The Trust Layer for
Autonomous AI
AI agents make million-dollar decisions every second. We independently verify they are right — before the money moves.
325+
Verified Predictions
15
Live Data Streams
2
Independent AI Councils
24/7
Continuous Operation
The Problem
Autonomous agents operate without verification
No Independent Verification
Agents self-validate their own outputs. When the model is wrong, there is no external check. Errors compound silently until real money is lost.
No Accuracy Tracking
Nobody grades whether AI predictions were actually correct. Without calibration data, agents cannot learn from mistakes or improve over time.
The Cost Is Real
A single wrong autonomous decision can cascade across markets in milliseconds. The cost of being wrong is no longer theoretical.
Our Solution
Multi-model debate engine with graded accuracy
Two independent councils of frontier AI models from different architectures — Anthropic, OpenAI, Google, xAI — receive identical raw intelligence and debate until they reach a verdict.
Epistemological Arbitrage
When models agree, confidence is high. When they disagree, that divergence is a signal nobody else can see — pure informational arbitrage.
Reality-Graded Predictions
Every prediction is timestamped, stored, and later graded against real-world outcomes. We do not just predict — we prove whether we were right.
Verification API
Plug our trust layer into your autonomous agents via a simple API call. Your agents stop guessing. They start knowing.
How It Works
From raw data to verified intelligence
01
15 Data Streams
Insider trades, legislation, prediction markets, macro indicators, options flow, and more
02
Multi-Model Debate
Independent AI councils from 4+ providers analyse, debate, challenge, and reach a verdict
03
Graded Output
Timestamped prediction with confidence score, later graded against real-world outcomes
04
Calibration Loop
Accuracy data feeds back into the system, making every cycle smarter than the last
Our Moat
A database that cannot be replicated
Every prediction cycle adds another data point to our growing ledger of timestamped forecasts graded against real-world outcomes.
After 12 to 18 months, this becomes institutional knowledge that no competitor can replicate without living through the same thousands of real-world resolutions. The database is not a feature — it is the product.
Company
Abstract Essence Ltd
Incorporated 24 February 2026
Company No. 17050130
71-75 Shelton Street, Covent Garden
London WC2H 9JQ, United Kingdom
Live since February 2026
Predictions generated every 2 hours
Graded against reality twice daily
Leadership
The team behind the engine
Marcin Sobczak
Founder & Director
Architecting the risk engine for high-stakes autonomous decisions. Abstract Essence was founded to build sovereign intelligence infrastructure, providing the missing verification layer for the agentic web through multi-model adversarial debate.
View LinkedIn Profile