Top Finance Technology Startups in 2027

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160 million Americans lack access to mainstream credit. Our low interest credit card and financial literacy app give people an opportunity to improve their credit and personal finances. Backed by behavioral finance, our integrated financial literacy system helps customers use credit responsibly and develops a proprietary underwriting platform that can expand access to other financial products all at fair rates.

InfinityPool Finnotech is a financial technology company building AI-native products at the intersection of wealth, markets and intelligent decision-making. Our flagship platform, Shankh Wealth, combines technology, data and AI to help investors understand their complete financial picture and access suitability-led wealth advisory. The broader Shankh ecosystem also includes Shankh School, focused on practical financial education. MANTHN turns fundamental, technical, sentiment and market data into actionable market intelligence, while MarketLink provides the connectivity and infrastructure required to bring together market data, brokers and investing workflows. We are also building Decuple, an AI-native suite designed to make business workflows across areas such as content, talent and revenue significantly more intelligent and productive. Across our products, our approach is the same: combine deep domain expertise, data, AI and thoughtful product engineering to solve real-world problems. We are a small, ambitious team building from India for opportunities that can scale globally.

We’re building MIRA, an AI-powered co-pilot embedded inside mortgage lenders’ LOS/POS platforms that streamlines fragmented, manual workflows like eligibility checks, document review, and loan structuring. Today’s mortgage process remains slow, costly, and frustrating—despite digital front-ends, the backend remains inefficient with over $11K in average loan origination costs. MIRA automates decision-making and support tasks using agentic AI models built on Azure and Google Gemini, helping borrowers self-qualify, aiding loan officers with scenario planning, and improving throughput across processing and underwriting—without replacing core systems. Our plug-and-play orchestration layer helps lenders modernize incrementally while improving borrower experience, sales velocity, and operational efficiency. We’ve deployed with our first enterprise client, have two more implementations underway, and are in discussions with multiple banks and IMBs. MIRA is backed by a veteran mortgage team with 20+ years of experience, combining deep domain expertise with next-gen AI capabilities.

Financial advisors can model almost everything a client owns except their real estate, which is often 30 to 50% of their net worth. The data is spread across tax returns, closing files, and loan statements, it changes from year to year, and some of it only the owner knows. Leveridge turns that into numbers an advisor can stand behind. AI reads the documents and pulls out the facts. A deterministic engine computes depreciation, basis, recapture, and federal and state tax, to the dollar. Every figure is marked confirmed or estimated, so the advisor knows which numbers to check. The hard problems are reconciling documents that disagree, measuring whether a model got it right, and keeping tax math exact. We launched in May 2026, 13 advisory firms pay for it, and we're raising our pre-seed. The stack is Python, FastAPI, PostgreSQL, React, and TypeScript on AWS. We're four people, fully remote, based in Los Angeles. Davis, our founding engineer, built financial planning simulation software before this. Ali and Rick bring years in wealth management and real estate. Engineers here own whole problems, talk every week with the advisors using their work, and ship in days.