AI Integration.
From AI-curious to AI-capable.
Integration is where most enterprise AI quietly fails. We specialize in the careful work of embedding models into production systems that already have users, compliance constraints, and uptime requirements. The work is less about novelty than about discipline: evaluation harnesses, cost and latency budgets, graceful degradation, and observability that tells you the moment something drifts.
Three commitments that shape every ai integration engagement we take on.
Strategy-first
Clear roadmaps aligned with how your business actually operates.
Governance-led
Responsible implementation that is measurable, safe, and production-ready.
Real impact
AI that improves activation, strengthens support, and reduces operational drag.
Anonymized summaries of recent work. Client identities are not disclosed by default; references available under NDA.
- 01
Copilot integration inside a 12-year-old policy platform
- 02
Agentic capability layer for a CRM used by 2,000 reps
- 03
Retrieval across a regulated knowledge base for a pharma client
- 04
Evaluation harness and SLA framework for an LLM vendor switch
Honest posture, not stage-managed numbers. We commit to specific targets in the engagement design phase, after we have read the work.
- Time to integration
Weeks, not quarters
- Evaluation coverage
Golden-set + production traces
- Observability
Cost, latency, drift, quality
- 01
Integration architecture and rollout plan
- 02
Evaluation harness and golden datasets
- 03
Production instrumentation and dashboards
- 04
Fallback and graceful-degradation patterns
- 05
Operator playbooks
Selection is driven by the engagement, not by a preferred-vendor list. We work on your infrastructure unless there is a compelling reason not to.
Begin with a 45-minute diagnostic call.
We leave the first conversation with a written perspective on the work, whether or not it becomes an engagement.