Real-world examples of how we've helped organizations achieve their AI goals while navigating complex regulatory requirements.
Configuring an intelligence and authoring platform to a corporate investigations firm's subject-check workflow, automating retrieval, triage, translation, and drafting while keeping every claim traceable to its source.
Analysts spent the bulk of a subject check on mechanical work: running the same searches across registries, litigation records, and news archives, translating non-English results, triaging what was relevant, and reformatting findings into the house report template.
A configured deployment that automates retrieval, screening, and drafting beneath the researcher, built on three design commitments established in discovery: every claim traceable to source, comprehensive coverage with a clean fallback to manual work, and the researcher in control of all final output.
Engagement
Design Standard
Technical due diligence for a private equity investment in an AI-powered healthcare technology company, assessing engineering capability, product strategy, and how much of the AI story held up under examination.
Assess whether an AI-powered healthcare technology company's technical capability, product roadmap, and organization justified a significant investment, and whether its AI claims reflected genuine capability or repackaged third-party tooling.
Independent technical assessment covering AI and ML capability, platform architecture and scalability, security posture, acquisition integration, data maturity, and the strength of the product and engineering organization.
Engagement
Focus
