AI agent use cases · Malaysia & Singapore

    AI agent development, shown use case by use case

    For each use case we show the manual workflow, the agentic redesign, how we build the loop on Claude, and how we prove it works — then build it for you.

    Member of the Anthropic Claude Partner Network. We use the agent patterns, not just the buzzword.

    Use cases across finance, insurance, retail & F&B, procurement & manufacturing, legal, HR and customer service.

    Our agentic development process

    Built on Anthropic's agent guidance and the Agent GPA eval framework. Building Effective Agents · Agent GPA

    1. 1Frame the problem
    2. 2Map the manual workflow
    3. 3Design the agentic workflow
    4. 4Build the loop on Claude
    5. 5Single model or multi-agent
    6. 6Evaluate & measure
    7. 7Deliver, POC-first
    Retail & F&BAvailable
    prompt chaining

    Order processing agent

    Take customer orders on WhatsApp — capture items, confirm details, and push them straight into your system.

    ValueBuild effort
    See how we'd build it
    routing

    Product enquiry agent

    Answer product questions instantly on WhatsApp — availability, specs and price — from your own catalogue.

    ValueBuild effort
    See how we'd build it
    evaluator-optimizer

    Corporate communications consistency agent

    Turn one approved message into on-brand, fact-consistent versions in every language — checked, flagged, and ready for sign-off.

    ValueBuild effort
    See how we'd build it
    Finance & accountingAvailable
    routing

    Cash application agent

    Match incoming bank receipts and POS settlements to open invoices and clear them — automatically, with only genuine exceptions going to a human.

    ValueBuild effort
    See how we'd build it
    Finance & accountingAvailable
    evaluator-optimizer

    Bank reconciliation agent

    Reconcile the bank statement against your cash book line by line — matching both directions, posting bank charges, explaining timing differences, and flagging genuine discrepancies.

    ValueBuild effort
    See how we'd build it
    orchestrator-workers

    Insurance claims agent

    Match a claim against the policy, the report and the receipts — and flag what doesn't add up.

    ValueBuild effort
    See how we'd build it
    evaluator-optimizer

    Contract review agent

    Compare a signed contract against the agreed template and surface the clauses that changed.

    ValueBuild effort
    See how we'd build it
    Human resourcesAvailable
    parallelization

    HR verification agent

    Verify that a candidate's certificates, references and stated history line up — before the offer goes out.

    ValueBuild effort
    See how we'd build it
    HR & workforce operationsAvailable
    routing

    Leave & shift-cover agent

    Take leave and MC requests, check them against policy and balances, route for approval, and find qualified cover for the shift — end to end.

    ValueBuild effort
    See how we'd build it

    Don't see your use case?

    If your team spends its day reading, checking and matching documents or requests by hand, there's probably an agent for it. Tell us the problem.

    Tell us the problem

    AI agent development — common questions

    How do you build an AI agent for a business in the region?
    We frame the problem, map the manual workflow, design the agentic loop, and build it on Claude using the Claude Agent SDK and the Model Context Protocol (MCP) — POC-first, so you see a working agent before committing to the full build.
    How much does AI agent development cost?
    A first, well-scoped agent typically lands in the low tens of thousands of Ringgit, plus running costs for the Claude model and infrastructure. You can model the running cost for your team with our Claude cost calculator.
    Which industries use these AI agents?
    Finance, insurance, retail and F&B, procurement and manufacturing, legal, HR and customer service — anywhere teams read, check and match documents or requests by hand.