Use AI aggressively, without irreversible dependencies.
Most companies adopt AI one vendor decision at a time. Each decision is small. Together they add up to lock-in: prompts tuned to one model, data in one cloud, workflows nobody can audit, and a renewal you cannot walk away from.
We make the opposite the default. Models will change. So will providers, prices and the rules. Every agent we deploy runs on your context, under your rules, and can move to another model when the market does.
- Context
- Understand the company: its data, its market, its constraints and its actual problem.
- Ridge
- The high line you navigate from. It shows you the terrain, and it holds while the terrain moves.
The landscape below will keep changing. Your context is the part you own.
Engineers may recognise ridge regression: a penalty that stops a model leaning too hard on any one input. We take the same view of providers.
You ask for one workflow. You keep an operating layer.
Clients usually come to us with one painful process to automate. We deliver that. Underneath it, we install the layer every later agent will need, so the second project costs less than the first and no provider owns the stack.
Company context
Your documents, data and rules, structured once and reused by every agent.
Agents
Automate the workflows that cost you the most, starting with one.
Models and tools
Routed per task, and swappable without rewriting the agents.
Governance
Permissions, evaluations, cost tracking and a record of every decision.
Human validation
People approve what matters before it reaches a customer.
What you buy first
One workflow automated with AI.
What we install with it
Context, permissions, evaluations, model routing, observability, human approval and vendor abstraction.
What you own at the end
An AI operating layer that is not tied to OpenAI, Anthropic, Mistral or Microsoft.
Titral, by Context Ridge
Titral proves you can change AI provider before you need to.
Public benchmarks compare models on standard tests. Titral compares them on your production traffic, so the answer is about your applications, not a leaderboard.
Observe
A light SDK, or the logs you already keep. Your applications keep running as they do today.
Replay
A sample of real sessions runs on alternative models and providers, including European and sovereign options. Optimal experiment design picks the sample, so results hold across all of production without testing every combination.
Decide
A verdict per application: what can migrate, to where, and what it does to quality, cost, latency and data residency.
AI Exit Test
Claims triage assistant
Illustrative, to be measured
Three of four alternatives clear the quality bar you set. Recommended exit path: the European provider, 38% cheaper, with data kept in the EU.
| Alternative | Quality vs. current bar 95% | Cost | p95 latency | Data stays in | Verdict |
|---|---|---|---|---|---|
| European providerEU-hosted API | 97.4% | −38% | 1.9 s | EU | Ready to migrate |
| Open-weight modelSovereign cloud, France | 95.8% | −52% | 2.4 s | France | Migrate after prompt changes |
| Second US providerUS-hosted API | 99.1% | −12% | 1.6 s | US | Ready, data stays in the US |
| Small open modelOn your own servers | 81.2% | −71% | 0.9 s | On-premise | Not yet: fails 6 of 40 edge cases |
Financial entities must keep exit strategies for the ICT services behind their critical functions, and those plans must be tested.
DORA, Regulation (EU) 2022/2554, article 28(8), paraphrased
AI Exit Test
One application, one verdict. The report above, on your data.
Continuous Exit Assurance
The test reruns when models, prices or your workloads change, so the answer stays current.
We are not AI consultants, and we are not an agency. We do not sell engineering days.
We install something you own, measure whether it works, and leave you free to change your mind.Une IA qui vous laisse changer d’avis.
Who you will work with
Murilo Vasconcelos Andrade
Former quant at Morgan Stanley and Santander. Founded Studiare, acquired by Kroton in 2015, then AIO, an AI learning platform used by more than 70,000 students. École polytechnique.
Thiago Sabetta
Researcher in statistical physics at CEA Saclay, then data at Capital Fund Management. Co-founder and CTO of AIO. École polytechnique.