Credit risk automation platform Kaaj raises $3.8 million from Kindred Ventures

Shivi Sharma spent a decade working in credit risk at places like American Express and Faro Bank.

At some point, they realized that teams were spending equal time analyzing all types of loans — regardless of whether they were worth $100,000 or $5 million — which meant that evaluating smaller loans was ultimately an unprofitable and time-consuming process for lenders.

She and her husband, Utsav Shah, realized there was an opportunity here.

“I watched as the vast majority of small business owners couldn’t access the capital they needed to grow, simply because the economy didn’t work out for the banks,” Shah told TechCrunch.

He continued: “Between our skills in building large-scale AI-powered decision-making systems and our expertise in banking credit risk and fraud risk assessments in financial services, we knew we could apply next-generation AI agent workflows to solve this decades-old problem.”

The couple decided to launch Kaaj in 2024, a company that helps automate credit risk analysis so that underwriting takes not days, but minutes. Kaaj said it has processed loan applications worth more than $5 billion, with clients including Amur Equipment Finance and Fundr. On Wednesday, the company announced a $3.8 million seed round from Kindred Ventures and Better Tomorrow Ventures.

The product works as follows: a small business applies for a loan, submits all the required documents (such as financial statements, bank statements, tax returns) – usually, when this happens, guarantors spend days manually checking all this information and recording it in their Loan Origination System (LOS).

Kaaj uses AI to identify, classify, verify and organize information into LOS. He also performs document tampering verification assessments for the guarantor’s fraud team. It integrates with existing CRM systems like Salesforce, HubSpot, or Microsoft and shows the lender whether the company meets the lender’s policy criteria.

“This allows a team processing 500 applications per month to handle 20,000 applications with the same staff, making microloans economically viable,” said Shah, the company’s CEO.

The hope is that more small businesses will be able to obtain loans from banks because it becomes more cost effective for the bank to investigate.

Other products on the market include Middesk, Ocrolus, and MoneyThumb. Sharma hopes Kaaj will stand out from the competition by automating the entire credit analysis process rather than parts of it.

“We do this by deploying AI workflows that mimic their teams, to help lenders analyze comprehensive loan packages,” she said.

The new capital will be used to help accelerate product development and expansion across independent and small business lenders. “We are focused on enhancing our AI agent capabilities, expanding our module offerings, and expanding our client base of lenders and brokers beyond our current footprint.”

Overall, Shah and Sharma hope that Kaag can, in some way, “revolutionize” lending to small businesses, bringing automation to a process that still requires a lot of paper.

“By automating the science of credit analysis, we free up human insurers to focus on the art of dealmaking and self-assessment, which is their true competitive advantage,” he said.