We build AI agents that
actually work.

Lanvar is a small AI engineering studio based in Montreal. We design and ship custom agentic systems for businesses — built on a methodology of execution lineage, not chat threads with a GPT subscription.

The problem we solve

Most AI agents fail in production. Not because the models are bad, but because the systems around them are built wrong. State lives in context windows. Every change reruns everything. Auditability is a screenshot. When something breaks at 3 AM, nobody can reproduce it.

We fix this by treating agentic work as a build graph — a directed acyclic graph of artifact-producing computations. Each node has explicit dependencies. Each output has a stable boundary. Runs are replayable. Changes trigger selective recomputation. The system is legible to the engineers who inherit it.

How we work

We start with a free one-hour audit. We study how your business actually works, identify the highest-leverage agent opportunities for your specific workflows, and write you a report. Yours regardless of whether you hire us.

If you decide to engage, we run a four-week pilot on a fixed fee. Build a custom agent tailored to your processes, your data, your team. Ship to a small group. Measure against baseline. Then we harden it for production — observability, evals, retry strategy, audit logs — and hand off the code. You own it completely.

From there, you choose: maintain it yourself (we build it to be simple and well-documented), or keep us on affordable ongoing support. No pressure, no lock-in. The system is truly yours.

Who's behind Lanvar

An engineer who's been building agentic infrastructure inside a Fortune 500 enterprise — the kind of environment where a wrong answer costs real money and "the AI did it" isn't an excuse anyone accepts. Lanvar is the practice that came out of that work, organized around a methodology that solves the real problems we kept hitting.