Behavioral intelligence, applied to your world
CentroidAI’s proprietary platform predicts change before it appears in traditional analytics — across eight industries where timing is everything.
Intelligence where timing is everything
Each FyndEm product applies the same proprietary behavioural analysis engine to a specific industry — delivering early-warning intelligence that existing tools can’t provide.
Plasma collection centers depend on a reliable, returning donor base. FyndEm Engage identifies which donors are at risk of lapsing before they stop coming, which are your most influential referral sources, and which lapsed donors are most likely to return.
- Donor churn prediction — months before lapse occurs
- Influencer network mapping — identify who drives referrals
- Lookalike analysis — find new donors who mirror your best performers
- Lapsed donor recovery prioritization
Most patients who will develop a serious chronic condition are already in the healthcare system. FyndEm Clinical analyzes existing patient data across laboratory values, medications, diagnoses, and visit patterns to surface patients who match the behavioral and clinical profile of early-stage disease — with AUC scores of 0.84 to 0.93.
- Validated models for eleven chronic disease categories
- Identifies undiagnosed patients — not just high-risk known patients
- Integrates with existing EHR infrastructure
- Missing data treated as a behavioral signal, not an error
Medical device companies invest heavily in sales teams and KOL programs — but most targeting decisions are based on historical procedure volume rather than predicted adoption behavior. FyndEm MedTech predicts which surgeons and KOLs are highest-probability adoption targets.
- Surgeon adoption scoring — ranked by predicted likelihood, not past volume
- KOL influence network mapping — training chains and peer influence
- Competitive displacement signal detection
- Integrates with existing CRM, Salesforce, and Veeva workflows
Retail and e-commerce businesses lose customers silently — purchasing frequency drops, basket sizes shrink, and by the time the trend is visible in dashboards, the customer is gone. FyndEm Retail detects behavioral shifts in transactional data weeks before churn becomes apparent, identifies customers primed for segment migration, and surfaces cross-sell opportunities hidden in purchasing patterns.
- Customer churn prediction — 60 to 90 days of early warning
- High-value customer identification and segment migration scoring
- Basket affinity and cross-sell propensity modeling
- Lapsed customer reactivation prioritization
Manufacturing quality failures are expensive — scrap, rework, warranty claims, and regulatory exposure. Most quality systems are reactive, catching defects after they occur. FyndEm Quality analyzes process parameters, sensor data, and supplier quality records to predict quality deviations before they reach downstream production or the customer.
- Quality deviation prediction — detect drift before defects occur
- Equipment failure early warning from sensor and process data
- Supplier quality scoring and incoming material risk profiling
- Root cause pattern analysis across production lines
For manufacturers selling consumables, equipment, or pharmaceuticals on recurring contracts, account retention is a constant commercial pressure. FyndEm Account analyzes your ERP order history to predict which accounts show early behavioral signs of defection and which have expansion potential — with no IT integration required.
- Account defection scoring — 3 to 6 months of early warning
- GPO and IDN peer network signal analysis
- Expansion candidate identification and prioritization
- Works from a standard ERP export — no IT integration required
University advancement offices spend significant resources on phonathon campaigns and annual giving outreach — but most calling lists are built on demographic segmentation or lapsed giving history alone. FyndEm Campus identifies which alumni show behavioral patterns most predictive of giving.
- Alumni giving propensity scoring — behavioral, not just demographic
- Re-engagement identification for lapsed donors
- Peer influence mapping within alumni networks
- Ranked, actionable calling lists for your phonathon team
Non-profit organizations depend on sustained supporter relationships — recurring donors, volunteers, and advocates whose engagement can shift without warning. FyndEm Advance identifies which supporters show early signs of disengagement, which are most likely to increase their commitment, and which lapsed donors are most recoverable.
- Supporter retention scoring — predict disengagement 90+ days in advance
- Major gift propensity identification
- Lapsed donor recovery prioritization
- Volunteer and advocate engagement prediction
One platform. Proven across eight industries.
CentroidAI’s proprietary behavioural analysis engine powers every FyndEm product — finding the signal your existing tools can’t see.
See it applied to your data — before you commit
Every engagement begins with a diagnostic — a retrospective run on your own historical data that shows what the model would have predicted before it happened. No forward commitment required.