AI-Ready Data Foundation
The models, definitions, and governed metric layer an AI analyst can actually answer from. Built, documented, and owned, so the same numbers hold whether a person or a model asks.
Decision Spine helps founders and scaling teams turn messy data, scattered metrics, and unclear reporting into AI-augmented decision systems leadership can actually trust.
Start with a single focused engagement or bring us in as your fractional data leadership. Every engagement is scoped to leave you with something durable.
The models, definitions, and governed metric layer an AI analyst can actually answer from. Built, documented, and owned, so the same numbers hold whether a person or a model asks.
A focused build: an AI analyst grounded in your governed metrics, verified examples, and metric tree, so its answers hold up and you see how much each layer of structure buys.
Define the metrics that actually move your business and connect them into a coherent tree, from north star down to the inputs teams can act on.
Senior data leadership part-time: strategy, hiring, and hands-on delivery until a full-time leader makes sense.
Tell us where decisions feel fuzzy and we'll point you to the engagement that helps first.
Most teams don't have a data problem so much as a decision problem. These are the standards we hold the work to.
Exact and rigorous. Definitions, metrics, and models are built to be right, not merely plausible.
Clean models, clear reporting, and systems that are a genuine pleasure to operate.
Trust built through clarity and reliability, so leadership can act without second-guessing the numbers.
We start from your decisions and your customers, then design the analytics backward from there.
Data connected to decisions and real outcomes, measured by the calls it improves, not charts shipped.
No sprawling roadmaps. A clear path from murky reporting to decisions your team can stand behind.
Map how decisions get made today, which metrics leadership trusts, and where the data quietly breaks down.
Shape the metric tree, definitions, and ownership the business actually needs. Nothing decorative.
Implement trusted models, reporting, and analytics your teams can read the same way every week.
Wire metrics into review cadences so they drive real, accountable operating decisions.
Refine the system as the business learns, priorities shift, and new questions emerge.
I'm Dmitry Ustimov. I've worked every layer between raw data and the decisions it drives, as Head of Data at fintechs like Zeal Group and Coins.ph, most recently leading data engineering at Neko Health, and now building HabiBubble. Decision Spine brings that to founders and scaling teams: one focused engagement, or as your fractional head of data.
Practical thinking on metrics, reporting, and data platforms, drawn from advisory work with founders and scaling teams.
AI analysts fail before SQL generation when they choose the wrong metric, table, or column. Static checks can catch many of those wrong-choice traps before the agent runs.
ReadSimple questions make AI analysts look ready. Real business questions combine several primitives, and small errors compound. From 1,488 graded runs, a repair method for AI-ready data: find the primitive that failed, find where its grounding lives, and move that grounding where the agent cannot skip it.
ReadIf your dashboards, metrics, or data platform are not helping leadership make better decisions, let's diagnose where clarity is missing.