We build production AI systems — and we build them with AI. Weeks, not quarters.
Agents wired into the systems you already run — CRM, ERP, internal tools — with monitoring, evals, and a human in the loop where it matters.
Your documents, tickets, and tribal knowledge, answering questions with citations. Retrieval designed for your data, not a demo dataset.
Workflows that used to need a team, run by pipelines with eval-gated accuracy. Exceptions route to people; everything else just runs.
LLM-powered products shipped to production — not prototypes that die in a slide deck.
The pipelines, warehouses, and quality gates that make AI outputs trustworthy. Data first; model calls second.
The engineering underneath it all — deployment, scaling, cost discipline, and the boring reliability work most AI shops skip.
AI-assisted delivery is the entire cost advantage. We keep the pods small and senior, let the toolchain do the leverage, and pass the speed on.
A tiered extraction platform — deterministic parsers first, LLMs only where they earn their cost — turning thousands of property websites into clean unit-level pricing data daily.
Speech-to-text plus LLM scoring with hallucination guardrails and evaluation harnesses — turning recorded leasing tours into scored, cited coaching for every associate.
Every engagement starts the same way: two weeks on your live data, ending with a working prototype slice and a scoped plan — not a strategy deck.
Browse the full library — case studies & blueprints → Detailed numbers and references available on a call.
The entry point. We take one workflow and your live data, and come back with a working prototype slice, an eval baseline, and a scoped build plan. Priced on the intro call — no open-ended discovery.
A pod of two or three senior engineers ships the system to production. The engineer who scoped it writes the code.
We operate, monitor, and improve what we shipped — evals watched, models swapped when better ones land, costs tuned.
Our engineers inside your team, bringing the AI-native toolchain with them. Staff augmentation without the body-shop economics.
Every pipeline ships with an evaluation harness. Accuracy is a number we report, not a feeling we project.
High-stakes outputs route through review. We tell you exactly where people sit in the loop — autonomy theatre helps nobody.
Code, prompts, pipelines, evals — yours. We never train on your data. The IP clause is one paragraph, in plain English.
Monitoring, versioned prompts, fallbacks, cost alarms. AI systems degrade quietly — ours are built to tell on themselves.
Two things, both literal. What we build: production AI systems — agents, RAG, LLM products. How we build: our own toolchain is generative AI, so a pod of two or three senior engineers delivers what used to need a team of six or eight. If neither were true we would just be a dev shop with a new logo.
AI agents wired into real systems (CRM, ERP, internal tools), RAG over proprietary knowledge, AI process automation, and LLM-powered products — plus the data engineering, cloud, and software work underneath them. We do not do robotics, computer vision moonshots, or "AI transformation" strategy decks.
The Sprint is two weeks and ends with a working prototype slice on your live data. Production builds typically run four to ten weeks depending on integration surface. We quote a specific timeline after scoping — and because the scoping engineer writes the code, the quote survives contact with reality.
Senior engineers, in pods of two or three. No partner-analyst pyramid, no account managers, no handoff between the people who sold the work and the people who do it.
Yes — all of it. Code, prompts, pipelines, eval suites, and infrastructure configs are yours. We never train models on your data, and we put that in writing.
Evaluation harnesses on every pipeline, deterministic logic wherever it beats a model call, citation requirements on generated claims, and human review on high-stakes outputs. We report accuracy as a measured number and monitor it after launch, because AI systems that work in demos degrade quietly in production.
The Sprint is a fixed price quoted on the intro call. Builds are fixed-scope quotes; Run and Embed are monthly. We do not publish a rate card, but you will have a number before any work starts — and no open-ended discovery phase, ever.