Credit risk automation platform Kaaj raises $3.8M seed from Kindred Ventures

Shivi Sharma spent nearly 10 years in credit risk at major institutions such as American Express and Varo Bank. Over time, she noticed a recurring inefficiency: underwriting teams were spending the same amount of time analysing every loan — whether it was a $100,000 request or a $5 million deal. That meant smaller loans were slow, costly, and often unprofitable for lenders to process.

Sharma and her husband, Utsav Shah, saw a clear opportunity.

“She watched countless small business owners get denied the capital they needed to grow simply because the economics didn’t work for banks,” Shah told TechCrunch.

With their combined background — building AI-driven decision systems at scale and deep experience in credit and fraud risk for financial institutions — the two believed they could modernise the long-standing bottleneck.

In 2024, the couple founded Kaaj, a platform designed to automate credit risk analysis, enabling lenders to move from days-long reviews to decisions made in minutes. Kaaj says it has already processed more than $5 billion in loan applications, including those from Amur Equipment Finance and Fundr. The startup has now raised a $3.8 million seed round, led by Kindred Ventures with participation from Better Tomorrow Ventures.

How Kaaj works

A small business submits its loan application with financial statements, tax returns, and bank records. Traditionally, underwriters manually verify and enter this data into their Loan Origination System (LOS), a process that can take days.

Kaaj automates these steps using AI that can:

• Identify and classify documents

• Extract and verify financial data

• Detect potential tampering for fraud checks

• Organise information into the lender’s LOS

It integrates with major CRMs such as Salesforce, HubSpot, and Microsoft, and can instantly assess whether a business meets a lender’s underwriting guidelines.

“This allows a team processing 500 applications a month to handle 20,000 with the same staff, making smaller loans economically viable,” said Shah, who serves as Kaaj’s CEO.

The founders hope this efficiency shift will help more small businesses qualify for loans, since banks will be able to evaluate them at a sustainable cost.

Competition and product vision

Other players in the space include Middesk, Ocrolus, and MoneyThumb. Sharma believes Kaaj can differentiate itself by automating the entire credit analysis workflow, not just parts of it.

“We deploy agentic AI workflows that operate like full underwriting teams, helping lenders evaluate loan packages end-to-end,” she said.

What’s next

With the new funding, Kaaj plans to expand its product offering, strengthen its AI agent capabilities, and grow across independent banks and small business lenders.

Ultimately, Sharma and Shah hope to modernise a system that remains highly manual and paper-heavy.

“By automating the science of credit analysis, we free up human underwriters to focus on the art of deal-making — which is where their real competitive advantage lies,” Shah said.