A few practical questions

We primarily work with private equity investors and their portfolio companies, typically mid-market businesses where data and AI can support value creation, operational efficiency, and growth. We also support management teams preparing for investment, transformation, or exit.

Our work typically aligns with the investment lifecycle: Pre-investment diligence – testing the data and AI assumptions in the investment case During ownership – acting as Data & AI Operating Partners to define strategy and deliver value Pre-exit – preparing the data and analytics story for buyer diligence

Engagement duration depends on the scope. Typical timeframes include: Data & AI diligence: 1–3 weeks Data strategy: 4–8 weeks Delivery and operating partner support: multi-month programmes aligned to value creation plans Exit readiness and VDD: typically 3–6 weeks depending on scope

Most of our work can be delivered remotely, particularly diligence and analytical assessments. For strategy and delivery engagements we often combine remote collaboration with targeted on-site workshops, particularly when working closely with management teams.

All engagements are senior-led. Our projects are delivered by experienced data and AI practitioners who have worked across investor environments, complex data platforms, and operational analytics programmes. Senior team members remain actively involved throughout the engagement.

We provide both strategy and delivery. Our work ranges from diligence and strategy through to implementation of data platforms, analytics, machine learning, and automation initiatives. We often work alongside existing technology teams or implementation partners.

Yes. We are technology agnostic and have experience working across a wide range of data platforms, tools, and environments — including AWS, Azure, Microsoft Fabric, Google Cloud, Snowflake and Databricks. Our work spans the full data and AI landscape — from data engineering and infrastructure through to analytics, machine learning, and AI. We design architectures and select tools based on what best fits the business, not a preferred vendor or ecosystem.

For diligence engagements we typically request access to: Data room materials System architecture overview Sample datasets or database access Key operational systems (ERP, CRM, platforms) For strategy or delivery engagements we begin with management interviews and system discovery.

Most engagements are delivered on a fixed-fee basis aligned to a clearly defined scope. For longer delivery programmes or operating partner roles we may work on retained or phased engagements aligned to the portfolio company’s value creation plan.

We focus specifically on the investor context. Our work combines technical data expertise with commercial understanding of value creation, ensuring that analytics, automation, and AI initiatives translate into measurable operational and financial impact.