The situation
A PE firm acquires a mid-size B2B SaaS company at a premium valuation. The investment thesis rests on three pillars: deploy AI to improve net revenue retention, monetize the platform’s usage and behavioral data as a commercial product for channel partners, and reduce SG&A through operational efficiency. At close, eight years of user behavior, product telemetry, and customer outcome data exist across a product database, a CRM, a billing system, and an event telemetry warehouse, with inconsistent schemas and no governance layer. The PE firm’s operating partner has a specific question about the AI already running in the platform — pricing recommendations, churn prediction, upsell suggestions — that needs to be answered with documented evidence.
The solution
The Knowledge Fabric™ connected the product database, CRM, billing system, and event telemetry warehouse. Entity resolution reconciled user, account, and product identifiers across all four systems. The same governed foundation serves the product team’s AI models and the operating partner’s workbench view simultaneously.
Data Commerce mapped the platform’s usage telemetry and product performance data to channel partner archetypes. GDPR and CCPA treatment was applied at the field level — default treatment for uncertain fields is exclude, not pass-through. Governed data products launched with a PolyPhaze Trust Score™ in every API response header. Freshness monitoring holds delivery automatically if data staleness exceeds the contracted SLA.
AI Decision Trace established a governed baseline across pricing recommendations, churn prediction, and upsell suggestions. Post-deployment monitoring caught three instances of the recommendation engine operating outside its intended decision boundaries before any customer outcome was affected.