Industry point of view
In life sciences, governed data isn't a compliance cost. It's the growth asset.
Most life-sciences leaders expect AI to transform their organizations — very few have actually scaled it. The difference isn't ambition or budget. It's whether the validated data foundation was built once, properly, so every audit, submission, and AI initiative stops being a fire drill.
What we see across the industry
Quality, regulatory, and commercial data live in separate validated systems — quality management, lab information, CRM, ERP — and cross-functional reporting still means manual exports and re-keying. Audit-readiness demands traceable, governed data that most mid-market firms assemble by hand, under deadline, every time.
Meanwhile the validation burden makes teams afraid to touch legacy systems, so workarounds multiply — and long sales and trial cycles make forecasting nearly impossible when pipeline, distributor, and field data never join up.
The regulatory direction is unambiguous: governance-first AI is becoming an expectation, not an option. The operators who treat that as an asset — one governed foundation feeding every audit and every model — are separating from the pack right now.
The research
The scale gap is measurable
Our experience here
Work we've already done in life sciences
Our life-sciences work runs deep. For Edwards Lifesciences, OBIS built an end-to-end quarterly board reporting package. For Northwestern Medicine, we built a proprietary modeling and simulation tool that shows physicians and private practices what going private — or public — would mean financially: custom data automation, workflow, UI/UX, and dashboard design in one product.
For Akina Pharmacy, we delivered full sales-cycle analytics that track attrition over time, plus a compounding-room workflow tracker that puts the day's compounds on the board and gives the team two weeks of forward visibility into how incoming orders hit the compounding schedule. And for Caregility, a healthcare-technology platform, we built the dashboard tracking online traffic, conversions, and spend. Behind all of it: a governance practice led by audit-trained practitioners (CPA, CFE) who speak validation and traceability natively.
“Great to work with. Excellent quality work!”
Where to start
Data & AI Governance & Architecture
The blueprint and the controls in one practice — modern data and AI architecture designed for scale, governed by audit-trained practitioners.
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Led by Jacqueline DeStefano-Tangorra, CPA, CFE, CDMP
Founder & CEO, Omni Business Intelligence Solutions
Forbes Technology Council member · Featured by the Wall Street Journal, Business Insider, CNBC, NASDAQ, and Microsoft
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