Technology.

Technology companies do not need help understanding generative AI. They need a partner who ships harnesses, evaluations, and platform plumbing at their own product cadence. In practice, the first deployments cluster around internal copilots, agentic workflows, evaluation harnesses, llmops platform, search & re-ranking: areas where evaluation criteria are objective, data is already in the system, and an evaluation harness can measure quality continuously.

Regulators-of-note for technology engagements typically include regional privacy law (GDPR / CCPA / Privacy Act), SOC 2, ISO 27001. The specific regulators that bind a given engagement depend on jurisdiction and the data classes in scope, so we map this explicitly during discovery rather than assume a global posture.

We do not run side-of-desk PoCs that never reach production. Every engagement ships working software that holds up in production, or we walk away. This is a deliberate trust boundary, not a capability gap. We are equipped to build the systems we decline to build, and we decline to build them because the risk-to-value ratio in this industry does not justify it.

Our technology engagements typically sit between VP of Engineering, Head of Platform, Chief Technology Officer and equivalent senior operators. The decision-maker varies by organisation, but the common thread is a leader accountable for both delivery and downside.

In technology businesses, generative AI shows up first in internal copilots: coding, support deflection, and knowledge retrieval over Confluence-class corpora. The same techniques look superficially similar across industries, but the data shapes, evaluation criteria, and adverse-event posture differ enough that copy-pasting an engagement from another industry usually produces a system that fails the first audit it sees.

We spend two weeks with your leadership and operators, rank the use cases that are worth doing, and come back with a clear plan and a clear price. We never start with a six-month strategy exercise. We go after the smallest piece that produces real value first.