Data source
LiveReal-time pulls from Crunchbase, Reddit, PH, G2, Trends + 45 more
→ A signal that does not depend on how confidently you typed.
Self-reported answers + curated case database
Stress-testing your thinking vs checking the market
ReadySetLaunch surfaces gaps in how you articulate the idea through 7 structured pillars. Preuve AI checks whether the market agrees - 50+ live sources, clickable links. The two tools answer different questions, so using both is worth the 30 minutes.
Head to head
Verdict
Preuve AI wins 9 of 10 validation steps.
ReadySetLaunch scores what you typed. Preuve scores what the market is doing.
Live data vs trained data, the upstream problem.
Data source
LiveReal-time pulls from Crunchbase, Reddit, PH, G2, Trends + 45 more
→ A signal that does not depend on how confidently you typed.
Self-reported answers + curated case database
Source links
VerifiableEvery claim links to its origin
→ Every number is a clickable URL you can verify yourself.
No links, signals are scored from your text
Competitor data
Real-timeLive data with funding, traffic, reviews, and links
→ Real competitors with real rounds, not your best guesses.
Not a feature, you describe competitors yourself
Sourced numbers, repeatable verdict, structured report.
Market sizing
SourcedBottom-up TAM/SAM/SOM with sources
→ A TAM you can defend, because every input has a link behind it.
Not provided
Scoring
Scored0 to 100 viability score across 6 frameworks
→ A median of 55, pass rate 18.3%. The score has to mean something.
Per-pillar signal strength, no numeric score
Demand signals
ExternalPulled live from Reddit, Product Hunt, G2, Google Trends
→ Demand observed in public, not asserted by the founder.
Self-reported "behavioural evidence"
Pivot recommendations
Actionable3 pivots based on competitive gaps + market signals
→ When the verdict is "no," you still walk away with directions worth testing.
Not a feature
Report format
Structured13-section interactive dashboard + PDF export
→ Share a dashboard or a PDF. Not a one-off in-app screen.
Browser-only launch readiness report
One-time pay vs subscription, and who it is for.
Cost
One-time$29 one-time per report (free scan first)
→ See the output before you pay. No credit math.
Credit packs from £14.99 (30 credits per pack)
Best for
Founders who need defensible market evidence
Founders who want to slow down and challenge their own pitch
Live data vs trained data, the upstream problem.
Data source
Real-time pulls from Crunchbase, Reddit, PH, G2, Trends + 45 more
→ A signal that does not depend on how confidently you typed.
Self-reported answers + curated case database
Source links
Every claim links to its origin
→ Every number is a clickable URL you can verify yourself.
No links, signals are scored from your text
Competitor data
Live data with funding, traffic, reviews, and links
→ Real competitors with real rounds, not your best guesses.
Not a feature, you describe competitors yourself
Sourced numbers, repeatable verdict, structured report.
Market sizing
Bottom-up TAM/SAM/SOM with sources
→ A TAM you can defend, because every input has a link behind it.
Not provided
Scoring
0 to 100 viability score across 6 frameworks
→ A median of 55, pass rate 18.3%. The score has to mean something.
Per-pillar signal strength, no numeric score
Demand signals
Pulled live from Reddit, Product Hunt, G2, Google Trends
→ Demand observed in public, not asserted by the founder.
Self-reported "behavioural evidence"
Pivot recommendations
3 pivots based on competitive gaps + market signals
→ When the verdict is "no," you still walk away with directions worth testing.
Not a feature
Report format
13-section interactive dashboard + PDF export
→ Share a dashboard or a PDF. Not a one-off in-app screen.
Browser-only launch readiness report
One-time pay vs subscription, and who it is for.
Cost
$29 one-time per report (free scan first)
→ See the output before you pay. No credit math.
Credit packs from £14.99 (30 credits per pack)
Best for
Founders who need defensible market evidence
Founders who want to slow down and challenge their own pitch
The gap
You score what you write. A confident founder writes confident answers - the signal reflects your conviction more than the market's reality.
The case database is historical. It will not surface the competitor that raised $10M last week or launched on Product Hunt yesterday.
Per-pillar signals are derived from your text, so there is no Reddit thread, Crunchbase entry, or G2 review you can click when someone asks you to back a claim up.
That designed friction is useful when you are fully committed to one direction, but it adds up fast when you are still weighing three or four options at once.
The difference
On every run, AI agents search Crunchbase, Google Trends, Reddit, Product Hunt, G2, and 35+ other sources in real time - so the competitor that raised last week actually shows up.
Every competitor entry, market estimate, and demand signal links back to its source, so you can click through and verify the claim before you cite it anywhere.
Median across 4,000+ ideas is around 55. Only 18.3% earn a go verdict. If your idea scores well against real data, it earned it.
Covers competitors, TAM/SAM/SOM, demand signals, risk flags, pivot options, and action plans. The output is structured enough to walk a co-founder or investor through without needing to narrate every number.
Workflow
Use the 7-pillar questionnaire to write down what you actually believe about the problem, customer, and demand. The slowness forces specificity you can later check against real data.
Take those answers to live evidence. Pull competitor maps and demand signals from 50+ real-time sources, and get a viability score with the receipts. Every claim links back to its origin.
You wrote down what you believe, then checked it against what the market actually shows. Now decide whether to build, pivot, or stop - with evidence behind each part of your pitch rather than just a gut feeling.
Challenge
Pressure-test your idea with ReadySetLaunch, then run the same idea through Preuve AI and compare the source links.
Test your idea free→Join 100+ entrepreneurs who upgraded
FAQ
ReadySetLaunch (RSL) is a structured startup idea validator that walks founders through 13 questions across 7 launch-readiness pillars: Problem Intensity & Clarity, Target Customer Specificity, Demand & Behavioural Signals, Differentiation, Execution Feasibility, Distribution Readiness, and Monetisation Viability. Each answer is scored against a curated database of historical startup outcomes and returned as per-pillar signal strength rather than a numeric score. Pricing is pay-once credit packs from £14.99 with no subscription.
ReadySetLaunch is good at what it claims: a structured self-interrogation across 7 pillars. The questionnaire forces founders to write out what they believe about the problem, customer, and distribution plan in plain English, which does surface gaps in weak answers. That is real value. Where it falls short is evidence: no live competitor pull, no Reddit or Product Hunt scan, no source links. RSL tests your answers about the idea. It does not test whether the market actually wants the idea.
Preuve AI is the best ReadySetLaunch alternative when you want source-linked market evidence on top of self-reflection. ReadySetLaunch scores your own thinking against a historical case database, while Preuve AI pulls live competitor, demand, pricing, and risk evidence from 50+ sources and links every claim back to its origin. Use RSL to find gaps in your own answers, then Preuve to find out whether the market agrees.
No. ReadySetLaunch scores answers against a curated database of historical startup outcomes - failures, unicorn breakdowns, and acquisitions, mapped to the 7 pillars. The dataset grows through an ingestion pipeline but it is historical case analysis, not real-time market data. A competitor that launched last week will not appear. A funding round closed yesterday will not appear. For live market data you need a tool that scans the web on every run.
They answer different questions. ReadySetLaunch surfaces gaps in how you articulate the idea. Preuve AI surfaces gaps in the market itself, through 50+ live source scans with a clickable link behind every claim. RSL outputs per-pillar signal strength scored from your text. Preuve outputs a 0-100 viability score plus a 13-section dashboard with competitor maps and demand signals. Most founders who use both run RSL first to sharpen their thinking, then Preuve to check whether the market agrees.
Use ReadySetLaunch if you want to slow down and challenge your own assumptions before talking to anyone. Use Preuve AI if you need clickable market evidence to take into a co-founder conversation, an investor meeting, or a build/kill decision. RSL and Preuve are complementary, not competing - one exposes gaps in how you articulate the idea, the other exposes gaps in the market. If you can only pick one, pick the one that solves the bigger problem you are dealing with right now.
No. Preuve AI sends search agents to 50+ live sources in parallel, filters and verifies what they bring back, then writes a 13-section report with a clickable link behind every claim. There is no chat. No opinions pulled from training data. No "great idea, here is your 90/100." The median score is around 55 across 4,000+ ideas, and only 18.3% earn a go verdict. Preuve AI scores against external evidence; ReadySetLaunch scores against your own answers. Both will push back, just on different things.
Yes. Run RSL first to interrogate your own answers across the 7 pillars, then take those answers to Preuve AI to check them against live market data. RSL costs around £14.99 for one full validation. Preuve AI is free for the initial scan and $29 for the full source-linked report. Under $50 total, and you come out the other end with both a clearer pitch and the evidence to back it up.
ReadySetLaunch features and pricing reviewed against the public homepage and pricing page as of May 2026. Preuve AI features current as of May 2026. ReadySetLaunch credit packs run from £14.99 to £99.99 with no subscription. All trademarks belong to their respective owners.