Media.

Media organisations need generative AI that accelerates editorial throughput without crossing the editorial-trust line. Research, tagging, and distribution are fair game. Byline-generation usually is not. In practice, the first deployments cluster around search & re-ranking, document intelligence, structured extraction, internal copilots: areas where evaluation criteria are objective, data is already in the system, and an evaluation harness can measure quality continuously.

Regulators-of-note for media engagements typically include ACMA, Ofcom, FCC, press-council codes. 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 deploy generative AI to author published editorial copy without editorial-desk review. Assistive use only, with attribution policy decided by the publisher. 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 media engagements typically sit between Chief Digital Officer, Head of Editorial Technology, Director of Distribution and equivalent senior operators. The decision-maker varies by organisation, but the common thread is a leader accountable for both delivery and downside.

In media, generative AI accelerates editorial research, asset tagging, and personalised distribution, with human-in-the-loop quality gates. 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.