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Connic

We spent our time on everything
except the agents.

Connic is one system for building, deploying, and running AI agents. We started it in Munich in 2025, after living through exactly that at our last company.

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Founded
2025
Based in
Munich, Germany
Deployed in
European Union
Models
Any provider
Why we started

The agents were the easy part

At our last company we put AI into production the way most teams still do. Frameworks for running an agent were never the problem. There were plenty, and all of them were early: unstable, breaking on minor upgrades, moving faster than anything we wanted underneath a production system.

Everything around them we built ourselves. A tracing product. Custom connectors out to every system we touched. Ingestion, some written, some bought. A database. A test harness. Deploy pipelines.

By the end, the agents were what we had spent the least time on. The most valuable part of the product got whatever the plumbing left over, and scaling it was the hardest work we did.

Connic is that entire stack as one product. One thing to adopt, one thing to learn, and it scales to millions of runs without extra configuration.

What it takes to run one agent
Assembled
Agent runtime
Connectors
Ingestion
Database
Vector search
Tracing
Testing
Deploy pipelines
Connic
Agent runtime
Connectors
Ingestion
Database
Vector search
Tracing
Testing
Deploy pipelines
Why Europe

Everything that came close was American

When we went looking for something that already did this, everything close was American. There was nothing comparable in the EU then, and there still is not much now.

So we built for European teams from the first commit. A German entity, a team in Munich, a platform deployed in the EU. Compliance has been part of the product from the first commit, not something added after a customer asked.

That does not make this a European-only product. Teams use it from anywhere and it should win on the merits. It means EU teams never have to choose between the tool they want and the rules they live under.

Principles

What we keep coming back to

01

Your time belongs to the agents

We own the tracing stack, the connector you would otherwise write twice, and the pipeline holding it together. If you are debugging our infrastructure, we have failed at our half of the job.

02

Compliance ships by default

Guardrails, approvals, audit trails, and EU deployment ship with the platform. You do not bolt them on the week after legal asks.

03

Agents are software

They should be versioned, tested, traced, and rolled back like anything else you ship. A prompt in a notebook is a prototype. Production is a different job.

04

Sovereignty is a starting condition

Where your workloads run, and who you contract with, should be settled before you build, not renegotiated during an audit. For European teams, that answer should already exist.

Where to go next

Documentation

Ship your first agent in under five minutes.

Pricing

Per-run and per-unit rates. No per-seat charges.

Connectors

Wire agents to the systems you already run.

Compare

How Connic sits against the rest of the field.

EU AI Act

What the regulation asks of you, and of us.

Blog

What we are building, and what we are reading.

Frequently Asked Questions

Connic replaces the stack teams normally assemble to run AI agents. Engineering teams define agents in YAML, write tools as standard Python functions, and deploy with a git push. One system covers execution, scaling, connectors, ingestion, observability, evals, testing, and storage, instead of a separate tool for each.

Connic is based in Munich, Germany, and contracts through a German entity. The platform is deployed in the European Union.

Connic was founded in 2025 in Munich, Germany.

Any of them. Connic supports the major providers, self-hosted models, and other third-party LLMs. Connic is bring-your-own-key: you connect your own credentials, and Connic never resells model capacity or marks up tokens.

No. Teams use Connic from anywhere. The platform is deployed in the EU, which matters if you have European data residency requirements, and is where it runs if you do not.

Software engineering teams and SaaS companies moving AI agents from prototype to production. Typical users are backend developers adding agent features to an existing product, and teams that would otherwise assemble and operate this stack themselves.