01 · build
Custom agent builds
Tool-calling agents and copilots for real workflows: triage, research, document processing, internal assistants, and coding agents. We start with the smallest agent that does useful work, then earn the right to add autonomy.
What's included
- Workflow and tool map before any code
- Step limits and explicit stopping conditions
- Human approval on anything that writes
- Tests, structured logs, and a run log you can read
You leave with
- A working agent in your environment
- Eval set and baseline results
- Runbook and handoff session
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02 · integrate
AI integration & RAG
Ground models in your private knowledge and connect agents to the systems your team already uses through MCP, APIs, and event streams, with access control that follows your data boundary.
What's included
- Retrieval over your docs and data
- MCP tool servers and memory between sessions
- Vector search: pgvector, Qdrant, Pinecone, Azure AI Search
- Model choice across major APIs and open models
You leave with
- Retrieval pipeline with freshness rules
- Tool gateway with auth and audit logs
- Retrieval quality report
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03 · harden
Production hardening
Your team already has a demo. We turn it into something leadership, security, and compliance can approve, without starting over.
What's included
- Eval gate in CI with golden datasets
- Layered guardrails and PII redaction
- Telemetry with OpenTelemetry
- Cost budget, alerts, and a kill switch
You leave with
- Risk review with findings ranked
- Eval harness wired into CI
- Go/no-go review document
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04 · orchestrate
Multi-agent systems
Planner, parallel implementers, test-writer, and reviewer agents, with contracts between them and a gate that checks the work.
What's included
- Role contracts and shared artifacts
- Isolated worktrees where they help
- Aggregation and reviewer gates
- Failure and retry policy
You leave with
- Orchestration repo
- Trace of a full swarm run
- Ops checklist
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05 · advise
Fractional AI architect
A senior practitioner inside your cadence: architecture reviews, roadmap cuts, hiring loops for agent engineers, and working sessions so the team ships the right agent.
What's included
- Weekly or sprint-based advisory
- Written decision log
- Optional pairing on the critical path
You leave with
- Architecture notes
- Prioritized backlog
- A team that needs less outside help
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