The scarce thing in AI isn’t capability. It’s trust.
Models got good fast. The ability to deploy them responsibly didn’t. Most teams ship AI as a black box — a prompt goes in, an answer comes out, and nobody can say what happened in between or what it cost. You can’t put that in front of your customers. We built the runtime that you can.
Choices we made, including the costly ones.
A position is only credible if it has a price. Here’s what building for trust forced us to do — and what we gave up for it.
Everything on the record
Every model call, tool invocation, approval, and euro is a persisted, replayable event — even though it would be faster to ship a thin proxy that forgets.
We keep the receipts so you can answer “why did it do that?” a month later.
Your data stays yours, in Europe
Agent state lives in European infrastructure and is yours to export or delete — even when US infra is cheaper and the lock-in would be stickier.
Sovereignty you can hand to your own customers as a guarantee, not a vibe.
Isolation per end-user, by default
Each smith is sealed — its own memory, tools, and history — even though shared context would be simpler to build and cheaper to run.
One user's data can never surface in another's. The boundary is the token.
Standards over proprietary
The primary surface is OpenAI-compatible and tools speak MCP, even though a bespoke protocol would lock you in harder.
Keep the SDK you have. Leave without a rewrite if we're not the fit.
You’re choosing between three things.
Not us versus a named competitor — that dates fast. The honest comparison is against building it yourself on a raw model API, or bending a general-purpose agent framework into a multi-tenant product.
| Roll your own | Generic agent framework | Ingram Cloud | |
|---|---|---|---|
| A private agent per end-user | |||
| Replayable audit trace of every action | |||
| Human approval before sensitive tools | |||
| Per-user cost attribution & budgets | |||
| Server-side tool & OAuth storage | |||
| EU data residency & ownership | |||
| Time to first production agent | weeks | days | an afternoon |
Read it before you believe it.
We document what ships, not what’s aspirational. The whole API is public, every page has a raw-Markdown twin for your coding agent, and the OpenAPI spec is generated from the live service.
- You're putting an agent in front of your own customers, not just yourself.
- Each user needs their own memory, tools, and history.
- You need to answer, later, exactly what the agent did and what it cost.
- Where data lives and who owns it is a question you have to answer.
- You need one shared chatbot and don't care what it did between turns.
- A single prompt to a model API already does the job.
- There's no end-user to isolate — it's an internal one-off script.
If that’s you, you don’t need us — and we’d rather say so.
Build on infrastructure you can trust — and leave.
Standard formats in, your data out anytime. The best reason to trust us with production is that you're never trapped here.