What we help you get right before you build
Every data investment downstream of these four decisions succeeds or fails based on how clearly you answered them. We help you answer them before a platform vendor does it for you.
Governance
We assess whether your data is trustworthy, traceable, and defensible — before you build AI on top of a foundation that hasn't been tested.
Engineering
We clarify what your pipelines actually need — batch versus streaming, tolerance for latency, real ingestion volumes — before you commit to a pattern or tool.
Warehousing
Snowflake, Databricks, Fabric, Redshift — the vendor will tell you they're the answer. We help you select the platform that actually fits your scale, team, and budget.
AI Readiness
A notebook on your laptop is not a production AI system. We map the real path from where you are today to autonomous agents that run reliably — no vendor spin.
Strategy first.
Implementation is your call.
We don't build platforms — which means we have no interest in selling you one. Our only goal is giving you the clearest possible picture of where you stand and the most confident path forward.
No implementation stake.
No platform bias.
The reason most data advisory fails is that the advisor benefits when you buy. We don't implement — so our only incentive is making sure you choose right.
One architect. Every call.
Every engagement runs through Dan Matkins — 25 years building enterprise data infrastructure. You talk directly to the architect, not a junior analyst reading from a playbook.
We don't sell platforms.
We don't implement technology — which means we earn nothing from vendor relationships. Our platform recommendations are shaped entirely by what fits your organization, not what pays a referral fee.
Clarity your team can act on.
Strategy documents, roadmaps, and vendor evaluation frameworks your internal team or implementation partner can execute independently. You leave with confidence and a plan — not an ongoing dependency on us.
Start with a strategy conversation.
Tell us where your data stands today. We'll come back with an honest read on what it takes to move toward trustworthy AI — and whether we're the right fit to help you get there.