Your Data Team. Ready Now
Most companies know data can transform their business. Few have the team to make it happen. We embed as your data organization — from strategy to production — solving the specific problems that actually move your numbers.
The ProblemYou don’t need a dashboard. You need outcomes.
Hiring a Chief Data Officer, building a team, choosing the right stack, and delivering projects takes 12–18 months and millions in payroll before you see a single result. Meanwhile, the problems you need solved — pricing inefficiencies, manual workflows, disconnected systems — keep costing you money every day.
Why this isn’t an IT problemA data team and an IT team solve fundamentally different problems.
Your IT team keeps the business running. They manage infrastructure, maintain systems, handle security, and make sure everyone can do their jobs. They’re essential — and they’re fully committed to that mission.
A data team does something different entirely. A data team looks at your operation and asks: where are we leaving money on the table? What decisions are we making on gut feel that we could make on evidence? What patterns are hiding in our transactions, our customers, our pricing?
What a data team actually does
A data team identifies the business problems where data is the answer — not more software, not better processes, but actual intelligence extracted from the information you’re already generating. They build the models, the applications, and the workflows that turn that intelligence into daily decisions your people make better, faster, and more consistently.
This means building pricing engines that know each customer’s elasticity. Entity resolution systems that tell you who your real customers are. Risk models that set credit limits automatically. Fraud detection that runs in real time. And critically — the applications that put all of this in the hands of the people who need it, designed so they actually use it.
IT Team
Measured on uptime, security, and system reliability
Manages infrastructure and maintains existing systems
Ensures everyone can do their jobs
Tools: ERP, CRM, networking, cloud infrastructure
Data Team
Measured on business outcomes: revenue recovered, risk reduced, decisions improved
Builds new intelligence from existing information
Changes how decisions get made
Tools: Databricks, graph databases, ML models, neural networks
Most companies that try to bolt data initiatives onto their IT department end up with dashboards nobody looks at and projects that never make it to production. Not because IT failed, but because they were asked to do a job that isn’t theirs.
Why IT can’t fill this role
It’s not a question of capability — it’s a question of mission. These require different skills (machine learning, statistical modeling, data engineering), different tools, and a fundamentally different way of approaching problems. Asking IT to do data science is like asking your accountant to do strategy — they’re both critical, but they’re not the same discipline.
Most companies that try to bolt data initiatives onto their IT department end up with dashboards nobody looks at and projects that never make it to production. Not because IT failed, but because they were asked to do a job that isn’t theirs.
What we doWe operate as your data team
We do the work a CDO and their organization would do — but focused entirely on solving the business problems that matter most to you right now. No org charts to fill. No roadmap debates. Just solutions in production.
We start with a specific problem, build the solution, and make sure your people actually use it. That last part is where most data initiatives die. It’s where we thrive.
How we work
We don’t hand you a model and walk away. We build the full workflow — the application your team touches every day, the intelligence running behind it, and the change management that makes adoption inevitable.
01. Identify
We find the highest-leverage data problem in your operation — the one where solving it changes how your team works.
02. Build
We design and ship the complete solution: applications, models, data pipelines, integrations — whatever the problem requires.
03. Embed
We roll it out in a way your people trust and use. If the sales team ignores the tool, we failed. So we build for trust first, optimization second.
The PatternWe solve the first problem, and the data reveals the next one. Entity resolution leads to better AML. A debt tracker uncovers millions in hidden exposure. A fraud model becomes an operational risk platform. This is what it looks like to have a data team that thinks like owners — we don’t stop at the deliverable, we follow the problem wherever the data takes it.
Is this for you?
You’re a mid-market company that knows data should be a competitive advantage but doesn’t have — and may never need — a full-time data organization. You have a specific problem that’s costing you real money, and you want it solved, not studied.