Wispr Flow - Don’t type, just speak
Mini tools
LLM-powered credit scoring that outperforms classical models.
SquareGen
Finbots
Overview
SquareGen installs proprietary GPT-style scoring systems inside lenders. We take your tabular credit, fraud, or portfolio data, translate it into a representation an LLM reads semantically, and fine-tune a model that produces calibrated default probabilities, a risk class, and a written rationale for every decision.
The output reads like a senior analyst's note, not a feature-attribution chart, which makes it defensible in front of a risk committee, a regulator, and a board.
Variables drop by 50 to 80 percent versus classical stacks, lowering bureau and data-source costs while keeping or beating incumbent AUC. The model lives inside your environment, runs without us, and is yours: weights, source, pipeline, and documentation transferred at close.
It complements rule engines, scorecards, and machine-learning models you already operate rather than replacing them. PoC under NDA in two to four weeks, benchmarked against your incumbent on your own data.
Supported features
Releases
Quantum Computing and Machine Learning specialist with over 15+ years of experience. Ph.D. in Quantum Computing and Master in Data Management. Certified in quantum technologies by BIMTECH, MIT xPro, KAIST, IBM, and Saint Petersburg University. 35+ machine learning and AI projects and 5+ quantum software application prototypes executed.
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