Turn Data Into Decisions You Can Trust
Data Platform Evolution modernizes your data foundations — platforms, BI and analytics integration, and decision-support systems — with governed semantics and trusted metrics, executed and sustained under the AI-MSL lifecycle.
Trusted by teams running production software
For organizations whose decisions outgrew their data platform
Analytics initiatives stall when metrics can't be trusted: semantics drift between teams, pipelines accumulate exceptions, and decision-support systems lag behind the questions the business is actually asking.
Data Platform Evolution defines a decision-first data architecture; AI-MSL builds on those foundations when implementing new features and data-driven capabilities — within the same managed lifecycle that governs the rest of your software.
“A metric nobody trusts is worse than no metric at all. Governed semantics is what turns a data platform into a decision platform.”
Co-Chair, LF AI & Data committee
What Data Platform Evolution covers
The areas of work AI-MSL covers — scoped to your system through assessment and executed under continuous lifecycle governance.
You always have visibility into the data work that moves your decisions forward — and what it costs before it ships.
Data Evolution Starts With Understanding Your System
Every AI-MSL engagement begins with a comprehensive system assessment. Using AppGraph and AI-MSL analysis, we evaluate your applications and infrastructure across 20+ dimensions — producing a prioritized report of platform and infrastructure opportunities.
With AI-MSL, modernization is not a one-time assessment — it becomes a continuous discovery process that keeps your technology roadmap current.
Pay for Changes— Not Headcount
Traditional data projects need big budgets and long roadmaps before any metric is trusted. AI-MSL works differently — every pipeline, semantic change, and integration is a delivery-ready change you can evaluate, prioritize, approve, and measure independently.
One Completed Governed Software Change
Delivered in cycles. Governed by design.
Data evolution in 2–3 day cycles
Most data-platform work is decomposed into small, governed cycles — each delivering an independent, validated improvement to platforms, pipelines, or metrics.
Governance built into every change
Data changes still touch critical reporting, analytics, and the decisions that depend on them. Every change passes through AI-MSL governance controls before deployment.
cycles
gates
“Teams evolve the data platform without sacrificing trust, accountability, or operational control.”
Nick Chase · Chief AI Officer, CloudGeometry
What you can count on every cycle
The same shape, every time — predictable, measurable, and prioritized.
What a cycle looks like in practice
Representative changes — each delivered as one governed cycle.
One definition, governed at the source — every dashboard and model reads the same number.
Is Data Platform Evolution right for you?
You're in the right place if:
Not sure
it's a fit?
Data Platform Evolution is built for the data side of your systems. If AI capabilities are the immediate goal, AI Transformation may be the better entry path; if the application itself needs structural work, see Application Modernization — every service runs on the same governed lifecycle. Or start with the assessment, and it will point you to the right one.
Outcomes you can measure
Data evolution becomes measurable — across trust, speed, decisions, integration, visibility, and readiness for what's next.
Data Platforms Proven in Production
Production data and analytics systems evolved under governance — from telemetry pipelines to multi-tenant scientific data platforms.
Longroad Energy
Production system processing 2.5 GB of daily telemetry from 6,000 renewable energy devices. AI-MSL delivered evaluation, requirements, and implementation-ready specification through governed phases with human gates at every transition.
Now the team argues less about whose numbers are right and more about the decision.
TetraScience
CloudGeometry helped TetraScience upgrade data security and single sign-on for its life-sciences data platform — streamlining compliance and securing multi-tenancy for scientific discovery on AWS.
Our data foundations finally match the science we run on top of them.
See What Data Evolution Under AI-MSL Looks Like for Your System
Every engagement begins with a System Intelligence Assessment. You'll receive a clear analysis of your architecture, technical debt, AI-readiness, and expected AI-MSL operating cost.