Your portfolio company is sitting on a goldmine of operational data trapped inside disparate ERPs, CRMs, and spreadsheets. We forward deploy engineers who unify it and build the system around it — AI-native, and architected to how your business actually operates.
Most portfolio companies don’t have a data problem. They have a visibility problem — the data exists, it’s just scattered across systems that don’t talk. We get credentialed into those systems on day one so we can make the data talk.
There is no single right architecture for solving that. Sometimes the answer is an enterprise warehouse. Sometimes it is a custom system our engineers build end to end — the ingestion, the transformation, and the interface itself. We make that call based on how your business actually operates, and we are equipped to build it either way.
We build the system the business needs instead of bending the business to fit a platform’s assumptions. Ingestion, transformation, and the application layer — written by our engineers with AI in the loop for efficiency.
Sometimes a warehouse is correct — Snowflake, Databricks, Fabric, Postgres. Sometimes it is not correct. The decision is based on a variety of reasons.
ERPs, CRMs, billing, payroll, and the operational tools nobody wants to keep reconciling — connected by pipelines our engineers build and agents watch, reconcile, and repair when a source system changes underneath them.
Power BI and Tableau when you already own them. Increasingly, custom front-ends we build ourselves — the exact views leadership runs the business on, with no per-seat license and no dashboard nobody opens.
Semantic models, governed metric definitions, and the tool interfaces that let AI agents query your business reliably. The difference between an agent that answers correctly and one that guesses convincingly.
Leadership asks in plain language and gets the number with the lineage behind it — no report request, no analyst in the middle, no waiting on the Monday deck.
Clean customer, vendor, product, and account hierarchies — with AI doing the matching, dedup, and exception triage that used to eat an analyst’s week, and rules that hold after we leave.
Demand, pricing, cohort, retention, and propensity models built in Python and SQL, with frontier models where they outperform — no black boxes, and the IP stays with you.
NetSuite, D365, SAP, and Sage rollouts with AI-accelerated chart-of-accounts mapping — plus operational data diligence for sponsors: what’s real, what’s reconstructed, and what the data is hiding.
We map the systems, pressure-test the data quality, interview the people who consume the reporting, and find the shortest path to the answers leadership is missing. Days, not a six-week assessment.
We build the pipelines, the data layer, and the interface — with AI compressing work that used to take quarters. You see working software in the first weeks, not an architecture diagram. We embed alongside the in-house team as we go.
We stay on as Interim Head of Data, or transition to your team with full source, documentation, and training. The IP stays in the business.
Tell us what you can’t see today and we’ll scope the system that answers it — sized to your business, not to a platform license.
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