DHVANI Voice Recognition for Law Enforcement
Fraudster voice identification at investigation scale.
The problem
A national law enforcement agency needed to identify fraudsters across thousands of voice call recordings — historical and real-time — across noisy conditions, multiple speakers, and multiple languages. Conventional voice biometrics failed on call-centre-grade audio and could not operate at investigation scale.
The system we built
DHVANI — a voice recognition and fraud identification system combining voice diarization, transcription, phrase detection, vector-based speaker similarity scoring, and a clustered vector lake for fraudster pattern recognition. Runs offline on historical files and in real-time on live streams.
What this means commercially
Voice-biometric forensics at investigation scale convert previously-impossible investigations into closeable cases. The commercial-equivalent value here is measured in case-closure rate and time-to-arrest — for which there is no commercial off-the-shelf alternative, and for which procurement of foreign-sourced systems is generally not permitted. DHVANI is an indigenous, deployed-in-perimeter capability with no foreign IP exposure — the kind of system regulated public-sector buyers can actually approve.
The outcome
Other systems we've shipped.
US County Deed Parser
From 70–80% accuracy to 95%+ across 240 counties.
BDO Indian Customs Document Intelligence
99% extraction efficiency on complex customs forms.
Not ready for AI yet? Want to chat about possibilities?
No pitch, no pressure. Just a conversation about where AI could fit, or where it can wait. Bring your skepticism — we'll bring ours.
Can we reproduce this outcome on your data?
A 4-week POC with signed KPIs. If it clears, we scale. If it doesn't, you keep the architecture blueprint.