Done-for-you AI agents for product & platform teams
We deliver the result —
a production AI agent in your platform.
Your team can ship a demo in a weekend. Making it work well — grounded in your data, proven not to make things up — is months of unglamorous work.
We have done exactly that in production. We deliver it to a measured bar, then hand it to you.
Same question, side by side — a live comparison
A quick DIY build — guesses, can’t check stock, delivery, or close.
Consults, solves the delivery, and closes the sale.
Why trust us with the result
Not a black-box agency. A real platform, proven in production.
We don’t trade on borrowed logos. We give you what you can verify yourself — the source, a running instance, and the licence terms.
Open-source core
The engine your agent runs on is public on GitHub — BSL 1.1. Inspect the runtime before you trust it.
View the engine on GitHub →Shipped in production
We have taken a grounded agent over a real device-fleet platform all the way to production — the hard tuning, integration, and deployment included.
How we work →Dogfooded in Cloud
syntheticbrew.ai runs on the same engine and grounding stack we deliver to you. We use it ourselves, every day.
See the platform →Everyone wants product AI. Almost nobody ships it well.
The demo is easy now. Production — answering right, every time, over your real data — is where projects die.
The demo lies about being done
A weekend prototype impresses the board, then stalls for months. The gap from "it answered once" to "it answers right, every time" is the whole project.
Hallucinations kill trust
A confident wrong answer inside your product is a liability, not a feature. One invented record and your users stop believing the agent.
The hard part is making it work well
Not writing files — tuning prompts, designing the knowledge graph, building the tools, wiring it together, deploying it, and proving it does not make things up. That is where the months go.
A clear line: what we deliver, what stays yours
We do the hard, unglamorous part that makes it work. Everything specific to you stays yours — to own, change, and run.
We prove it, not just claim it. Before launch we stand up an eval harness against your real data — every answer scored for groundedness and correct citation. You sign off on numbers, not a vibe.
How it plugs into your platform — we never enter your stack, the agent reaches it through a clean contract
Grounded answers flow back into your product UI or your support console — you build the surface, we deliver the brains behind it.
How we work — start free, ship to a bar, then it is yours
Fixed scope, fixed price, objective acceptance. You are never locked into an open-ended engagement.
Fit call
Free, 30 min
We map your data, APIs, and the first agent — and tell you honestly whether it is worth doing. No slides.
Scope & fixed quote
You decide
A concrete scope and a fixed price. No open meter, no surprises. You commit only if the number works.
Build & tune
The hard part
We go into the work: MCP tools, knowledge graph, prompts, assembly, deployment — tuned until it answers right.
Acceptance bar
Measured, not vibes
It ships only when it passes evals on your real data: grounded, cited, and refusing when it should. You sign off on numbers.
Handover
It is yours
Config-as-code in your repo, deploy chart, docs, admin access. You run it on your infra. 60-day warranty on platform defects.
Why not just build it, or buy a hyperscaler?
The honest comparison. We will tell you when building in-house is the right call.
You keep control. We are never in your critical path.
We deliver and hand over. The agent runs in your environment, on an open core — no dependency on a young vendor to keep the lights on.
Runs on your infrastructure
After handover it lives in your environment, behind your auth. Your data never leaves your control — and never trains a model.
You own it, not us
Config-as-code in your repo, taxonomy and prompts yours to change. No dependency on us to keep it running.
Open-source core
The engine is public (BSL 1.1). Inspect the runtime before you trust it. If we vanished tomorrow, your agent keeps running.
Signed, tamper-proof auth
Every request is cryptographically signed (Ed25519). Bring your own LLM keys — used per request, never stored or logged.
EU data residency, GDPR DPA, and a security questionnaire — handled during scoping.
One fixed fee for the result. Support only if you want it.
Scoped and fixed after a free fit call — no open meter, no mandatory subscription.
We deliver a working, grounded agent in your platform — proven, deployed, and handed over.
- ✓Free scoping fit call
- ✓MCP tools + knowledge graph + prompt, tuned
- ✓Eval bar acceptance on your real data
- ✓Deploy + handover (config-as-code, docs)
- ✓60-day warranty on platform defects
Want us on call after handover? Changes, tuning, and priority fixes — never required, never bundled.
- ✓Ongoing changes & new tools
- ✓Grounding re-tuning as data drifts
- ✓Priority response
- ✓Cancel anytime
- ✓Or run it entirely yourself
The things technical buyers ask first
Do you host and operate it? +
No — and that is deliberate. We implement it to a proven bar and hand it over; it runs on your infrastructure, behind your auth, under your control. No dependency on a young vendor sitting in your critical path. If you want us on call afterwards, that is an optional support retainer, never bundled into the base.
We have no ML team — can we actually run it after handover? +
Yes. The agent is a service plus config-as-code — taxonomy, prompts, and tools in your repo — that your backend engineers run like any other service, with the deploy chart and docs we hand over. Day-to-day operation needs no ML specialist. The one ML-flavoured task is re-tuning grounding as your data and schemas drift; that is exactly what the optional support retainer covers if you would rather not own it.
Why pay you if our team could build this with AI? +
You could scaffold a demo — most teams can now. The work we sell is the part that takes months: tuning the knowledge graph for full recall, getting the prompt to use tools and refuse when data is missing, building and hardening the integration, and proving it does not hallucinate with evals on your real data. We have done exactly this in production. You get the result in weeks, your engineers stay on your roadmap.
What exactly do we end up owning? +
Everything specific to you — your MCP tools, taxonomy, prompts, and the whole config as code in your repo, plus the deploy chart and docs. You can change it, redeploy it, or take it further without us. The open-source engine underneath is yours to self-host.
What if we do not have a clean API? +
Common. If your systems are not cleanly exposed, building the MCP connector is an add-on we scope in the fit call — or your team builds it against our contract. Either way there are no surprises after the quote.
How do you handle the risk that we are not happy with it? +
The engagement is staged and the acceptance bar is objective: it ships only when it passes evals on your real data. You see the numbers before you sign off. And the fit call is free, so you learn whether it is even worth doing at zero cost.
What happens if you go out of business? +
Your agent keeps running — it is on your infra, the config is yours, and the engine is open-source (BSL 1.1). That is the point of this model: you are never dependent on us to keep the lights on.
See if a grounded agent is worth building for you
A free 30-minute fit call. We map your data and APIs to a concrete agent, tell you honestly whether it is worth doing, and what the result would take.
No slides, no obligation — a working session on your actual data and APIs.