80% Oracle, 2020
"We have tons of data, but don’t use it."
Over 80% of enterprise data goes completely unused, not because it isn't valuable, but because preparing and analyzing it takes forever.
Self-building AI Data Scientist
AI,
that builds AI. Autonomous, Understandable.
For All.
Get from raw data to working AI models and explained business insights, without a PhD or a data science team.
The Problem
Sound familiar?
These aren't edge cases. They're the everyday reality for finance teams trying to do more with their data.
85% Forbes Tech, 2024
"Our AI projects keep failing."
85% of ML projects fail before they ever ship, usually because the underlying data was never properly cleaned or understood.
3.9M McKinsey, 2025
“Our ML Engineers, Data Scientist, and specialists’ capacities are too small or their overloaded”.
McKinsey estimates the AI talent gap at 1.4 to 3.9 million people by 2027 in Europe alone.
95% Dataiku, 2025
"We don't trust what the AI is telling us."
Black-box AI isn't just frustrating, in finance and regulated industries, it's a liability. If you can't explain the reasoning, you can't use it.
An autonomous solution could help to fill these gaps.
Solution
From raw data to explained insights in three steps
Subheadline...
Upload your data
Errors, gaps, and anomalies detected and fixed. Automatically.
Run your analysis or model
Platform selects, builds, and validates the right model tests for your selected task.
Understand the Why
Causalities, not correlations. Every decision logged and traceable.
Under the Hood
Built different, from the ground up.
Four components, each a technical first - working together as one autonomous system.
Self-Validating Data Engine
Our AI tests its own cleanup results before passing anything forward. The data you model on is actually clean.
Autonomous Model Builder
Like a data science team on autopilot. It selects, builds, trains, and validates the right model — without you configuring anything.
Business Worldmodel
A causal knowledge graph that learns how your business works over time and uses that context to make smarter, more stable predictions.
Full Explainability & Audit Layer
Every step is logged. Every decision is traceable. Built for regulated industries and the EU AI Act from day one.
Pilot Access / MVP
We're building this with our first customers.
The MVP is in its final stages. We're currently selecting a small group of pilot partners, finance teams and financial service companies in the DACH region who want to be first to see what autonomous AI actually looks like in practice.
- No commitment.
- Real data. Real results.
- Shape the product roadmap
Founder Note
Why I'm building this
"I spent five years in finance watching revenue streams, financial services and multi million Euro decisions run on fragile, manual Excel processes, only because real, custom AI solutions were too complex and too opaque to use. I built Neuroloop to fix that."
Rasmus, Founder & CEO