Stop burning money on AI tools that break. We build custom agents for your specific workflows — you own it completely, it costs 70% less to run, and you decide if you want to maintain it yourself or let us handle it.
Every week another agent platform launches with a slick demo and a 47-step onboarding flow. Every LinkedIn post tells you your competitors are already ahead. Your inbox is full of consultants pitching "AI strategy" who won't tell you what would actually work for your business — because that takes time, and time is the one thing you can't give them for free.
So you do what most small businesses do. You sign up for a tool. You try it for two weeks. It half-works. You can't tell if the broken half is the tool, the model, or your team. You give up. You go back to running the business by hand. Next month, another tool launches. And the loop starts again.
You don't need another tool. You need someone to look at your business and tell you the truth about which agents would actually move the needle — and which ones wouldn't.
Every AI tool demos beautifully. Then you try to use it for your actual business. The same three problems show up every time — and they're why most AI investments fail.
When something goes wrong, you're stuck waiting for the vendor. Your team can't debug it, can't modify it, can't even understand what happened. You're paying monthly for a black box.
The tool runs up your bill doing the same work over and over. Small changes trigger full reruns. There's no way to tell it "you already did this part" — so you pay for it again.
Generic tools force you to change your workflow to match their assumptions. Your edge cases? Not supported. Your specific process? "Coming soon." You end up working around the tool instead of with it.
Most AI tools start from scratch every time. Change one thing, and the whole system reruns — burning your money on work it's already done. Ours doesn't. It tracks every step, caches the results, and only redoes what actually changed.
The result: 70% lower running costs, systems you can actually debug when something goes wrong, and automation that fits your business instead of the other way around.
One call. We map your workflows, identify the three highest-leverage agent opportunities, and write you a report. Yours regardless of whether you hire us.
We pick the highest-ROI workflow from the audit. Build it as an execution-lineage graph. Ship to a small group of users. Measure against the baseline.
Observability, evals, retry strategy, role-based access, audit logs. The thing your compliance team will sign off on. The thing finance can put on a budget line.
Full code transfer. Docs, runbooks, training. From here, you choose: run it completely on your own, or keep us on affordable maintenance. No pressure, no lock-in — it's truly yours.
Inbound tickets, emails, or calls. Classify, enrich, draft, escalate. Human-in-the-loop where it matters. Cuts queue volume 40-70% on real workloads. Built so the wrong answer is debuggable, not invisible.
CRM-aware agents that research, score, and personalize at the level of a junior SDR — without the ramp time or the burnout. Wired into your existing data so the agent doesn't make up account history.
RAG done seriously: typed retrieval, source-grounded answers, version-aware indexes. The agent your finance team can trust to read a contract. The kind that says "I don't know" when it doesn't.
Most of our work is bespoke. Manufacturing QA. Insurance underwriting. Legal-doc review. Whatever it is, the methodology stays the same — DAG, artifacts, identity-based replay. You own it at the end, and you choose: maintain it yourself or let us handle it affordably.
We publish a written report after every audit — anonymized but detailed. If your situation looks like one of these, we probably know exactly what's wrong and how to fix it.
We tracked every commit, eval run, and standup in a fintech's six-month agent build. Six of the eight features that shipped moved no metric. Here's where the engineering time actually evaporated — and which two features carried the rest.
Request access →Most retrieval pipelines fail in ways that don't trip the obvious alarms. We instrumented twelve production deployments and catalogued what the teams didn't know was happening — and what the dashboards never showed them.
Request access →A production agent diverged from its staging twin: same model, same temperature, same inputs, different behavior. We mapped where non-determinism enters agent systems, why teams stop noticing, and the engineering required to put it back in its box.
Request access →None. We give you the report whether or not you hire us. Our bet is that the report itself demonstrates how we think, and a meaningful percentage of the businesses we audit decide to engage us for the pilot. The ones that don't still get a useful artifact, and we still get a sharper sense of where in the market our methodology lands.
Most AI systems re-run everything every time something changes — burning tokens on work that's already been done. Our approach caches intermediate results and only recomputes what's actually affected. Clients typically see 60-70% lower running costs compared to traditional approaches. Plus, you're not paying us a monthly retainer to keep it running — the system is designed to be maintained by your own team.
Most AI agencies sell you a generic platform and lock you into expensive retainers. We do the opposite: we build custom systems designed around your specific workflows, not theirs. You fully own everything at the end. And you choose what happens next — maintain it yourself (it's built to be simple) or keep us on affordable support. No lock-in, no black boxes, no surprise bills.
Yes. Always. The repository, the prompts, the eval suite, the deployment scripts — all transfer to your org at handoff. We do not lock the substrate. We do not run it as a black box. The system is built to be maintained by your own team. If you want ongoing support, we offer affordable maintenance — but that's your choice, not a requirement.
Yes to both. Most of our builds are self-hosted in the client's VPC — AWS, GCP, Azure, or on-prem — because that's where the data already lives. We bring the substrate, you bring the cloud. No data leaves your environment.
From founder-led teams of 10 up to enterprise divisions inside companies of 10,000+. The methodology is the same; the engagement shape changes. Smaller teams get a tighter pilot scope. Larger teams get more attention to compliance, audit, and security review. Both get the free audit.
Engineers who've built AI systems inside large enterprises — places where failure isn't an option and "it works sometimes" doesn't cut it. We started Lanvar because we kept seeing businesses burned by AI vendors who overpromised and underdelivered. Our methodology exists because we got tired of watching good companies waste money on systems that couldn't be maintained or trusted.
We respond within 24 hours. If your situation fits, we'll schedule a one-hour call to map your workflows and identify where AI can actually help — free, no strings attached.