Judgment
before the build.

Know what to build, on which platform, in what order and at what cost, before you fund any engineering.

  • Your estate, measured

    Every workload read as it runs, with what it costs.

  • Every bet, priced

    Each use case gets a cost and a written verdict.

  • One funded direction

    A costed roadmap your board can approve.

Assess in two weeks, typically · Fixed price · The findings are yours

Costed mapGovernanceArchitectureBacklogReady to fund

Get the decision right,
and the build follows.

MeasurePriceDecideDelayBuildDon't build

Programs that fail in the build were usually lost months earlier, in the decision: a platform picked before its workloads were measured, a use case picked for its sponsor, governance left for the first audit.

  • Measured, not assumed

    Assess reads every workload as it runs and prices each move against the cost of standing still.

  • Decided in the right order

    Governance first, then the platform, then the backlog. Each decision sets the terms for the next.

  • No is a valid answer

    Every use case gets a written verdict, and Don’t build is recorded with the same care as Build.

This is the right engagement when

  • The board wants a costed plan, and the use-case list has no prices.
  • Governance is scheduled for after go-live, or after the first audit.
  • The choice is Fabric, Databricks or staying put, and no workload has been measured.
  • An AI demo worked, and nothing yet shows it can reach production.
  • A tuned estate has recovered spend, and its next workload is undecided.

What we decide with you,
before the build is funded.

  • AssumedMeasuredCosted map

    Data Strategy Assessment

    We read your estate as it runs, typically in two weeks. You keep a costed modernization map with its TCO delta.

    Explore Data Strategy Assessment
  • OwnerAccessDataset

    Data Governance

    Owners, access tiers and lineage are decided before the next workload lands, in a governance model the platform enforces.

    Explore Data Governance
  • TodayAt scaleVerdict

    Technology Selection

    Fabric, Databricks or the platform you run today, settled on the few workloads that carry the decision, before any migration is funded.

    Explore Technology Selection
  • Fund in orderDelayDon't build

    Data & AI Strategy

    Every candidate use case gets a written verdict. The survivors become a costed roadmap and delivery backlog.

    Explore Data & AI Strategy
  • ControlsDataBaseline

    AI Readiness

    One agent is measured before it is built: Butter's free verdict, then typically two weeks on its data, controls and evaluation baseline.

    Explore AI Readiness

Five decisions,
in the right order.

Assess and the Blueprint phase settle five decisions, and each one sets the terms for the next.

Ready to fund
  1. Assess, typically two weeks: what runs where, on which platform and at what cost, with each move priced against the cost of standing still.

    You receive

    Costed modernization map

    Every move priced against the cost of standing still, with its TCO delta.

    Butter, from the Mandelbulb Kit

The Mandelbulb Kit Strategy & Advisory edition

Engineered in-house.
The Mandelbulb Kit.

Accelerators, agents and products we build and maintain ourselves, brought into an engagement wherever they fit.

Use caseFour scoresVerdictSuitabilityReadinessValueRiskBuildBuyPilotDelayDon’t build

Use-case screen · Feeds the shortlist

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

Plugs into Measure the estate

Explore more about Butter

What this is not.

This practice ends in a funded decision. The work after it belongs to the next practice.

The story this practice stands on.

A state government administrative building at dusk, warm light between the columns of its stone colonnade

Government of Andhra Pradesh

Government · Tax administration

Net GST growth, department-reported
21%
Interoperable modules on a shared data fabric
4

AI-Drafted GST Enforcement in Andhra Pradesh, Signed by an Officer

AI Tax Officer, which we delivered for Andhra Pradesh's Commercial Taxes Department, runs on decisions settled before the build: one shared data fabric, four interoperable modules, and an officer who decides on every AI draft. The department reports net GST up 21% and credits AI-based scrutiny as one driver among several.

The technology assists in identifying cases and preparing drafts, while the final decision remains with the authorised officer.

Babu AhmedChief Commissioner of State Taxes, Andhra Pradesh · The Times of India, 21 Aug 2026Read the source (opens in a new tab)

Partners and recognition.

  • Microsoft 2024 Partner of the Year, Analytics Award Finalist
  • Microsoft Fabric Featured Partner
  • Microsoft Solutions Partner
  • Google Partner
  • Databricks
  • Anthropic
  • OpenAI

Questions buyers ask.

What does a data strategy and advisory engagement deliver?

It delivers a funded decision: what to build, on which platform, in what order and at what cost. From Assess you keep the findings report, the costed modernization map and the use-case shortlist. From the Blueprint phase you keep the governance model, the target architecture and the priced backlog with its written verdicts. All of it is yours whether or not we build together.

How long does data strategy and advisory work take, and how is it priced?

Assess typically takes two weeks, and the Blueprint phase that follows typically takes two to three weeks. Each phase is fixed price and fixed scope, priced up front, so the cost does not grow with what the work recommends. For a single agent use case, Butter gives a free first verdict in about two minutes, and the AI Readiness pass typically takes two weeks.

Do you recommend Microsoft Fabric or Databricks?

We recommend whichever platform wins on your workloads, and the platform you run today is one of the candidates. The governance rules are set first, platform-neutral, and the platform is then chosen against them on the few workloads that carry the decision. The result is a target architecture with its reasoning written down, not a preference carried in from the last project.

How is this different from a strategy deck from a large consultancy?

Every finding is measured on your estate, so it can be checked. A typical strategy deck holds a maturity score, a long list of initiatives and a platform recommendation with no workload behind it, and nothing in it can be proved wrong. Assess reads every workload as it runs and prices each move against the cost of standing still. Every candidate use case gets a written verdict, and walk away is recorded with the same care as build.

What do we need in place before strategy work starts?

You need the estate you want to decide about and the use cases you are weighing; nothing has to be built or migrated first. Assess reads every workload as it runs, so the work starts from the estate itself rather than from its documentation. The first step is a 30-minute working session on your estate and your use cases, which ends in one shared shortlist.

What comes next.

When the map is funded, the estate is ready to move. The map, the governance model, the target architecture and the priced backlog go with it. The question becomes how to move the estate and prove the numbers still match.

This practice

Decide

Strategy & Advisory

When the map is funded

Bring us the decision
you keep deferring.

Book a 30-minute working session on your estate and your use cases. It ends in one shared shortlist.