Production agents that survive real traffic. Eval pipelines, MCP servers, retrieval, observability, cost guardrails — every layer engineered, not glued. In business terms: automation capacity without new headcount, and AI features your customers can actually trust.
LangGraph or custom orchestration depending on your needs. Iteration limits, retries, idempotency, circuit breakers — all the boring things demos skip.
One server per logical domain (the right way — see our opinion piece). OAuth, rate limits, audit logs, idempotency keys.
Embeddings pipeline with freshness SLOs. Hybrid search where it earns its keep. Chunking that survives doc-format changes. Recall metrics, not vibes.
30-case suite in CI on day one. Tool-selection evals, output evals, regression replays from prod traces. Fail the build on regression.
LiteLLM or Portkey. Per-task model routing (frontier when needed, mid-tier by default, small for high-volume). Prompt caching tuned per surface.
OpenTelemetry spans for every LLM and tool call. Cost per request, latency per step, prompt version per call. Queryable in your existing tooling.
For your own engineers, support, or operations team. Connects to Jira, Slack, your data warehouse, runbook repos. Replaces the "ask the senior" bottleneck.
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.
Multi-step agents that touch multiple systems. Provisioning, reporting, follow-ups. Designed with humans in the loop where the stakes are real.
Our founding CTO has run platforms supporting 500+ microservices at peak for fintech and security companies — the same reliability engineering (retries, idempotency, observability, cost control) is what we apply to every agent we ship. Agents are distributed systems; we treat them that way, so your automation stays an asset instead of becoming an outage.
Founder track record, anonymized. We'll walk you through relevant specifics on the intro call.
QuantAimLabs