Evaluation harness
Regression tests on real questions and tasks before each model or prompt change.
Solutions
Outcome-first AI, not feature lists.
Every engagement combines one or both pillars below—scoped to a workflow your team already runs, with humans in the loop where it matters.
Pillar one
Knowledge you can trust
Turn scattered documents into answers your team can verify. We prioritize citation, permissions, and honest uncertainty over fluent guessing.
- Semantic search across docs, wikis, and file stores
- Q&A with links back to source passages
- Summaries for long PDFs, policies, and report packs
- Access control aligned to existing folders or groups
Example outcomes
- Operations
- HR and ops policy answers in seconds instead of Slack threads
- Consulting
- Find prior analyses and decks by topic, client industry, or methodology
Pillar two
Workflows that move
AI that participates in the work—triage, extraction, drafting, routing—without removing human judgment on consequential steps.
- Ticket and email triage with suggested categories
- Draft replies and internal updates for review
- Structured extraction from unstructured inputs
- Handoffs to CRM, ticketing, and project tools via API
Example outcomes
- Operations
- Support agents approve AI-drafted replies; faster first response
- Consulting
- Proposal sections generated from templates; partner edits and sends
Production quality
What “done” includes.
Observability
Logging, cost tracking, and quality sampling—without storing more than you need.
Handoff & runbooks
Documentation and optional retainer so the system improves after launch.
Not sure which pillar fits first?
The AI Opportunity Audit maps your workflows and recommends one pilot with clear metrics.
See the $5,000 audit →