POVA is an AI investigator. Give it the records, logs, and contracts you already have. It cross-checks everything against everything else, and where timelines, facts, and relationships stop fitting their context, it builds you a case. Sometimes that’s an operational or financial misalignment. Sometimes it’s a hidden agenda, or someone quietly connecting things that were never supposed to touch.
People, vendors, accounts and service identities. Not anonymous anomaly scores.
Amounts, accounts, and the exposure at stake, reconciled against the ledger.
What happened, in order, with the timestamps that put it there.
Who is connected to whom, including the ties nobody declared.
Ripple effects across systems, the vendors and people someone brought along, the slow siphoning that stays under every threshold.
Every claim points to the file, row, and log line it came from.
The innocent readings, tested and either ruled out or left standing.
What to do Monday: revoke, recover, escalate, or close it out.
Coverage, method, and what was not examined. Stated, not implied.
Anonymized from a live case. This is the unit of work, not a chart.
Anonymized from real engagements. Ask us for the specifics under NDA.
Dormant elevated access and after-hours system activity.
Privileges kept after role changes. After-hours access that bypassed change management. Gaps in the audit trail.
Access revoked, logging enhanced, regulator informed.
Earnings and inventory stopped matching the evidence around them.
Likely manipulation, concentrated around a management change, with dates, amounts, and the people involved.
Evidence package handed to the legal team.
Subcontractor billing that didn’t line up across properties.
Divergent billing, recurring maintenance issues, and work-order timing that pointed to padding.
Contracts renegotiated, preventive maintenance put in place.
The analysis never touches the internet. POVA runs on your hardware, or on POVA BOX, a sealed offline appliance. Your data stays in the room it started in.
POVA is built by Roy Daya. He has spent more than 25 years getting reliable answers out of data, across fraud investigations, industrial safety systems, and audit analytics. He holds a Kellogg MBA and founded AppliedML, the computer-vision company with more than fifty AI solutions running on industrial sites.
LINKEDIN →On a scoping call, an expert works through your data with you and tells you straight: is there a case here, and what is it worth.
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