Illustrative AI-generated scene for the DataValue Strategy case study
AI illustration*

Company Brain case studies

The consulting project that remembers what the meeting decided

How faster documentation could grow into lasting institutional knowledge

  • CompanyDataValue Strategy
  • SectorPerformance management consulting
  • SourceVendor customer story, Dust and Idoption

Consultants are paid for judgment, yet many spend hours turning workshops into meeting notes, specifications and training guides.

DataValue Strategy, an enterprise performance management consultancy set up in 2019, tackled that mismatch by putting AI inside its recurring project work.

What DataValue Strategy did

According to a customer story written by Dust partner Idoption, DVS piloted AI assistants with eight expert ambassadors and gave each project a shared space for transcripts, documents and outputs.

Reported benefits include about 70% less time writing meeting notes and about 50% less time preparing training guides. The headline claims projects are delivered 20% faster, while the figures in the story itself are task-level. The full 42-person team was due to move onto the tool in September 2026. A system to capture senior consultants' expertise was described as in development, with no results yet.

What it already gives the business

This is a meaningful step. Workshop decisions are easier to find, and handovers no longer start from an empty inbox.

A project archive records what was said. It does not automatically keep the reasoning behind why a seasoned consultant chose an architecture or warned against an attractive shortcut.

The ExValu perspective, a hypothesis

Where a Company Brain could take it next

A Company Brain extension could connect a consultant's approved reasoning with past implementation exceptions, project outcomes and patterns from sales discovery.

Suppose several consultants independently find that one client requirement predicts an expensive round of rework. The system could raise that hypothesis during scoping, leading to a more accurate proposal and a margin gain the team can test.

What an owner and a buyer would look for

Hours saved on drafting are a start. A buyer looks further: gross margin by project, rework, on-time delivery, staff handover time and recurring revenue.

Client confidentiality, inherited access rights and the accuracy of AI-generated project conclusions need ongoing review.

The problem behind this case

Facing the same problem?

About this analysis

* The image is AI-generated and does not show DataValue Strategy staff. The facts and figures on this page come from the published source named below.

This is an independent ExValu analysis of a published case. Facts and figures are as reported in the source below, which our team checked on October 9, 2026. The ideas for next steps are our own perspective and make no claim about conditions inside DataValue Strategy.

Primary source: Vendor customer story, Dust and Idoption. Available at dust.tt/customers/how-datavalue-strategy-delivers-epm-projects-20-faster-with-dust.

Research cross-check: ExValu working research, Company Brain Research 2, case inventory of October 6, 2026.

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