AI that moves a business metric — not a demo.
We build production AI: RAG pipelines, agentic workflows, computer vision systems, and integrations that move real KPIs. Less "chat with our docs," more 89% autonomous ticket resolution and 97.4% defect detection.
Ideal for: B2B SaaS automating support and ops, marketplaces wanting smarter search and recommendations, and any team sitting on a useful dataset they haven't operationalized.
What we build
RAG & agentic systems
GPT-4-class models grounded in your data via Pinecone / pgvector. Evals, guardrails, and human-in-the-loop where it matters.
Computer vision
Defect detection, OCR pipelines, document understanding, custom-trained models on your data. Deployed to cloud or edge.
ML for product features
Recommendations, search ranking, fraud signals, churn prediction — embedded inside your product, not buried in a dashboard.
AI integration into existing products
Most products don't need a new AI app — they need AI inside the one they already have. We retrofit cleanly.
How we run a ai solutions engagement
Use-case validation & data audit
Before any model work, we validate the business case and check the data is actually fit for purpose. We'll tell you when it isn't.
Baseline & evaluation harness
We build the eval set first. Every model change is measured, not vibes-tested. You see the curve, not just the demo.
Production deployment + guardrails
Hosting, prompt versioning, fallbacks, rate limits, cost monitoring, output filtering — the unsexy work that keeps AI safe in production.
Ongoing model & data monitoring
Performance drift, cost spikes, prompt regressions — caught before your users (or finance) notice.
Stack we ship with
Defaults — we adapt to your existing stack when the project requires it.
Core capabilities
What teams typically scope us for.
Scoping a ai solutions project?
30 minutes is enough to know whether we're a fit. We'll come prepared with questions, leave you with a written scope and quote within 48 hours of the call.