Is Your Data Infrastructure Ready for What You're Building?
Answer 8 questions about your data platform. Get an honest assessment of where you stand — and what to fix first.
Where does your most important data live today?
How data is stored determines the cost and complexity of everything built on top of it.
Why we built this assessment
Every data platform engagement we run starts with the same conversation: how is data stored, who can access it, how do you know it's correct, and what breaks when something goes wrong? Teams that have clear answers ship ML features and analytics products. Teams that don't spend months untangling infrastructure before anything useful gets built.
This assessment tests the eight factors that determine whether your data platform is an asset or a bottleneck. High scores mean you're ready to optimize and scale. Low scores mean the foundations need attention first — and that's the more valuable finding.
Can you trace a metric from dashboard back to source?
Do you find problems or do your stakeholders find them?
Can your models and analytics serve real users reliably?
What happens after the assessment
You see your score and what it means
Each question maps to a real factor we evaluate in every data platform engagement. Your breakdown shows which areas are strong and which need work.
You book a consult if the fit looks right
Strong platform? We review it for optimization opportunities. Gaps in governance or reliability? A hardening engagement closes them. Early stage? We'll map the shortest path forward.
We define the work and execute it
Platform hardening, pipeline modernization, MLOps infrastructure, compliance automation — scoped to the gaps that matter most for your goals.
Common questions
We're early — our data is a mess. Is this still useful?
Especially useful. A low score tells you exactly where the foundations are weakest, so you fix the right things first instead of guessing. Most teams start here.
Is this for teams building ML models?
It's for anyone whose work depends on data infrastructure — ML teams, analytics teams, data engineers, and the leaders who need to trust the numbers. If your question is specifically about AI integration, our AI Readiness Assessment is a better fit.
Is this actually free?
Yes. No signup, no email gate. We built this because every data platform conversation starts with these same questions. It saves time for both of us.
What kinds of data platform work do you do?
Data lake and warehouse architecture, lineage and governance, pipeline modernization, MLOps and model serving, compliance automation, and cost optimization. Full details here.
Ready to evaluate your data infrastructure?
Take the assessment above, or skip straight to a conversation. Either way, we'll tell you honestly where your platform stands and what to prioritize.