services
AI Integrations
RAG systems, custom agents, copilots, and AI-grounded internal search — built into the tools and data your team already uses.
what is it?
AI integrations bring large language models, retrieval systems, and custom agents into your existing tools and data — not as a separate AI product, but as a layer that makes your team faster. Whether that's RAG-grounded search over twelve years of internal docs, agents that handle tier-1 customer queries, or copilots inside the tools your team already uses, we build AI that answers to your codebase, runs on your infrastructure, and stays under your control.
We work in your VPC when needed. We use your choice of model provider. We build in TypeScript or Python depending on your stack. The output is code your team owns — not another vendor-managed black box.
RAG & retrieval
Private retrieval systems over your documents, codebase, or knowledge base. Citation back to source. Permission-aware. VPC-deployed when required.
Custom agents
Multi-step agents with tools, memory, and clear handoff to humans. Anthropic + OpenAI APIs, our orchestration code, your data.
Copilots in your tools
Copilots embedded in the workflows your team already uses — internal admin panels, CRMs, support consoles.
Customer-facing AI
Production AI features your customers see — chat, search, recommendation, generation — with the eval harness and guardrails to ship them confidently.
how we work
How an AI integrations engagement actually runs
We start with a 1-week eval phase. We benchmark the model, prompt design, and retrieval quality against your actual data. You see numbers — recall, precision, latency, cost-per-query — before we commit to an architecture.
Then a 6–10 week build. Senior engineers in your codebase, weekly demos to your lead, every line code-reviewed before merge. We ship to a staging environment by week 4, production behind a feature flag by week 8.
We leave behind a working system, an eval harness so you can keep grading the model after we're gone, and runbooks for prompt updates, model swaps, and incident response.
Tools we use:
- Anthropic API
- OpenAI
- Postgres + pgvector
- LangChain
- TypeScript
- Python
- AWS / GCP
- Inngest
- Sentry
- OpenTelemetry