Problem💯 When a small business by Muhammad AdreesProblem💯 When a small business by Muhammad Adrees

Problem💯 When a small business

Muhammad Adrees

Muhammad Adrees

Problem💯 When a small business applies for a loan or cash advance, an underwriter has to answer one question: can this business pay us back? To answer it, they manually review months of bank statements, tax returns, and business documents, calculating cash flow, spotting risks, scoring against the lender's policy, and writing a recommendation.
This takes a skilled human 4-8 hours per file, and lenders process hundreds per week. It's slow, expensive, and two underwriters often reach different conclusions on the same file.
What we built🙌
- A platform that compresses this work from hours into minutes, while keeping a human in control of the final decision.
- The system ingests applications and supporting documents, extracts and validates the underlying financial data, evaluates it against the lender's risk policy, and produces a reviewable recommendation the underwriter can approve, modify, or reject.
- AI handles the heavy lifting, reading documents, summarizing patterns, generating draft assessments.
Outcomes🎉
- Underwriting review time reduced from ~6 hours to under 30 minutes
- 5-10× more files processed per underwriter
- Eliminated manual data entry from bank statements
- Consistent, explainable decisions with full audit trails
Stack🧰
FastAPI, Python, PostgreSQL, Redis, GCP, React, TypeScript, and a mix of LLM and document-AI tooling.
Best fit for🔥
Lenders, fintech startups, credit and risk teams, MCA/lending platforms, and anyone building AI for financial workflows where decisions need to be fast, auditable, and trustworthy.
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Posted May 19, 2026

Problem💯 When a small business applies for a loan or cash advance, an underwriter has to answer one question: can this business pay us back? To answer it, ...