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Dispatch Commander

Dispatch spreadsheets replaced by a route solver

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  • Securing AI agents: permissions, prompt injection and audit trails

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  • What an AI model really costs in production

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  • Getting retail AI ready for peak season

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Strategy

Find where AI pays off.

We find the work agents can take on, rank it by return and prove the first one.

Book an AI audit

Most AI projects stall before they start.

  1. Audit

    Find the work agents can take on.

    A look at your processes, data and tools.

  2. Prioritize

    Rank use cases by return.

    Use cases ranked, with a business case for each.

  3. Prove

    Test the first one before you scale.

    A prototype or MVP in front of real users.

Where agents pay off.

Start where the work is repetitive and the rules are clear.

  • Support agent with a headset smiling at her computer

    Customer service

    Answers from your own docs. Hands off to a person when it should.

  • Man working on a laptop at a standing desk in a warehouse

    Operations

    Documents, tickets and approvals handled end to end.

  • Two colleagues giving each other a high five at a desk

    Sales

    Leads qualified, quotes drafted, CRM kept current.

  • Tax documents, a calculator and a phone on a dark desk

    Finance and back office

    Invoices, reconciliation and reporting without the copy-paste.

Hands sketching a wireframe in a notebook on a dark desk
Where do we start?

Not sure where AI pays off?

Start with an audit. We find the work agents can take on.

  • Roadmap and ROI
  • Use case priorities
  • Proof-of-concept scope
Book an AI audit

Know the use case? Prove it first.

  • Developers working side by side at a long desk

    Prototypes and MVPs

    A deployable product in 4–8 weeks, so you learn before you scale.

    • Interactive prototypes and clickable demos for stakeholder validation.
    • Lightweight MVPs with core flows and real data to test assumptions fast.
    • Quick iteration cycles to test, gather feedback, and pivot before full build.
    Book an AI audit
  • Engineer reviewing code at a workstation in a dark room

    AI risk review

    Data, privacy and model risks checked before you build.

    • Prompt injection and jailbreak mitigation with input sanitization and guardrails
    • Model output validation and guardrails to prevent harmful or off-brand responses
    • Data lineage and sensitive data protection for AI pipelines and training data
    Book an AI audit

What you get.

  • Roadmap

    A roadmap and ROI

    Where to start, what it costs and what it returns.

  • Priorities

    Use cases, ranked

    Ordered by return and effort, with the first one picked.

  • Scope

    A proof-of-concept scope

    What to build first, scoped and priced.

Built, then run by the same team.

  • Senior-led from start to finish.

    The people you meet build it.

  • We run what we build.

    easyvisas is live, and we operate it.

  • Fixed price, scoped upfront.

    Scope and price agreed before we start.

Person working across several monitors

What we've shipped

All case studies

easyvisas – fully AI-powered immigration processing

Agentic AI backend with RAG over immigration policy and 12,000+ historical cases — automated document intake through decision support.

Read the case study

Questions

Where do we start if we are not sure AI pays off?
Start with an audit. We tell you where AI creates value, with a roadmap, ROI and a priority order for use cases.
How quickly can Meterra ship a working MVP?
For a well-scoped MVP — defined user stories, agreed tech stack, available design direction — we typically deliver a deployable product in 4–8 weeks. We use iterative two-week sprints, share progress continuously, and prioritize the core user flows that prove the concept so you can begin user testing as quickly as possible.
How long does it take to build and deploy an AI agent?
It depends on the scope. We agree the timeline and a fixed price before we start. Every plan includes testing, monitoring and deployment.
How are engagements scoped and priced?
Fixed price, scoped upfront: scope and price are agreed before we start. Timelines are estimated during discovery.