraph · CrewAI

Multi-agent orchestration

Claude Skills

Reusable SOPs

Vision & perception

GPT-4o Vision

VLM · cloud

Claude Vision

VLM · long-doc

Qwen2.5-VL · LLaVA

Open VLM · on-prem

YOLO v11 · SAM 2

Detection · segmentation

DeepFace · MediaPipe

Face · pose

RT-DETR · Florence-2

Edge-optimised

DocLayout · PaddleOCR

Document AI

Whisper · Distil-Whisper

Speech-to-text

Infrastructure, data & integration

Model Context Protocol

Open standard · tools/data

NVIDIA Jetson · Orin

Edge GPU

ROS 2 · Isaac

Robotics

vLLM · TensorRT-LLM

On-prem serving

Postgres · pgvector

Structured + vector

Qdrant · Weaviate

Vector search

Slack · Teams · WhatsApp

Channels

SAP · AutoCount · MyInvois

Legacy / regulatory

What this means in practice

Your system is never locked to one vendor. Today's Claude Opus is tomorrow's better model — and switching is a one-line config. Sensitive data stays on your perimeter when needed; cloud reasoning kicks in only where it adds value. Same architecture serves Bursa-listed manufacturers and family-run F&B chains.

Physical & edge delivery

We ship the hardware too. Sourced, integrated, commissioned.

Cloud AI alone is not enough for industrial workloads. VYROX delivers the edge GPUs, cameras, sensors and IoT gateways that run AI where the data is born — on the factory floor, at the lift lobby, in the warehouse, on the road.

NVIDIA Jetson Orin family

Orin Nano · Orin NX · AGX Orin

Edge GPU modules running Llama, Qwen-VL, YOLO and SAM at 30+ FPS on-device. 8GB to 64GB unified memory, 20–275 TOPS. Industrial-grade enclosures, deployed in 40+ live sites.

IP cameras & vision sensors

4K · ONVIF · RTSP · PoE

Hikvision, Dahua, Axis, and industrial machine-vision cameras. Vendor-agnostic ingestion pipeline. Edge inference at the camera or backhaul to a Jetson cluster.

Cobots & robotic arms

ROS 2 · MoveIt · Universal Robots · Doosan

Pick-and-place, assembly assist, defect-eject systems. Vision-conditioned policies wired to the LLM reasoning layer for handling novel cases without re-programming.

IoT gateways & sensors

LoRaWAN · 5G · Modbus · OPC-UA

Temperature, vibration, current, occupancy, air-quality. Bridged into the agent's tool layer via MCP. Predictive maintenance and smart-building automation in one fabric.

On-prem inference servers

RTX 6000 · L40S · H100 · vLLM

Air-gapped Llama 3.3 70B / Qwen 2.5 72B clusters for regulated industries. Sized for tokens-per-second on actual workloads, not vendor benchmarks. Quarterly model refresh.

Custom edge-AI appliances

x86 · ARM · Fanless · 24V industrial

When off-the-shelf doesn't fit: bespoke fanless edge boxes with Jetson + 4G/5G + dual-NIC, IP65 enclosures, DIN-rail or ceiling mount. Built in our KL lab, deployed regionally.

A typical day, before vs after

Same business, same headcount, completely different operation.

Not a hypothetical. This is the real before/after from a mid-market property management group with 4,200 units across Klang Valley. RM 612k saved year-one, zero tenant complaints, headcount unchanged.

Before · Pre-AI operation

2 admin staff manually answer 80–120 tenant queries / day on WhatsApp; first reply lag 47 min
Invoices typed into AutoCount from paper DOs; ~6% data-entry errors caught at month-end audit
Aircon and lift schedules set seasonally; energy bill grows ~9% YoY despite occupancy flat
Late-night incidents (water leak, false alarm) page on-call security, escalate to property manager next morning
Quarterly reports take 11 working days across 4 staff; rarely contain forward-looking analysis
Vendor invoices reconciled manually against POs; 22% mismatches require follow-up

→

After · 6 months in

Agent answers 84% of queries instantly (median 12s); admin staff redeployed to leasing
Vision pipeline reads DOs, posts invoices to AutoCount in < 30s; 0.4% exception rate, all human-reviewed
Energy agent autotunes HVAC + lifts on occupancy and weather; 28% utility reduction
Incident-triage agent classifies, dispatches and updates tenant in < 90s; manager sees overnight digest
Report-writing skill produces draft monthly in 9 min; analyst spends time on insight, not formatting
Reconciliation agent matches invoice ↔ PO ↔ DO end-to-end; 2.1% mismatch rate, all flagged with context

A decade of engineering · 2015 → 2026

We didn't pivot to AI. We grew into it.

VYROX started in IoT and ELV systems. We added vision and edge AI as the silicon got there. We added agentic AI the week Anthropic shipped Computer Use. Each step earned the next.

2015

VYROX founded in Kuala Lumpur

Started as an ELV / IoT integration firm. First customers: property developers, manufacturers, sport clubs.

2017

First AI-on-edge deployment

Face-recognition access control on NVIDIA Jetson TX1 across a Bursa-listed property group. Still running today.

2019

SnookerKing & VIPSnooker launched

Our own AI-powered SaaS for snooker centres. Today: 500+ live centres across 23 countries. Eat-our-own-cooking proof.

2020

Pandemic-era contactless rollout

Smart-access, intercom, parking-lock systems scaled to 60+ sites. Lift access, EV charging, smart-laundry products born here.

2023

First production LLM deployment

GPT-4 + RAG customer-support agent for a regional e-commerce operator. 84% containment, 11s median reply.

2024

Vision-AI QA on production lines

YOLOv8 + Qwen-VL hybrid for electronics contract manufacturer. RM 2.4M defect-cost recovery year one.

2025

Agentic AI & Computer Use

First production Computer Use agents driving AutoCount, MyInvois, vendor portals. Legacy software became automatable.

2026

127 deployments. 11 SaaS products. MCP everywhere.

Model-agnostic architecture standard on every new build. Anthropic Build Partner. NVIDIA Inception member. Anthropic Computer Use, Claude Skills, Claude Agent SDK shipping in production.

The team you'll work with

Engineers who built it. Operators who shipped it.

VYROX is led by a small, senior team. You'll be working directly with the engineers who write the code and ship the systems — not partners, not "client success managers".

Ts. Dr. Leong Yee Rock

Founder & lead AI engineer

11 years building production AI / IoT systems across SEA. Drives architecture, model selection, and customer-side technical decisions. Available on every project.

Ts. (MBOT) · PhD · Bursa CTO advisor · Anthropic Build Partner

Engineering pod

8 senior engineers · KL

Full-stack Python / TypeScript engineers. LLM, vision, robotics, MCP. Each engineer has shipped at least 6 production AI systems. Median tenure 4.2 years.

Claude Code · OpenHands · ROS 2 · vLLM · Postgres

Operations & delivery

4 PMs · 3 field engineers

Customer-facing PMs run the audit, scope and delivery. Field engineers do on-site commissioning across SEA — racks, cameras, edge GPUs, training.

PMP · ISO 27001 LA · PDPA-trained

Data & eval

3 ML engineers

Build the eval harnesses, golden datasets, and observability that keep production agents honest. Catch model regressions before customers feel them.

LangSmith · MLflow · pytest · pgvector

We're hiring

Senior ML / agent engineers, KL-based, on-site & remote

hr@vyrox.com

Solutions by industry

Your industry. Already solved.

Twelve verticals. Production-ready playbooks. Every one has shipped for a real customer in Malaysia or the region.

Manufacturing & Electronics

Lights-out QA & predictive maintenance

Vision + Physical + Agentic. Inspection at full line speed, MES/SOP copilot, cobot-assisted assembly, OEE intelligence.

Typical savings RM 2 to 8M / year

Retail & E-commerce

Footfall, planogram, loss prevention

Vision + Language + Agentic. Out-of-stock detection, personalised recommendations, WhatsApp sales agent.

Basket +18% · shrinkage −35%

F&B / Restaurants / QSR

Voice-AI drive-thru, kitchen safety, demand forecast

All four pillars. Multilingual order taking, waste forecasting, auto-rostering, review intelligence.

Labour −30 to 45% · food cost −12 to 18%

Real Estate & Smart Buildings

Buildings that run themselves

Physical + Agentic + Vision. HVAC + lift + lighting AI, CCTV intrusion, tenant WhatsApp concierge.

Utility −20 to 35% · OPEX −22%

Logistics & Warehousing

Autonomous yard & inventory

Vision + Agentic + Language. Camera cycle counting, AGV orchestration, OCR'd DO, customs paperwork.

Mis-picks −28% · outbound +40%

Healthcare & Clinics

Clinical copilot & front-desk agent

Language + Vision + Agentic. Voice-to-EMR scribe, image triage, appointment agent, claims pre-check.

No-shows −40% · charting −7 min/visit

Banking, Insurance & Fintech

KYC, claims, underwriting

Language + Agentic. Document understanding, fraud detection, conversational banking.

Claims SLA: 5 days → 4 hours

Energy & Utilities

Predictive asset intelligence

Vision + Physical + Agentic. Drone-borne inspection, thermal monitoring, load forecasting, HSE reporting.

Inspection man-days −60%

Legal, Compliance & Audit

Contract review & regulatory monitoring

Language + Agentic. Clause extraction, redlining, NDA generator, e-discovery.

Review hours −75%

Hotels & Hospitality

Multilingual concierge & dynamic rates

Language + Vision + Agentic. Review sentiment, biometric self check-in, housekeeping audit.

RevPAR +9% · concierge ops −50%

Automotive & Dealer

Damage assessment & diagnostic agents

Language + Vision + Agentic. Photo-based damage estimate, parts forecasting, test-drive lead scoring.

Quote turnaround: 2 days → 12 min

Education & Training

1:1 tutor agents & auto-grading

Language + Agentic. Curriculum generator, parent/admin chatbot, AI-text detection.

Teacher prep −60%

Don't see your industry? Tell us what you do. We've probably already built something close.

Deep dive · Sport clubs, clubhouses & sport centres

The operating system for modern clubs.

VYROX has shipped 500+ live deployments to snooker centres, golf clubs, sports clubs, recreational clubhouses, pickleball & padel courts, gyms, and karaoke lounges across 23 countries. We know your day. We've automated it.

A real day in the life

Member taps WhatsApp at 14:02. By 14:03, the agent has booked the court, charged the wallet, assigned a coach, prepped the F&B order, opened locker 12, and queued a tow-truck reminder for the member's car expiring at 18:00.

No human touched it. The shift manager only sees a digest at end of day. The receptionist is gone, redeployed to member retention. The club captures revenue at every interaction, 24 hours a day, in English, Bahasa, Chinese — without hiring.

Talk to us about your club →

WhatsApp booking agent

Members book courts, bays, classes or lanes in plain language — the agent checks availability, conflicts, weather and pricing, takes payment, confirms, sends QR access. Cancellation and reschedule too.

claude-sonnet · pos · stripe · whatsapp

Member onboarding & KYC

New member fills a 90-second WhatsApp flow. Agent extracts IC details, takes a face photo, runs the verification, issues a digital member card, charges joining fee, and adds them to the loyalty programme.

vision · face-recognition · stripe · pdpa

F&B order taking

Member scans a court-side QR; the agent shows the menu (with allergens), takes the order in any language, prints the kitchen ticket, charges the wallet, and pings when ready. Tips and upsells included.

menu-skill · foodserva · whatsapp · pos

AI snooker / pickleball scoring

Overhead camera tracks balls, players, fouls and scores in real time. Live leaderboards on the clubhouse TV; members get auto-clips of their best shots; coaches replay any frame to debrief.

yolo-v11 · sam-2 · jetson-orin · livestream

Coach video feedback

Member uploads their swing or stroke. Vision-language model returns annotated frame-by-frame feedback (grip, stance, follow-through). Pairs with a real coach for the next session.

qwen-vl · mediapipe · pose-estimation

Smart locker, racquet & cue rental

Self-service rental via QR. Agent confirms the rental, releases the locker, sends a clean-photo reminder on return, charges damage if vision detects an issue, releases deposit automatically.

smartlocker · vision · stripe · iot

Renewal & dormant reactivation

Agent watches every membership end date and visit frequency. Sends personalised renewal offers, win-back vouchers, referral bonuses. Reactivates dormant members at 3×, 6× and 12× the rate of email blasts.

claude-sonnet · crm · whatsapp · loyalty

Energy & HVAC autotune

The agent watches occupancy, ambient temperature, and forecast. Pre-cools courts before peak booking, throttles unused zones, dims unused LEDs. 22–32% utility cut without member complaints.

energy-skill · modbus · iot · forecast

Incident triage & safety

CCTV catches a slip, an unattended bag, a smoke event, an unauthorised entry. Agent classifies, dispatches the right staff, opens an incident ticket, notifies management, and timestamps everything.

vision · classification · escalation · audit

Visitor / guest management

Member invites a friend. Friend receives a QR pass on WhatsApp, gets through the boom-gate, the lobby door, and the lift. Visit logged, member notified, pre-paid day-pass charged automatically.

superpass · ultrapass · qr · ocr

Auto monthly statements & reports

Treasurer's nightmare gone. Agent drafts the management committee pack in ~9 minutes: P&L, AR ageing, court utilisation, member churn, F&B mix. Editable Google Docs, branded, with charts.

report-skill · gsheets · gdocs · whatsapp

Tournament & league orchestration

From registration to seedings to brackets to live scoring to prize-money settlement. Agent runs the whole tournament; organiser only approves edge cases. Auto-publishes highlights to socials.

bracket-skill · livestream · clip-cutter · social

Our shipped club products

VIPSnooker

Snooker club management · 500+ centres · 23 countries

SnookerKing

Member-facing snooker app · scoring · F&B · loyalty

SportServa

Multi-sport club platform · pickleball · golf · tennis · padel

FoodServa & Poserva

F&B POS · kitchen display · LHDN e-Invoice ready

Solutions by problem

Pick your pain. We've got the fix.

Twelve problems we hear every week from business owners. Each has a proven AI solution.

Labour

"We pay too many people to do repetitive work."

Data entry, reconciliation, copy-paste, scheduling, basic ticket triage.

The fix

Agentic AI takes the task end-to-end. LLM handles the unstructured bits. Humans handle exceptions only.

↓ 60 to 80% headcount on that workflow

Quality

"Humans miss defects after a few hours."

Visual inspection fatigue, inconsistent grading, missed scratches, wrong labels.

The fix

Vision AI inspects on the line at 12 ms per frame. Active learning on edge cases. Self-improving daily.

99.4% recall vs 92% human baseline

"We get drowned in customer messages."

WhatsApp, Messenger, IG, web chat, phone, email. Same questions, five languages, 24/7.

The fix

Language AI copilot grounded in your knowledge. Voice and chat on every channel.

70 to 85% auto-resolution

Uptime

"Equipment fails without warning."

Surprise downtime, missed maintenance windows, expensive emergency repairs.

The fix

Physical AI on vibration, current, and acoustic signatures. Tiny edge model. Agent auto-schedules maintenance.

7 to 14 day failure foresight

Docs

"Documents are a mess."

PDFs, scans, handwritten DOs, foreign invoices stuck in inboxes and filing cabinets.

The fix

Vision AI reads any layout. Language AI structures and validates. Agent pushes into your ERP/CRM.

↓ 80% manual entry · ↓ 95% errors

Security

"Cameras record but no one watches."

Hundreds of CCTV feeds, three guards, zero attention. Incidents found only after the fact.

The fix

Vision AI on every stream. Custom event taxonomy: PPE, fights, falls, theft, intrusion.

Detect < 3s · false alarm < 1%

Revenue

"Sales follow-up leaks leads."

Leads come in faster than humans can follow up. Quotes take days. WhatsApp goes unread.

The fix

Lead-qualifier agent responds in under 60 seconds. LLM drafts proposal. Books meeting on rep's calendar.

3× SDR output · +22% win rate

OPEX

"Energy and utility bills keep climbing."

HVAC on empty floors. Lights on after midnight. Generators idling. Water leaking.

The fix

Physical AI + IoT sensor fusion. Occupancy, weather, and tariff aware. Agent negotiates setpoints hourly.

20 to 35% utility savings

Decisions

"We have data. We don't have answers."

Power BI dashboards nobody opens. Excel everywhere. Decisions on gut feel, always late.

The fix

Executive briefing agent every 6am. Natural-language KPI Q&A. Anomaly flagging with drill-through.

Decisions in minutes, not weeks

Risk

"Audits are a nightmare."

Manual evidence collection, missing logs, frantic email chains before the auditor arrives.

The fix

Language AI reads regulations, maps to your controls. Agent auto-collects evidence weekly.

Audit prep: 6 weeks → 2 days

Velocity

"Our dev team is overloaded and slow."

Backlog never shrinks. Bug fixes take weeks. Features slip a quarter.

The fix

Claude Code + Codex inside your engineering org. They read the whole codebase, write features, run tests, open PRs.

5 to 10× shipping velocity

Legacy

"We're stuck on a legacy system with no API."

AutoCount, SAP green-screens, government portals, custom Windows apps from 2008. Manual data re-entry forever.

The fix

Computer Use and Browser Use agents. The AI literally sees the screen and clicks like a human, but 10× faster and never tired.

Manual data-entry roles eliminated

Proof · Customer stories

Real businesses. Real numbers.

Composite stories pulled from real deployments. Names changed, numbers honest. The kind of detail your CFO will want.

Story 01

Manufacturing

Penang

Electronics OEM replaces an 18-person QA team with 4 smart cameras.

Before

18 inspectors across 3 shifts. RM 1.2M/yr payroll. 8.3% defect escape to customer. Quality dropped after 2pm every day.

After

4× Jetson Orin running vision AI on 4 line stations. 0.4% escape rate. 11 inspectors retained for higher-skill roles, 7 promoted into engineering.

Payback: 6.2 months. Quality rating with their largest customer went from B-tier to A-tier within one quarter.

Escape rate

0.4%

was 8.3%

Throughput

+38%

same line

Labour cost

−61%

redeployed

Payback

6.2 mo

full invest

Story 02

Retail

Klang Valley

Home-appliance retailer handles 1,400 daily WhatsApps with 4 people instead of 12.

Before

12-person CS team buried under 1,400 WhatsApps/day. 6-hour average first-response. NPS sitting at 32.

After

Claude-powered copilot grounded in product KB + order DB. 81% solo resolution. CS team of 4 running upsells instead of tickets.

NPS jumped to 71 in 90 days. Repeat purchase rate up 24%. Customers came back because they finally got fast answers.

First response

was 6 hours

Auto-resolved

81%

no human

NPS

from 32

CS headcount

−67%

on tickets

Story 03

F&B / QSR

12 outlets

Drive-thru chain replaces night-shift order takers with a multilingual voice AI.

Before

Voice order-takers averaged 8% errors, 32s order time. Night-shift turnover 140%/yr. Upsell hit-rate barely 11%.

After

Edge voice agent in BM/EN/Chinese with local accent training. 19s order time, 1.2% error rate. Staff redeployed to kitchen prep.

Upsell hit-rate went from 11% to 38%. The agent never forgets to ask.

Order time

19s

was 32s

Error rate

1.2%

was 8%

Upsell hit

38%

from 11%

Avg ticket

+RM 4.20

per order

Story 04

Real Estate

KL CBD

28-storey office tower saves RM 612k in year-one utility bills.

Before

Fixed HVAC schedules. Empty floors still cooled to 22°C. Utility bill RM 2.18M/yr. Chillers cycled wastefully in peak tariff.

After

On-prem AI agent reads occupancy + weather + TNB tariff. Negotiates setpoints and chiller cycles every 60 seconds.

28% utility reduction = RM 612k saved year one. Zero tenant complaints. Temperature control actually improved.

Utility bill

−28%

RM 612k

Payback

7 mo

all-in

Carbon

−312t

CO₂ / yr

Tenant sat

+11pt

comfort

Story 05

Insurance

Mid-tier

Insurer cuts claim processing from 5 days to 4 hours.

Before

5-day average claim SLA. 22-person processing team. Customer churn driven by slow payouts more than premium.

After

Vision AI extracts data. Language AI cross-checks policy and fraud. Agent auto-approves 78%, routes 22% to underwriter pre-filled.

SLA: 4 hours. Team reduced to 8 specialists. Customer retention jumped 14%.

SLA

4 hrs

was 5 days

Auto-approve

78%

of claims

Processing team

−64%

redeployed

Retention

+14%

customer

Story 06

Energy

85MW solar

Solar farm replaces a 3-engineer inspection team with an autonomous drone.

Before

Monthly thermal inspection by 3 engineers, 4 days per pass. Hotspots discovered late = lost generation revenue.

After

Autonomous drone + on-board Jetson + vision AI. Weekly 38-minute patrol. Issues become CMMS tickets, routed automatically.

Generation uplift +3.8% from earlier hotspot fixes. Inspection cost down 82%.

Inspect time

38 min

was 4 days

Inspect cost

−82%

man-days

Generation

+3.8%

uplift

Payback

11 mo

hardware

Story 07

Healthcare

8 branches

Dental group cuts no-shows by 40% and reactivates 1,400 dormant patients.

Before

18% no-show rate. 4 receptionists juggling WhatsApp, phone, walk-ins. Bookings 3 weeks out, so patients forgot.

After

WhatsApp booking agent triages symptom, suggests service, checks availability, books, reminds. Reception handles 3× volume.

No-shows dropped to 11%. Reactivated 1,400 dormant patients in month one. Pure recovered revenue.

No-shows

−40%

18 → 11%

Recovered

1,400

dormant

Reception capacity

3×

same team

Revenue

+22%

in 6 mo

Story 08

SaaS company

Engineering

SaaS team ships 11 features in the quarter they used to ship 3, using Claude Code + Codex.

Before

14 engineers. Slow PR cycle. 9-day average feature lead time. Senior devs drowning in code reviews. Backlog 4 quarters deep.

After

Claude Code + Codex wired up via MCP to Linear/GitHub/Sentry/Postgres. AI drafts code, opens PRs, fixes failing tests. Engineers review and ship.

Feature lead time: 9 days to 1.8 days. Engineers reclaimed their evenings. Customer churn fell 31%.

Lead time

1.8 d

was 9 days

Shipped / Q

was 3

PR cycle

−74%

to merge

Churn

−31%

in 6 mo

Story 09

Trading firm

Legacy software

Trading firm eliminates 4 data-entry clerks using Computer Use on AutoCount + LHDN portal.

Before

AutoCount has no usable API. 4 clerks spent their days re-keying invoices then logging into LHDN MyInvois to file e-invoices. Error rate 6.2%. Mounting penalty risk.

After

Computer Use agent watches the screen, clicks through AutoCount, logs into MyInvois, fills the e-invoice form, captures the LHDN reference, writes it back. 24/7.

RM 240k/yr in payroll saved. LHDN penalty exposure eliminated. The legacy software didn't need to change.

Clerks

4 → 0

on this task

Error rate

0.1%

was 6.2%

Payroll saved

RM 240k

per year

Uptime

24/7

no shifts

The CFO conversation

Less payroll. More profit. Measured.

We don't sell innovation. We sell P&L outcomes. Here's how the math works.

Where savings come from

Manpower reduction. Agents and vision systems run 24/7. No shifts, OT, MC, training, attrition.
Error elimination. AI doesn't fat-finger invoices, miss defects, or mis-route shipments.
Cycle-time compression. What took days happens in minutes. Cash conversion accelerates.
Inventory and energy optimisation. Better forecasts cut waste; smart control cuts bills.
Vendor consolidation. One AI stack replaces 6 to 10 single-purpose SaaS tools.
Compliance automation. Eliminates weeks of audit prep per cycle.

Where new revenue appears

Faster sales motion. Agents qualify, follow up, book. Pipeline grows without hiring.
24/7 availability. Capture leads and orders at 2am in any language.
1:1 personalisation. Bespoke offers for every customer, not just top tiers.
AI-native products. Features competitors don't have. Premium pricing power.
Better decisions. Exec briefings driven by reasoning, not lagging dashboards.
Dormant customer reactivation. Agents re-engage every lapsed account automatically.

Back-of-envelope

If your business has just 10 hours per day of automatable work...

Year-one labour recovered

RM 280k

Plus error / opportunity cost

RM 140k

Total year-one impact

RM 420,000

Typical mid-market deployment pays for itself in ~5 months. Everything after that drops to the bottom line.

How we work

From idea to ROI, in weeks.

No 18-month consulting decks. We build it, ship it, and stand behind it.

01 / Week 1

Free AI Opportunity Audit

We sit with your team for 2 to 3 days, map every workflow, score each on automation potential and ringgit impact, and give you a ranked opportunity backlog. No charge if you commit to a pilot afterwards.

02 / Weeks 2-5

Pilot sprint

We build one highest-value use case end-to-end on real data. Live demo in week 5. You see it work before the bigger budget conversation.

03 / Weeks 4-8

Data and integration

Knowledge bases built. APIs wired. Edge devices provisioned. MCP connectors to your ERP, CRM, WhatsApp, SAP, MES, BMS, CCTV.

04 / Weeks 6-10

Hardening and testing

Red-team the AI on real edge cases. Set guardrails, approval gates, and cost caps. Compliance review for PDPA / ISO. It only goes live when it's safe.

05 / Week 10+

Go-live and change management

Phased rollout. Team training. SOP rewrites. Dashboards showing savings in real ringgit. We don't disappear after launch.

06 / Ongoing

Continuous improvement

Monthly model upgrades. Prompt tuning from production traces. New agent rollouts. Your AI stack gets smarter every quarter, automatically.

	VYROX	Big-4 consultants	Freelance / prompt-eng	SaaS "AI module"
Time to working demo	5–15 days	3–6 months	2–6 weeks	Day 1 (toy demo)
Time to production ROI	~5 months	12–24 months	Usually never	Marginal
Engineers who ship code	Always	Slide decks	One generalist	Their roadmap
Model agnostic (MCP)	Yes	Vendor preference	Whichever they know	Locked-in
Self-host / on-prem option	Yes (Llama, Qwen)	Often outsourced	Rare	No
Computer Use / Browser Use for legacy	Yes	No	No	No
Outcome-based pricing option	Yes	No	Sometimes	No
Eval harness & regression tests	Standard	Rarely	No	Opaque
Local team, Malaysia HQ	Yes	Mixed	Mixed	US/EU support
Typical engagement size	RM 25k–500k	RM 800k–5M+	RM 10k–80k	Subscription

Honest pricing

No retainer trap. No 50-page SoW. Clear scopes, fixed prices.

We never quote a project unless the expected ROI is at least 3× the fee in year one. You should never pay more than one-third of your year-one savings.

Tier 01 · Pilot

Proof in 4 weeks

RM 25k – 80k

One end-to-end use case on real data. Live demo, real users, measurable result. Decide on production after you see it work.

1 high-value workflow scoped & built
Real-data integration, not mock
Eval harness & success metric defined
Week-5 live demo with your team
Production-readiness assessment

Discuss a pilot

Tier 02 · Production · Most chosen

Ship to production

RM 80k – 280k

Full production deployment of one capability: LLM workflow, vision pipeline, agentic worker, or edge AI system. Hardened, monitored, on-call support.

Production-grade build, eval-tested
Integration to your ERP / CRM / WhatsApp
Cloud, on-prem, or hybrid deploy
3-month bug-fix & tuning warranty
Knowledge transfer to your team

Scope a project

Tier 03 · Platform

Full AI platform

RM 280k – 500k+

Multi-capability rollout across the business. LLM + Vision + Agentic, plus edge hardware where needed. Outcome-based pricing available.

3+ capabilities integrated end-to-end
Edge hardware sourcing & commissioning
Dedicated engineering pod (3–6 mo)
Outcome-based / gain-share contracts
Ongoing MLOps & model upgrades

Plan a rollout

Free first

AI Opportunity Audit, no commitment

45 minutes with a senior engineer. We score every workflow on automation potential and ringgit impact. You leave with a ranked backlog — even if you never hire us.

Book the audit →

Under the hood

An architecture that survives the next 5 model generations.

Every VYROX system follows the same blueprint. Models swap, capabilities expand, vendors come and go — your business logic stays put.

Layer 01 · Tools & data

Your stack, exposed safely

Postgres, ERP, file shares, CRM, WhatsApp, ticketing, cameras, sensors. Wrapped as MCP servers with audit logs, scoped permissions, and rate limits. Nothing is exposed that doesn't need to be.

Layer 02 · Reasoning

Best model for each task

Claude Opus 4.7 for complex multi-step reasoning, Sonnet for the agent loop, Haiku for the fast path, GPT-4o for vision-heavy work, Llama on-prem for sensitive workloads. Routed by a thin orchestrator — never hard-coded.

Layer 03 · Agents & skills

Your SOPs, as code

Each business process becomes a versioned, evaluable Skill. Procurement, dispute resolution, onboarding, quote-to-cash — written in plain language, runnable by every agent, instrumented end-to-end.

Layer 04 · Evals & guardrails

Production-grade trust

Every system ships with a golden dataset, regression tests, confidence thresholds, and human approval gates on irreversible actions. We measure hallucination rate as a hard KPI, not a vibes check.

Layer 05 · Observability

You can see everything

Token-level traces, tool-call logs, latency p95/p99, cost per action, eval scores per release. Grafana dashboards your team actually uses, plus alerts on accuracy regressions before customers feel them.

Layer 06 · Governance

PDPA, ISO, BNM, MOH-aligned

Role-based access, encryption at rest and in transit, optional air-gapped deploys. Full audit trail of every model output that touched a customer. Documentation packs for regulators in regulated industries.

# A typical VYROX agent call — model-agnostic, eval-bound, observable from vyrox.agents import Agent from vyrox.evals import golden_set agent = Agent( model="claude-opus-4-7", # swap to any provider via MCP tools=["postgres", "whatsapp", "erp.invoice"], skill="dispute_resolution_v3", # versioned SOP eval=golden_set("customer_disputes_2026Q1"), guardrails={"approve_above_rm": 5000}, # human gate ) result = agent.run(message) # traced, logged, billable per action

The honest answers

Questions you're actually wondering.

Will AI replace my staff?

It will replace specific tasks: the repetitive ones. Your people get redeployed to higher-value work. Most clients reduce hiring rather than firing. They grow output without growing payroll.

Is our data safe? Can we keep everything on-premise?

Yes. We deploy open-weight models (Llama, Mistral, Qwen) on your own GPUs or private cloud for sensitive workloads. Nothing leaves your perimeter. PDPA/ISO documentation provided.

What does a project actually cost?

Pilots typically RM 25k to 80k. Production deployments RM 80k to 500k+ depending on scope, data complexity, and infrastructure. We always quote against expected ROI. You should never spend more than 1/3 of year-one savings.

How do you stop AI from making things up?

Grounded answers with citations from your documents. Structured outputs validated against schemas. Golden-dataset testing. Confidence thresholds. Human approval gates on anything irreversible. We measure hallucination rate as a hard KPI.

We don't have clean data. Can we still do this?

Yes, that's exactly what AI is good at. It copes with messy PDFs, scanned receipts, handwritten DOs, inconsistent schemas. We build the data pipelines as part of the engagement.

What if a better AI model launches next year?

Your system is built model-agnostic on MCP. Swapping GPT-4o for Claude 5 or Llama 4 is a config change, not a rebuild. You benefit from every frontier release automatically.

Do you handle hardware too (cameras, edge GPUs, sensors)?

Yes. NVIDIA Jetson, IP cameras, IoT gateways, PLCs, robotic arms. Sourcing, integration, on-site commissioning. End-to-end delivery.

How fast can we see a working demo?

For most use cases, 5 to 15 working days from kick-off. We believe in showing, not telling.

What if my industry has strict compliance (banking, healthcare, government)?

We deploy fully on-prem with air-gapped options. Audit logs, role-based access, encryption at rest, BNM/MOH-aligned architectures available. Several clients operate in regulated sectors.

Do we have to commit to one AI vendor (Anthropic, OpenAI, etc.)?

No. We build everything model-agnostic using MCP, the open standard adopted across the industry. Today we may use Claude Opus 4.7 for reasoning, GPT-4o for vision, Llama 3.3 on-prem for sensitive workloads. Tomorrow we swap any of them with a config change.

Can AI really automate apps with no API (SAP, AutoCount, LHDN portal)?

Yes. Using Computer Use (Anthropic) and Browser Use, the agent literally looks at the screen, moves the mouse, types, and clicks, exactly like a human operator, just faster, 24/7, and with a full audit log. We've deployed this on AutoCount, MyInvois, SST portal, legacy Windows ERPs, and dozens of vendor portals.

What is MCP and why do you keep mentioning it?

MCP (Model Context Protocol) is an open standard, created by Anthropic and now adopted by OpenAI, Google, Microsoft, Cursor, and the broader industry. It lets AI agents securely connect to your tools, databases, and APIs. It matters because it eliminates vendor lock-in.

What happens when the AI gets it wrong?

Every irreversible action passes through a confidence threshold and (where appropriate) a human approval. Wrong answers are logged for retraining. Kill-switches let you pause any agent instantly. We engineer for graceful degradation, not just success.

AI that runs your business.

Not just talks about it.

Certified, accredited and partnered where it counts.

Your business is leaking money on work AI was built to handle.

A decade of shipping. Now multiplied by AI.

Four capabilities. One stack. Yours.

A digital employee who has read every document you own.

Eyes that understand what they see, not just record.

Workers that act, not just answer.

Intelligence that moves atoms, not just bits.

All four working together is where the magic happens.

AI doesn't replace your judgement. It removes the work that gets in the way of it.

If you do work, AI can help you do less of it.

Built on the same agent stack Anthropic, OpenAI, and Google ship.

You don't need to learn any of this. You just need to know we already have.

The same tools Anthropic, OpenAI & NVIDIA ship on. Wired into your business.

Wired to the tools your business already runs on.

We ship the hardware too. Sourced, integrated, commissioned.

Same business, same headcount, completely different operation.

We didn't pivot to AI. We grew into it.

Less slideware. More working systems.

Engineers who built it. Operators who shipped it.

Senior ML / agent engineers, KL-based, on-site & remote

Independent press coverage across the region.

Your industry. Already solved.

The operating system for modern clubs.

Member taps WhatsApp at 14:02. By 14:03, the agent has booked the court, charged the wallet, assigned a coach, prepped the F&B order, opened locker 12, and queued a tow-truck reminder for the member's car expiring at 18:00.

WhatsApp booking agent

Member onboarding & KYC

F&B order taking

AI snooker / pickleball scoring

Coach video feedback

Smart locker, racquet & cue rental

Renewal & dormant reactivation

Energy & HVAC autotune

Incident triage & safety

Visitor / guest management

Auto monthly statements & reports

Tournament & league orchestration

Pick your pain. We've got the fix.

"We pay too many people to do repetitive work."

"Humans miss defects after a few hours."

"We get drowned in customer messages."

"Equipment fails without warning."

"Documents are a mess."

"Cameras record but no one watches."

"Sales follow-up leaks leads."

"Energy and utility bills keep climbing."

"We have data. We don't have answers."

"Audits are a nightmare."

"Our dev team is overloaded and slow."

"We're stuck on a legacy system with no API."

Real businesses. Real numbers.

Electronics OEM replaces an 18-person QA team with 4 smart cameras.

Home-appliance retailer handles 1,400 daily WhatsApps with 4 people instead of 12.

Drive-thru chain replaces night-shift order takers with a multilingual voice AI.

28-storey office tower saves RM 612k in year-one utility bills.

Insurer cuts claim processing from 5 days to 4 hours.

Solar farm replaces a 3-engineer inspection team with an autonomous drone.

Dental group cuts no-shows by 40% and reactivates 1,400 dormant patients.

SaaS team ships 11 features in the quarter they used to ship 3, using Claude Code + Codex.

Trading firm eliminates 4 data-entry clerks using Computer Use on AutoCount + LHDN portal.

Less payroll. More profit. Measured.

Where savings come from

Where new revenue appears

If your business has just 10 hours per day of automatable work...

From idea to ROI, in weeks.

Free AI Opportunity Audit

Pilot sprint

Data and integration

Hardening and testing

Go-live and change management

Continuous improvement

Engineers who ship. Not consultants who slide.

Why most AI projects fail. Why ours don't.

No retainer trap. No 50-page SoW. Clear scopes, fixed prices.

Proof in 4 weeks

Ship to production

Full AI platform

AI Opportunity Audit, no commitment