Before

Months of work to bid on a portfolio.

Retail NPA portfolio evaluation took months — constraining competitive bidding speed. The process required manual segmentation, regulatory compliance checks across SARFAESI and DRT, and analysis spanning legal, technical, field-ops, and executive disciplines. Analyst subjectivity introduced inconsistency. Key-person risk compounded with every senior departure.

With Colrows

Semantic reasoning, end to end.

A semantic reasoning layer combining ML for bulk scoring with a knowledge graph for regulatory interpretation and edge-case handling. The AI agent synthesises historical data, legal heuristics, and institutional knowledge — producing an auditable reasoning trail behind every bid rationale.

What changed in production.

>95% Reduction in evaluation cycle time (months → hours)
100% Regulatory coverage — RBI SARFAESI & DRT modeled
Expert disciplines unified: legal, technical, field, executive
100% Auditable reasoning trail behind every bid rationale

“The investment committee didn't ask us to justify the number. For the first time, the number came with its own justification — traceable to regulation, to precedent, to the account itself.”

Post-deployment reflection

Bid faster. Defend the number.

Auditable, regulator-grade AI for portfolio evaluation, risk, and compliance — without sacrificing speed.