Shivi Sharma has worked in credit risk for 10 years at companies such as American Express and Varro Bank.
At one point, she realized that her team was spending the same amount of time analyzing every type of loan, whether it was worth $100,000 or $5 million. This means that valuing small loans is ultimately an unprofitable and time-consuming process for lenders.
She and her husband, Utsav Shah, recognized an opportunity here.
“She saw that the vast majority of small business owners couldn't access the capital they needed to grow, simply because the economy wasn't going well for banks,” Shah told TechCrunch.
“Between our skills in building large-scale AI-powered decision-making systems and our expertise in assessing credit and fraud risks in banking in financial services, we realized that we could apply the next generation of AI agent workflows to solve this decades-old problem,” he continued.
The couple decided to launch Kaaj in 2024. Kaaj is a company that helps automate credit risk analysis so underwriting takes minutes instead of days. Kaaj said it has processed more than $5 billion in loan applications with customers such as Amur Equipment Finance and Fundr. The company announced Wednesday that it has secured a $3.8 million seed round from Kindred Ventures and Better Tomorrow Ventures.
This product works as follows: Small businesses apply for loans and submit all required documents (financial statements, bank statements, tax returns, etc.). Typically, when this happens, the underwriter spends several days manually verifying all this information and recording it in the Loan Origination System (LOS).
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Kaaj uses AI to identify, classify, verify, and organize information into LOS. We also perform assessments to check for document tampering for insurance company fraud teams. It integrates with existing customer relationship management (CRM) systems, such as Salesforce, HubSpot, and Microsoft, and can also display lenders if your business meets the criteria of the lender's policies.
“This will enable a team that processes 500 applications per month to process 20,000 applications with the same staff, making it economically viable even for small loans,” said Shah, the company's CEO.
It is hoped that more small and medium-sized enterprises will be able to obtain loans from banks, as it will be more cost-effective for banks to investigate small and medium-sized enterprises.
Others on the market include Middesk, Ocrolus, and MoneyThumb. Sharma hopes Kaaj will stand out from its competitors by automating the entire credit analysis process, rather than just parts of it.
“We accomplish this by deploying agent AI workflows that mimic their teams to help lenders analyze end-to-end loan packages,” she said.
The new capital will be used to accelerate product development and expand across independent and small business financial institutions. “We are focused on enhancing the capabilities of our AI agents, expanding our module offering, and growing our lender and broker customer base beyond our current footprint.”
All in all, Shah and Sharma hope Kharji can somehow “revolutionize” small business lending, automating processes that still require a lot of paper.
“Automating the science of credit analysis frees up human underwriters to focus on the art of deal creation and subjective evaluation, which is a real competitive advantage,” he said.