Service · AI integrations

AI features that ship — and stay shipped.

Forty percent of our 2026 pipeline is AI work. We treat models as components: scoped, measured, fallback-handled, replaceable. Not magic; engineering.

MCP + ClaudeAgentic AI in production
What we cover

Capabilities, in plain English.

01
Closed + open models

Claude, GPT, Llama, Mistral. We pick what fits the latency, privacy and cost profile — not the headline.

02
RAG over your data

Retrieval pipelines tuned per domain, with eval suites you can run on every change.

03
Agent flows

Multi-step actions with rollback, guardrails and human-in-the-loop where it matters.

04
Evals + monitoring

Production observability for prompts: token cost, latency p99, regression alerting.

05
On-device inference

Small models running locally for privacy-sensitive flows where data shouldn't leave the device.

06
Cost engineering

Caching, prompt distillation, fallback hierarchies. We bring AI bills down month-over-month.

Stack

Tools we reach for first.

Boring tech where it buys speed, sharp tech where it actually pays.

Deep dives — how each compares
ClaudeOpenAILlamaPostgres + pgvectorPythonTypeScriptModal

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