Nous aidons les entreprises à adopter l'IA sans le bruit ni la complexité.
Fondée en 2024 par une petite équipe d’ingénieurs, opérateurs et designers.
Most companies we meet don’t need more AI demos. They’ve seen them. What they need is someone to sit with them, understand how their business actually works, and figure out where AI quietly belongs — and where it doesn’t.
The hard part of AI integration isn’t the model. It’s the seam between the model and the work. Permissions, data quality, edge cases, ownership, the moment a human takes over. That’s the part the average vendor skips.
We don’t. That’s the entire reason Integra AI exists.
We treat AI as a piece of operational design — one that has to make peace with your tools, your team, your tone, and your governance. When that’s done well, it disappears into the work. That’s the bar.
We treat AI integration as a design problem first and a technical one second. The work proceeds in three deliberate stages — slow enough to be right, fast enough to matter.
We sit with the people doing the work. We map the systems, the data, the handoffs, and the friction. The output is a shared picture of where AI actually belongs — and where it doesn’t.
We prototype in days, not quarters. Once a workflow is working in the wild (with real users, real data, real edge cases), we harden it into a production system on infrastructure you own.
Tools age fast in this space. We hand over with documentation, training, and a written evolution plan — then stay reachable as models, vendors, and your business change underneath you.
These aren’t slogans on a careers page. They show up in how we scope work, what we say no to, and how a project ends.
We never start a build before we’ve sat with the team doing the work. Half our engagements end in a different scope than they started — and that’s the point.
We pick the model, the platform, and the stack that fit your situation — not our resale margin. We hold no kickbacks, no reseller agreements, no quotas to hit.
If AI is the wrong tool for the job, we’ll tell you. Some of the most useful work we’ve done has ended in “this is a process problem, not an AI one — here’s who can help.”
We ship on infrastructure you own and code you can read. Nothing locked behind our login. If we vanish tomorrow, your system still runs Monday.
For consequential decisions, AI drafts; a human signs. We design the seam carefully. Confidence scores, review queues, audit trails — the unglamorous parts that matter.
Success looks like fewer tickets, faster intake, calmer Mondays — not a flashy demo. We measure value in hours returned and decisions made, not novelty.
There is a particular shape to the AI conversation in 2026: a lot of capability, a lot of vendors, and a lot of nervous executives. Boards want to know “what is our AI strategy.” Teams have been told to “experiment.” Pilots get started. Most quietly stall.
The pattern we see isn’t a failure of the model. The models are extraordinary. The pattern is that the work around the model — the messy human, operational, governance work — never got done. The bot was deployed but no one defined who owns it. The automation went live but no one mapped the edge cases. The audit was great but the recommendations got filed.
We think this is a great moment for businesses that take integration seriously. The marginal cost of intelligence keeps falling. What stays scarce — what compounds — is the work of making it land. Of stitching it into how a company actually decides, drafts, sells, supports.
That’s the work we want to be doing for the next decade. If that sounds like something you’d value, we should talk.
Bring a problem you’ve been circling. We’ll tell you honestly whether AI is the right tool for it, what the smallest useful version looks like, and what it would take to ship.
Calls are run by a senior consultant, not a sales team. We come prepared.
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