Custom AI Build

What "Custom AI Build" actually covers

Most production AI systems are not just a model. They're a stack:

• Model selection and (where useful) fine-tuning
• Retrieval architecture: vector DB, hybrid search, re-ranking, freshness
• Agent and tool-use orchestration when the system needs to act, not just answer
• Evaluation harness with eval datasets, metrics, and regression tests
• Guardrails for PII, content safety, and policy compliance
• Integration with your customer-facing or internal systems
• Observability: tracing, logging, drift detection, cost and latency dashboards

We build all of it. The end state is a production system, not a demo.

When this is the right engagement

• You've completed an AI Pilot (with us, or with another vendor) and want to ship the validated use case to production.
• You have a real production target with users who will rely on the system.
• You need integration with existing systems (EHR, DMS, SIEM, CRM, e-commerce platform, etc.) that goes beyond a AI Agent wrapper.

If you're still validating feasibility, start with a Pilot. If the system is already in production but needs ongoing improvement, look at Managed AI.

How it works

A typical 4-month Build:

• Month 1: Foundations. Model selection, retrieval architecture, evaluation harness, success-criteria contract.
• Month 2-3: Build. Iteration cycles against the evaluation harness. Integration with your systems. Internal alpha.
• Month 3-4: Hardening. Performance, cost, security review, guardrails, observability. User-facing alpha or beta.
• Handoff. Documentation, evaluation harness, and runbook handed to your engineering team.

Most Builds are paired with Private AI Deployment — the deployment shape is part of the architecture from day one.

How we work with your team

We're not a black-box vendor. We work alongside your engineers — pairing, code review, shared repo, regular demos. The goal is that your team can extend, evaluate, and operate the system on day one of production. That's also the foundation that Training & Enablement and Managed AI are built on.