A measured read of the acquisition
Inventory the acquired estate and its dependencies. Give the operating team a costed route for the decisions ahead.
You receiveCosted modernization map
Delivered through Data Strategy AssessmentFaster value creation.
From the data you own.
Read portfolio systems, reporting definitions and platform spend together so the next acquisition starts with a costed data plan.
Read the acquired estate
Know the workloads, owners and dependencies before the move.
A shared portfolio view
Make KPI definitions comparable across companies.
Spend with a purpose
Tie platform decisions to the value-creation plan.
Scoped in the first working session · Fixed price · The findings are yours
Make the portfolio legible.
Price the next move.
Each acquisition arrives with its own systems, reports and spend. Start from the workloads that run today and the decisions the hold period demands.
Measure before consolidating
Read the estate and its operating cost first.
Agree what compares
Set shared metric definitions before building portfolio reports.
Fund a bounded bet
Screen AI ideas against the data and controls available.
This is the right partner when
- A new acquisition needs a costed estate assessment.
- Portfolio reports use incompatible KPI definitions.
- Platform spend lacks workload-level ownership.
Data and AI work
across the portfolio.
Start with the decision, follow the data, and leave each engagement with something your team can use.
A platform choice for the portfolio
Test candidate platforms against representative portfolio workloads. Compare the operating model and cost before selecting the target.
You receiveVerdict and target architecture
Delivered through Technology SelectionAcquired estates consolidated with evidence
Move each bounded data wave with source-to-target checks. Give owners the evidence needed to approve cutover.
You receiveCutover evidence
Delivered through MigrationsPortfolio KPIs on shared definitions
Align metrics across company ERP and reporting systems. Make portfolio reporting comparable without erasing useful local detail.
You receiveSemantic model
Delivered through Analytics & BIPlatform spend under control
Read Fabric or Databricks spend by workload. Benchmark the estate and hand back the measured comparison.
You receiveRefreshed baseline
Delivered through Data Estate OptimizationAI bets screened across the portfolio
Trace one company’s proposed AI workflow against data and permissions. Price the gaps before funding a pilot.
You receivePriced gap list
Delivered through AI Readiness
The Mandelbulb Kit Private Equity editionBuilt and maintained in-house
Engineered in-house.
The Mandelbulb Kit.
Accelerators, agents and products we build and maintain ourselves, brought into an engagement wherever they fit.
Use-case screen · Screen the value bet
Butter
A free first verdict on one AI use case, in about two minutes, with no call.
- Asks eleven short questions about one use case
- Scores suitability, readiness, value and risk
- Returns one of five verdicts: Build, Buy, Pilot, Delay or Don't build
Before investment
Explore more about ButterAlso in this edition
- SAPBridge · BOBJ TransformerAt reporting exitSAP data on Microsoft Fabric or Databricks, reconciled to the source, with a planned exit from BusinessObjects built in., explore SAPBridge · BOBJ Transformer
- Atlas AIAcross the portfolioTurns a project inbox into an operating picture: every message routed to its project, today’s priorities surfaced, commitments tracked., explore Atlas AI
What the first
engagement looks like.
Start with a bounded piece of work and a clear record of what your team receives.
Scan the estate
Workloads, owners and dependencies across the acquisition.
You receive
Workload inventory
Baseline the cost
The cost of each platform and workload as it runs today.
You receive
Cost baseline
Price the route
A sequenced route priced against the measured baseline.
You receive
Costed modernization map
Questions buyers ask.
How do private equity firms use data and AI?
Private equity firms use data and AI to speed value creation across portfolio companies: reading an acquired estate, making KPIs comparable, controlling platform spend and screening AI ideas before they are funded. We start from the workloads that run today and the decisions the hold period demands, so each move is priced against a measured baseline rather than a vendor estimate.
Which data platform suits a private equity portfolio?
Each acquisition arrives with its own systems, so the platform choice should be tested rather than assumed. A Technology Selection engagement runs candidate platforms against representative portfolio workloads and compares operating model and cost. Our work is platform independent: Microsoft Fabric, Databricks or BigQuery for data, with Azure OpenAI, OpenAI, Anthropic, Gemini or a self-hosted model for AI.
How should a private equity firm start with portfolio data?
Start with the estate behind the value-creation plan. Bring the acquisition to a 30-minute working session and we agree where to start. The usual first engagement scans the acquired workloads, owners and dependencies, baselines what each platform and workload costs today and prices a sequenced route against that baseline. It is scoped in that session, fixed price, and the findings are yours.
What governance should be settled before consolidating portfolio data?
Settle ownership, access and metric definitions before you consolidate. Each acquired company brings its own owners, permissions and KPI definitions, and merging them without agreement produces portfolio reports nobody trusts. Agree shared definitions first, move each bounded data wave with source-to-target checks and give owners the evidence they need to approve cutover. Screen AI ideas against the data and controls each company actually has.
What does a first private equity engagement deliver?
A first engagement delivers a workload inventory, a cost baseline and a costed modernization map for the acquired estate. The inventory names workloads, owners and dependencies. The baseline shows what each platform and workload costs as it runs today. The map sequences the route, priced against that baseline, so the operating team has a costed plan for the decisions ahead.
What we do.
For Private Equity, the four practices run as one loop.
Strategy & Advisory
Judgment before the build. We map what your data can actually do for the business, price the path, and hand you a plan you keep, whichever way you decide.
Modernization
We move your data out of aging systems onto a foundation built for what comes next, without losing a single number along the way.
Data & AI
The work your teams feel every day: live operational intelligence, reporting people trust, and AI that acts inside the systems you already run.
Data Estate Optimization
A running estate quietly gathers waste. We find it, tune it, and turn the savings into the budget for whatever you build next.
Partners and recognition.
Bring the acquisition.
Leave with a next step.
Bring the estate behind the value-creation plan. We will agree where to start in a 30-minute working session.