Know what your estate runs, what each workload costs and what each move is worth, before anyone funds a migration.
Every workload, found
What runs, who owns it and what it depends on.
Cost by workload
Spend read per platform and per workload, not per invoice line.
A costed route
Each move priced against the cost of standing still.
Assess in two weeks, typically · Fixed price · The findings are yours
Most roadmaps are priced on an inventory two reorganizations old and a cost model that averages away the ugly workloads. The undocumented dependency shows up a few waves in, after the budget is committed.
Scanned, not surveyed
We read what actually runs, cloud and on-premises, whatever the inventory on file says.
Priced per workload
Spend, including the hours that keep fragile pipelines alive, is attributed workload by workload.
Read against your decisions
Maturity is tested against the decisions due in the next four quarters, not a generic scale.
Five steps, typically two weeks, take you from the decisions you face to a costed route.
We list the decisions the business must make in the next four quarters, and the systems each one touches.
You receive
Decision list
The decisions due in four quarters, each with the systems it touches.
Accelerators, agents and products we build and maintain ourselves, brought into an engagement wherever they fit.
Use-case screen · Screens the candidates
A free first verdict on one AI use case, in about two minutes, with no call.
Plugs into Screen and read maturity
Explore more about ButterThis work ends in a measured estate and a costed map. Choosing the platform and the bets comes next.
Already on Databricks or Fabric and paying too much?
That is Data Estate OptimizationEstate measured, and the platform still open?
That is Technology SelectionMore use cases than budget to fund them?
That is Data & AI Strategy
Swiggy
Quick commerce · Retail
Swiggy promised delivery in under ten minutes, yet read dashboards up to 10 minutes old; dark-store stock-outs took 5 to 10 minutes to show, and leaked discount codes spread faster than batch reports could reveal the abuse. We read the estate against those decisions and put five production workloads on one real-time Microsoft Fabric platform instead of five stitched tools. Decision latency fell from up to 10 minutes to seconds, on 1B+ events a day.
A data strategy assessment measures the estate you actually run, prices each workload and turns that into a costed route forward. Ours scans every workload in scope, cloud and on-premises, with its owner and dependencies, attributes spend by platform and by workload, and tests the estate against the decisions due in the next four quarters. The output is a costed modernization map with a TCO delta on every major move.
It typically takes two weeks, at a fixed price agreed up front. The scope is fixed too, so the assessment cannot become a discovery that discovers a longer discovery. It is Assess, the first phase of our method, and it runs across the estate in scope, cloud and on-premises, ending in the findings, the use-case shortlist and the costed modernization map.
You keep four things: the findings report, the workload inventory and cost baseline, the costed modernization map and the use-case shortlist. The report says plainly what runs, what it costs and what is fragile. The map sequences every move by dependency, with a TCO delta on each major move. All of it is yours whether we run the next phase, another firm does, or your own team does.
It measures the estate instead of surveying it. Many maturity scores come from a workshop and an inventory two reorganizations old; this assessment reads what actually runs and prices it workload by workload, engineering hours included. Maturity is tested against the decisions your business faces, not a generic scale. The artifacts stand on their own, because an assessment that only makes sense if you hire the assessor is a sales document.
No. The scan starts from what actually runs, whatever the inventory on file says, and missing owners are flagged as they surface. What helps is a view of the decisions the business must make in the next four quarters, because the first step frames those decisions and the systems each one touches. The usual starting point is a 30-minute working session on the estate you run.
Natural next step
The workload inventory, the cost baseline and the costed modernization map go into the Blueprint phase, typically two to three weeks, where the question changes from what the estate costs to what to commit to: the governance rules first (Data Governance), then the platform chosen against them (Technology Selection), then the backlog, sized, sequenced and priced (Data & AI Strategy). When the map is funded, it crosses to Move, our Modernization practice, with the design the Blueprint phase produces.
Owners, access tiers and lineage are decided before the next workload lands, in a governance model the platform enforces.
Fabric, Databricks or the platform you run today, settled on the few workloads that carry the decision, before any migration is funded.
Every candidate use case gets a written verdict. The survivors become a costed roadmap and delivery backlog.
One agent is measured before it is built: Butter's free verdict, then typically two weeks on its data, controls and evaluation baseline.
Bring your estate to a 30-minute working session. We agree there whether Assess is the next step.
