Counter Signal

Inspiration

Most agents today can search the web, summarize information, and generate reports. But they usually stop at one question:

Is this claim true?

CounterSignal started from a different question:

What is that truth worth?

In the real world, not all information has the same value. A claim verified by multiple fresh, independent sources should not be priced the same as a weak or uncertain claim. Even more importantly, contradiction should not always be treated as failure. In markets, hiring, funding, product launches, and company strategy, disagreement between sources is often the most valuable signal.

That became the core idea behind CounterSignal:

SuperBrain tells you whether a claim is true. CounterSignal tells you what that truth is worth.

What it does

CounterSignal is an agentic intelligence system that takes a live claim, gathers evidence from the open web, scores the evidence, and dynamically prices the result.

The system classifies every claim into one of three outcomes:

1. High-confidence intelligence
   When multiple strong sources support the claim, it becomes premium intelligence.

2. Contradiction signal
   When sources disagree, the claim is not discarded. It becomes a paid contradiction signal, because market confusion itself is valuable.

3. Blocked claim
   When confidence is low and there is no meaningful contradiction, the system blocks the claim instead of publishing weak intelligence.

The pricing logic is based on:

$$ price = f(confidence, contradiction, freshness) $$

Where:

• Confidence measures how strongly sources support the claim.
• Contradiction measures how much sources disagree.
• Freshness measures how recent and relevant the evidence is.

How we built it

CounterSignal follows a simple but powerful flow:

Claim → Evidence → Confidence → Price → Payment → Provenance

## Accomplishments that we're proud of

## What we learned

## What's next for Counter Signal

Built With

• datadog
• nimble
• python
• senso