Security
Two things changed at once: attackers got faster, and your own organization started running agents that act without a human in the loop. This practice covers both — the defensive posture and the governance that makes AI deployable in a regulated environment.
Your SOC is drowning in alerts that mostly are not real, which means the ones that are get found late. We deploy Google SecOps as the foundation for autonomous detection and response — the system triages, and your analysts spend their time on the small number of things that warrant a person.
Beyond tooling: the shift from reactive monitoring to a platform where goal-oriented systems handle the threat lifecycle independently. This is a program, not a product, and we scope it as one.
Incident response, readiness testing and cyber transformation — before an incident, during one, and in the reckoning afterwards. Mandiant's capability, brought in through us rather than assembled under pressure at the worst possible moment.
Security is where AI and data programs go to die, usually three weeks before launch. We build the controls into the architecture from day one so that security is what lets the program ship rather than what stops it.
A workshop to identify where the value is. An assessment to plan the work properly. A pilot to prove it in your environment before you commit. Each one is a defined piece of work with a deliverable, not an open-ended statement of work.
Book a working sessionThe other practices
Gemini Enterprise inside the tools your team already uses, grounded in your own data.
Customer-facing agents, and the platform that lets the tenth one ship faster than the first.
One governed platform on BigQuery, and an honest view of what is worth migrating.
Landing zones done properly the first time, and the enterprise platforms nobody wants to move.
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