Fintech founders compete against incumbents with thousand-person risk teams. AI is the equalizer. The ones who deploy the intelligence layer underwrite smarter, detect fraud faster, and scale without proportionally scaling compliance headcount.
Fintech founders compete against incumbents with thousand-person risk teams. AI is the equalizer. The ones who deploy the intelligence layer underwrite smarter, detect fraud faster, and scale without proportionally scaling compliance headcount.
Fintech founders compete against incumbents with thousand-person risk teams. AI is the equalizer. The ones who deploy the intelligence layer underwrite smarter, detect fraud faster, and scale without proportionally scaling compliance headcount.
The operators already deploying intelligence in fintech — and what they are doing with it.
ML-native fraud detection across $1T+ processed
AI-native finance operations platforms for growth companies
AI underwriting replacing FICO-only consumer lending decisions
Real-time data infrastructure powering 10K+ fintech apps
Most fintech operations still run on batch jobs, Excel reconciliations, and weekly fraud reports. The customers who defraud you this afternoon won't be flagged until next Tuesday. The layer closes that window to seconds.
Each layer is modular. Pick what ships first based on your diagnostic — we build, we measure, we expand.
Every transaction scored in milliseconds across device, behavior, and network signals. Fraud caught before settlement.
Applications scored with hundreds of signals beyond FICO. Approval rates up, default rates down.
Identity verification, document checks, and sanctions screening in under sixty seconds.
AML/CFT rules plus ML-based anomaly detection. False positives collapse, true positives rise.
AI-handled tier-1 inquiries with full transaction context. Human support only touches the hard cases.
Portfolio health, fraud trends, underwriting performance, unit economics — one live picture for leadership.
No three-month discovery phases. No decks that pretend to be strategy. Ship one layer, prove the numbers, scale.
Operational audit against the system you actually run — and the one you think you run.
Build one capability layer on your real data. Small surface, production-grade quality.
Hard numbers against baseline. Ship, scrap, or expand — data decides, not feel.
Documentation, training, handover. Pulso stays on retainer only if the system still needs us.
One call. Thirty minutes. We tell you which layer ships first — or we tell you you do not need us yet. Honest either way.