▸ Engagement 02 · 6–12 weeks · From $90k

Agentic AI & MCP Systems

Production agents that survive real traffic. Eval pipelines, MCP servers, retrieval, observability, cost guardrails — every layer engineered, not glued.

▸ What's in scope

Built for production, not demos

Agentic workflows

LangGraph or custom orchestration depending on your needs. Iteration limits, retries, idempotency, circuit breakers — all the boring things demos skip.

MCP server design

One server per logical domain (the right way — see our opinion piece). OAuth, rate limits, audit logs, idempotency keys.

Retrieval & RAG

Embeddings pipeline with freshness SLOs. Hybrid search where it earns its keep. Chunking that survives doc-format changes. Recall metrics, not vibes.

Eval pipelines

30-case suite in CI on day one. Tool-selection evals, output evals, regression replays from prod traces. Fail the build on regression.

LLM gateway & routing

LiteLLM or Portkey. Per-task model routing (frontier when needed, mid-tier by default, small for high-volume). Prompt caching tuned per surface.

Observability for AI

OpenTelemetry spans for every LLM and tool call. Cost per request, latency per step, prompt version per call. Queryable in your existing tooling.

▸ Use cases

Patterns we ship

Internal copilots

For your own engineers, support, or operations team. Connects to Jira, Slack, your data warehouse, runbook repos. Replaces the "ask the senior" bottleneck.

Customer-facing AI features

RAG over your product docs, in-product copilots, automated triage. With the redaction layer, evals, and rollback story you'd want for any user-facing feature.

Workflow automation agents

Multi-step agents that touch multiple systems. Provisioning, reporting, follow-ups. Designed with humans in the loop where the stakes are real.