AI-native risk infrastructure

See and price the MSME operator no one else can.

Trip-level intent and capability signals for logistics lending. Live with LetsTransport, Repos Energy, and BlackBuck Financials.

Live pilots and design partners

  • LetsTransport
  • Repos Energy
  • BlackBuck Financials
  • Trukkr

The gap

A creditworthy population no incumbent can see.

Traditional NBFCs

What they see
CIBIL score, financial filings
What they miss
Most truckers: thin credit files, informal or incomplete filings

Secured alt-data lenders (e.g. BlackBuck)

What they see
FASTag, toll, telematics — but only to size collateral
What they miss
Unsecured working capital need, the larger half of the gap

Invoice discounters

What they see
Formal invoices and receivables
What they miss
Operators paid in cash or UPI per trip, with no invoice at all

A large, creditworthy population is rejected or pushed to informal, higher-cost credit — not because they're unbankable, but because none of the existing players can see or price their real operating signal.

The platform

One architecture matching demand and supply.

Operators to loads, borrowers to lenders — scored on trip-level data and closed with voice AI. Three engines, one compounding loop.

Operations

AI RM

See and move your network in real time.

A point-in-time view of your operators — who is available, where they are, and what they will accept — turned into prioritised, voice-booked loads.

  • Live mobility map of the network, filterable down to a single lane
  • Close-probability scored from availability, lane history, and return-trip pull — with the reasons shown
  • Batch outreach above a chosen probability, not cold-calling everyone
  • Structured call outcomes — price, availability, yes or no — ranked for assignment

Captures supply that today goes unreached and unclosed.

See it in the demo
Finance

AI RM + AI Risk Analyst

Match the right borrower to the right lender.

A two-step loop: score the whole database on live signals, let the AI RM find who actually wants the money, then evaluate only the responders and route them to a lender.

  • Step 1 — pre-approve on trip-level signals, before any document is collected
  • Segment and batch the outreach by geography, availability, and ticket size
  • Step 2 — collect documents only from the operators who said yes
  • Route to a lender panel, each lender's own criteria layered on ours

Converts leads faster and collects documents from far fewer people.

See it in the demo
Recovery

AI Collections

Monitor at trip level, intervene before default.

Continuous portfolio monitoring at the trip level produces live default signals — and the highest-ROI response is often better terms, not harder chasing.

  • Trip-level portfolio monitoring and out-of-pattern detection
  • Live default-probability signals shared with partner banks
  • Term adjustment — lower rate or longer tenor — for high-intent borrowers
  • Repayment outcomes feed back into the models

Better recovery and higher net LTV across the book.

See it in the demo

How it works

A single loop that compounds.

Every booking, decision, and repayment sharpens the trip-level signal the next one runs on.

1Operations

Prioritise and book open supply with voice AI — and build the trip-level data set.

2Finance

Pre-approve on that data, let the AI RM find real intent, then evaluate and route to a lender.

3Collections

Monitor the book at trip level and intervene before default.

Repayment and trip outcomes feed back into every model.

Why we win

Distribution-first. Structurally hard to copy.

Distribution

Embedded via logistics-platform partnerships, not built cold.

Data

Trip-level signal others don't have.

Technology

Proprietary intent + capability models.

Expertise

Credit + applied AI, in one team.

Adaptability

Faster iteration than NBFC stacks.

Feedback speed

30–90-day working-capital cycle vs multi-year secured loans.

Timing

Early mover on trip-level unsecured working capital.

Proof

Numbers from live pilots and back-tests.

48%

Addressable-revenue uplift on initial client sample, using our intent-and-capability framework.

2.7%

Default rate on our highest-scoring rejected segment, below the approved-book average (TransUnion CIBIL MSME Pulse, 2025).

$50K

Paid pilot with LetsTransport (250K+ truckers, 30 cities).

800K+

Truck operators reachable via BlackBuck Financials partnership.

PartnerStatusScaleScope
LetsTransport$50K paid pilot250K+ truckers, 30 citiesDistribution + data; not itself a lender
Repos Energy / Repos PayLOI ongoing25K+ businesses, 220+ citiesAI risk intelligence; Repos Pay is their upcoming NBFC wing
BlackBuck FinancialsLOI ongoing800K+ truck operatorsConfirmed use of AI RM + AI Collections; risk-stack partner

Ongoing conversation: Trukkr (UAE) — early GCC-market signal, tracked separately.

Market

A $156B India wedge inside an $8T global gap.

TAM$8T

Global MSME credit gap (IFC / World Bank).

SAM$156B

India logistics-specific (working capital + truck financing).

SAM (conservative)$112–119B

Bottom-up-validated capture rate.

Expandable: ASEAN $300B, GCC $250B.

Team

Credit domain expertise, applied-AI execution.

AJ

Ayush Jain

Co-Founder & CEO

~6 years credit strategy: JPMC (Auto Credit Strategy) and American Express (Commercial Charge Card; Head of Data Strategy & AI for Commercial Wholesale Lending).

AY

Aman Yadav

Co-Founder & CTO

IIT Roorkee. LLM and voice AI product background.

BG

Ben Godwin

Strategic Advisor

Ex-Chief Underwriting Officer, American Express APAC.

Partner with us, or invest in us.