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Marlith
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#12954 Radar 4

AI analyzes loan applications from CSV data for instant decisions.

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Product memo

Lenders use Marlith to automate loan application analysis, making faster, data-driven decisions. It processes borrower CSV data directly, bypassing traditional credit bureaus and manual reviews. The engine delivers instant approve/review/reject decisions, recommended loan amounts, and key financial metrics. This approach targets lenders who prioritize rapid processing and performance data without complex integrations.

For who
Lenders analyzing loan applications
Solves what
Automates loan application analysis using cash flow data for faster, better decisions.
  • CSV upload for underwriting
  • Instant credit decisions
  • Automated financial metrics

In their own words

Marlith — AI Loan Decision Engine

Make smarter loan decisions using cash flow data. Drop a borrower CSV, get a clean credit decision, recommended loan amount, and a defensible audit trail — instantly.

Operator & company

Company

Founded

May 2026

Operating model

Business model

Saas

Platform

Web app

Audience

Sales

Product channels

Builder strategy

ProvenRadar analysis

Strategy Type
Niche Specialist
Stage
Vc Growth
Effort
Solo Buildable

Commercial cues

Model
free only
Free tier
Yes
Trial
No

Pricing strategy

Marlith offers a free tier; paid plan details are not publicly priced.

  • A free tier lets lenders test CSV analysis without commitment.
  • Annual pricing targets high-volume lenders processing billions in originations.
  • No-signup friction removes barriers to initial product adoption.
About Marlith Expand

Marlith provides an AI-powered engine for lenders to automate loan application analysis. It helps make smarter loan decisions by analyzing cash flow data directly from borrower CSV files.

This approach offers instant credit decisions, recommended loan amounts, and a defensible audit trail, all without relying on traditional credit bureaus. Marlith targets lenders who need rapid processing and performance data to simplify their underwriting process and improve decision accuracy.