Generative AI that survives your users.
We design LLM-powered experiences around your data model, risk appetite, and latency budget, not generic chat wrappers. From retrieval to release, you get evals, monitoring hooks, and a path to iterate safely.
Capabilities
What we build with you.
Six areas we typically own or co-own with your team, from first API call to production hardening.
LLM integration
Model routing, streaming UX, token accounting, and fallbacks, wired into your auth, tenancy, and observability stack.
RAG over private data
Chunking, embeddings, re-ranking, and freshness controls so answers cite what they should and refuse what they shouldn’t.
Fine-tuning & evals
Dataset hygiene, task-specific metrics, regression suites, and human review loops that scale beyond the pilot team.
Custom copilots
Role-aware assistants embedded in internal tools, shortcuts, approvals, and domain actions instead of endless prose.
Content & workflow generation
Structured outputs, JSON mode, and schema-bound generation for ops, marketing, and support workflows.
Prompting & safety guardrails
Policy layers, PII handling, jailbreak resistance, and escalation paths so “creative” doesn’t mean “non-compliant.”
How we work
From ambiguity to an operating model.
Discover & de-risk
Success metrics, data access, and failure modes are spelled out before we touch code.
Vertical slice
One end-to-end path in production-like conditions, not a slide deck of possibilities.
Harden & scale
Eval harnesses, caching, cost controls, and dashboards your SREs won’t hate.
Handover & coach
Runbooks, prompt libraries, and pairing so your team owns the roadmap after we step back.
Stacks we like
Technologies we’re productive with.
We meet you where you are. These are common anchors in recent work.
- OpenAI
- Anthropic
- Amazon Bedrock
- Google Vertex AI
- LangChain
- LlamaIndex
- pgvector
- Pinecone
Ready to move past the prototype?
Tell us about your users, your data, and what “good” looks like. We’ll reply with a sensible first step.