AI Agents & LLM Applications
AI agents and LLM applications engineered for production
We build agentic systems on top of frontier large language models: autonomous agents, in-product copilots, retrieval-augmented generation (RAG) pipelines and evaluation harnesses. Every system is instrumented, tested against real user data and designed to degrade gracefully.
Outcomes
- Copilots embedded inside your product, not bolted on
- Agents that call tools, take actions and report back reliably
- Grounded answers over your own documents and data
- Measured quality with evals, tracing and guardrails
What we deliver
- Agent architecture and orchestration layer
- RAG pipeline with ingestion, chunking and vector search
- Prompt, tool and eval suites with regression tracking
- Observability: traces, cost and latency dashboards
Stack
- Claude
- OpenAI
- Gemini
- LangGraph
- Vercel AI SDK
- pgvector
- Pinecone
FAQ
AI Agents & LLM Applications, explained
We are model-agnostic. We routinely ship on Claude, GPT and Gemini models and pick the right one per task based on quality, latency and cost. We also fine-tune and self-host open-weight models when data residency demands it.
More services
Often paired with
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