AI Integration that reaches production
Everyone has a prototype. Few have AI running reliably inside real business processes — with security, cost control, and measurable results. That last mile is an infrastructure problem, and it's the one we solve.
The problem
AI initiatives stall in the gap between the demo and the enterprise: company data can't leave compliance boundaries, token costs are unpredictable, outputs need auditability, and nobody owns the operational side. The result is a graveyard of proofs-of-concept and growing pressure from the board to "do something with AI."
What we build
Secure AI landing zone
Azure OpenAI and ML workloads behind private endpoints, with managed identity, content filtering, and audit logging — your data stays inside your tenant's boundaries.
RAG over your data
Retrieval-augmented generation with Azure AI Search: assistants and copilots that answer from your documents, tickets, and knowledge bases — with citations.
Process automation
AI embedded in real workflows — document processing, support triage, report drafting — through APIs and event-driven integration, not a chat window on the side.
LLMOps & cost control
Prompt versioning, evaluation pipelines, usage quotas per team, and dashboards that show what AI costs and what it returns.
How an engagement runs
- Pick the right use case: we score candidates by business value, data readiness, and risk — and start where AI can prove itself fast.
- Build the foundation once: a governed AI platform other teams can reuse, instead of every project re-solving security from scratch.
- Ship a production use case: end to end — data pipeline, evaluation, monitoring, human-in-the-loop where it matters.
- Measure and scale: real metrics against the baseline, then a repeatable path for the next use cases.
What you get
- AI in production, inside your compliance boundary, with measured business impact.
- A reusable AI platform — the second and third use cases ship in weeks, not quarters.
- Cost transparency and guardrails, so the CFO and the CISO both sleep at night.