AI Strategy for SaaS & Technology

Capability building is usually underfunded relative to technology. The constraint is rarely the model; it is the number of people who can deploy one safely.

In saas & technology, per-tenant economics and enterprise security review decide whether a feature can ship. That single fact reshapes how ai strategy has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is support deflection, usually integrated against support tooling. Every engagement opens with a measurement: the cycle time, the cost per transaction, or the error rate we are being asked to move.

Built by engineers who ship production systems, not by a practice that subcontracts the build. You own the code, the models where they are open-weight, and the documentation to run it without us.