Shivi Sharma spent ten years working in credit risk at places like American Express and Varo Bank.
At some point, she realized that the teams were spending the same period of time analyzing all sorts of loans – whether or not they were price $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.
“She watched as the vast majority of small business owners didn’t have access to the capital they needed to grow simply because the economics weren’t right for the banks,” Shah told TechCrunch.
“Between our skills in building large-scale AI-based decision-making systems and our expertise in assessing credit and fraud risk in banking and financial services, we realized that we could apply next-generation AI agent workflows to solve this decades-old problem,” he continued.
The couple decided to launch Kaaj in 2024, which helps automate credit risk evaluation, because of which loan guarantee now not takes days, but minutes. Kaaj said it has processed greater than $5 billion in loan applications from Amur Equipment Finance and Fundr, among others. On Wednesday, the company announced a $3.8 million seed round from Kindred Ventures and Better Tomorrow Ventures.
The product works like this: a small business applies for a loan by submitting all the obligatory documents (similar to financial statements, bank statements and tax returns) – typically when this happens, underwriters spend days manually verifying all this information and logging it into their lending system (LOS).
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Kaaj uses artificial intelligence to discover, classify, confirm and organize information into LOS. Also conducts assessments to ascertain for document tampering for the insurance fraud team. It integrates with existing customer relationship management (CRM) systems similar to Salesforce, HubSpot or Microsoft and even shows the lender if the company meets the lender’s policy criteria.
“This allows a team processing 500 applications a month to handle 20,000 applications with the same staff, making smaller loans cost-effective,” said Shah, the company’s CEO.
The hope is that more small businesses will give you the option to access bank loans because it becomes less expensive to have them checked by a bank.
Others on the market include Middesk, Ocrolus, and MoneyThumb. Sharma hopes Kaaj will differentiate itself from the competition by automating the entire credit evaluation process, not only parts of it.
“We do this by deploying agent-based AI workflows that mimic their teams to help lenders analyze end-to-end loan packages,” she said.
The fresh capital will likely be used to speed up product development and expansion among independent lenders and small businesses. “We are focused on enhancing the capabilities of our AI agents, expanding our module offerings and scaling our customer base of lenders and brokers beyond our current footprint.”
Overall, Shah and Sharma hope that Kaaj can in some sense “revolutionize” small business lending by bringing automation to what is still a paper-heavy process.
“By automating credit analysis, we enable insurers to focus on the art of the deal and subjective assessment, which is their real competitive advantage,” he said.