How Preuve works, and what the score means
Preuve AI doesn't rate your idea from training data. Ten agents pull live evidence from 50+ sources, score it 0-100 on six factors, and link every claim to a source you can click. No training-data guesswork, no flattery.
Every claim audited across 246 paid reports.
How does Preuve AI work?
Validation runs as a multi-agent pipeline. You give it one paragraph; it returns a cited verdict in about a minute.
You describe the idea
One paragraph: what you are building, who it is for, how it makes money. No deck, no spreadsheet.
10 agents query in parallel
Each agent owns one domain and pulls live evidence from 50+ data sources.
Findings are cross-validated
When two model runs disagree, the verdict reruns until they converge.
You get a cited 0-100 score
Six factors, one number, a source URL behind every claim, plus risk flags and 2-3 pivots that could lift it.
What does the score measure?
Market size & growth
Bottom-up TAM/SAM/SOM and whether the market is expanding or shrinking.
Real demand signals
Whether people search for, complain about, or pay to solve this. Not a hunch.
Competitive density
How crowded the space is and whether incumbents already solve it well.
Moat durability
How easily the idea is copied, and what makes it defensible.
Business model viability
Pricing power, acquisition cost reality, and a path to margin.
Regulatory & execution risk
Legal, compliance, and operational blockers that quietly kill ideas.
What does your viability score actually tell you?
Launch-readygo
Strong signals across the board. Only about 18.3% of scored ideas reach this band, where most AI validators hand out a 75-85 to nearly everything.
Worth reshapingconditional
Where most ideas land. Positioning, target, timing, or crowding is holding it back. A sharper angle often moves the number 10-20 points.
Strong headwindsno-go
The market is signaling hard against the idea as framed. Rethink the core, not the wording, before you write code.
It does not score you
It rates the idea and its market, not your ability to execute.
It is not a guarantee
A probability read on public evidence available today.
It is a snapshot, not a verdict
Change the target, positioning, or timing and the number moves.
What a low score is really telling you
A low score is a direction, not a verdict. It usually means one of these, and each is fixable before you build.
The market is crowded
15+ competitors already doing this. You need a sharper angle than the incumbents.
The timing is off
The market may not be ready, or it peaked two years ago.
The positioning is wrong
Same product, different framing, different score. One idea tested across four angles ranged from 42 to 66.
The target is too broad
Narrow to a specific buyer and the demand signals sharpen.
What is open, and what stays under the hood
The exact factor weights, thresholds, and agent prompts are proprietary and stay unpublished. What is not proprietary, and what most tools skip: every factor is scored against live, cited evidence you can open and check yourself. The verdict is auditable even though the recipe is not.
Common questions
You describe your idea in a paragraph. Ten AI agents query 50+ live data sources in parallel, each covering one domain (competitors, market sizing, demand signals, community sentiment, regulation). Findings are cross-validated across models; the result is a 0-100 score with a source URL behind every claim, plus risk flags and 2-3 suggested pivots.
A single 0-100 viability rating built from six factors: market size and growth, real demand signals, competitive density, moat durability, business model viability, and regulatory and execution risk. About 18.3% of ideas reach launch-ready (70+), so the number stays honest rather than flattering.
A direction, not a verdict. It usually means the market is crowded, the timing is off, the positioning is wrong, or the target is too broad. The report shows which factor is dragging the score down and suggests pivots that can lift it.
50+ live data sources across 10 categories: regulatory filings, hiring data, market research, funding databases, community signals, search demand, pricing pages, and more. Every claim links back to a source you can check.
No. A raw LLM rates an idea from memory and tends to agree with you. Preuve scores each factor against live, cited evidence and cross-checks the verdict across models until they converge. The exact weights are proprietary, but the evidence is open for you to verify.