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Custom AI agents, built inside your business

An Agentica engineer learns the workflow with your team, builds against the systems it uses, and proves the agent beside the current process. The first deployment is scoped around one measure and one operating boundary.

Built for your context

When off-the-shelf doesn't fit your workflow

The valuable workflows are often shaped by your own data, rules, and accumulated judgment. We map that context first, then decide what an agent can own safely.

The engagement

Embedded engineers, a scoped pilot, then production

  1. Embed & map

    An engineer sits with your team, learns the workflow, and identifies the highest-ROI place to start.

  2. Pilot in shadow

    We build against your real data and run the agent alongside your existing process, so nothing breaks while we prove it works.

  3. Ship to production

    Once it clears your success metric, the agent goes live on your infrastructure, monitored and supported.

  4. Reuse what worked

    Proven underlying components carry forward, making the next deployment faster without carrying your data with them.

Built for your context

What you get

  • Production engineers

    Engineers who ship production code on-site, not consultants who ship slides.

  • ROI before novelty

    Agents aimed at high-volume, repetitive, cognitively expensive work, measured against a metric you set.

  • Proven components

    Every build draws on Agentica Harness and reusable components, so you pay less for what we've already solved.

Use cases

Real deployments. Measurable outcomes.

  • Agents that answer on your own data, hand over cleanly when they should, and report what they could not solve.

  • Every document checked against the rules you actually operate under, with the reasoning kept for the audit.

  • Usage watched and capped per team, so a longer chain of reasoning never turns into a surprise on the invoice.

  • Being built with pilot customers now. It lands here once it has run in production.

  • Being built with pilot customers now. It lands here once it has run in production.

  • 3/4 X

    Average return our clients see on AI investment

  • 100%

    Source code ownership yours on day one, forever

Pricing

Priced to budget, not to a meter

Deployment

One-time fee

Subscription

Fixed fee

A one-time deployment fee to build and ship the agent. Then a flat subscription for hosting, monitoring, support, and improvement. We don't meter tokens, so your bill doesn't move because an agent reasoned longer or ran more often.

Not sure about the pricing and how it works?

Talk to our team

Packages

Custom agents, practically

What's a forward-deployed engineer?

An Agentica engineer who works with your team, on-site where it helps: they learn the workflow, build against your real systems and data, and ship the agent into production.

How is this different from a consultancy or software house?

We don't hand over a report or a codebase and leave. Our engineers build the agent, prove it beside your current process, and run it in production, and the next deployment starts from components that already work.

How long until a custom agent is in production?

The first deployment is scoped around one workflow, one measure and one operating boundary. It runs in shadow until it clears that measure, then goes live on your infrastructure.

Who owns the agent and our data?

You do. The source code is yours from day one, and your data stays inside the agreed boundary. Reusable components carry forward without carrying your data with them.

What does it cost?

A one-time deployment fee to build and ship the agent, then a flat subscription for hosting, monitoring, support, and improvement. We don't meter tokens.

Bring us your hardest workflow

Tell an engineer what your team does by hand today. We'll tell you what an agent could take off their plate, and how fast.

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