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description=Vibe-research for vibe coders and solo founders. Verdikt generates cited digital reports with named risks and a Verdikt Score on startup ideas, before you spend weekends building.;

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Text of the page (random words):
verdikt validate your startup idea before you build skip to content beta solutions pricing blog contact sign in get a verdict solutions pricing blog contact get a verdict sign in not a gpt wrapper typically 40 cited sources vibe research before you vibe code pitch your idea in a sentence verdikt generates a digital research report with a verdikt score named risks and dozens of cited sources before you build get my verdict read a sample verdict live brief save exit brief ready review your brief 10 of 12 sections captured submit to run the verdict 01 founder solo founder 6 weeks in day job at a series a saas built mvp on lovable in 3 weekends 02 thesis indie hackers will pay 9 mo for streak accountability that lives next to their build log 03 problem builders drop habits at week 3 notion templates feel like homework streaks lives in ios 04 icp indie hackers shipping side projects ai builders launched in the last 90 days 05 solution one tap habit log that lives next to the build log no new app no new tab 06 value prop replace notion streak templates with a purpose built widget inside your existing workflow 07 market size 45m reachable pool of indie hackers and ai builders shipping on no code platforms 08 competition streaks habitify notion templates do nothing none are embedded in dev tools 09 business model 9 mo saas freemium with 7 day streak limit upgrade unlocks unlimited analytics 10 gtm launch on product hunt and indiehackers seed with 50 beta testers from twitter build in public 11 traction empty 12 risks empty your brief 10 of 12 sections understood foundation 3 3 founder solo 6 weeks in day job at series a saas built mvp in 3 weekends ships between day job hours thesis 9 mo streak accountability lives next to the build log indie hackers are the wedge problem habits drop at week 3 notion feels like homework market customer 5 5 icp indie hackers shipping side projects ai builders on lovable bolt solution one tap habit log value prop replace notion templates market size 45m reachable pool indie ai builders competition streaks habitify notion none embedded in dev tools execution 2 4 business model 9 mo freemium saas gtm product hunt indiehackers traction not captured yet risks not captured yet the output anatomy of a verdict a real memo fully marked up you ll know exactly what you get before you pay the lede 2 one sentence you can quote in twelve seconds no hedges named risk 4 the single fact that would reverse this verdict named upfront not buried confidence 6 calibrated on source quality and tier mix not vibes verdikt score 78 indie hackers will pay 9 mo for streak accountability that lives where they build not in another app problem indie hackers drop habits at week 3 notion templates feel like homework market 45m reachable pool indie ai builders wtp 9 mo named risk notion ships a native habit tracker template within 6 months 30 probability source 12 reddit r saas habit tracker pricing thread public vendor pricing pages reddit com r saas comments habit tracker wtp tier 1 source tiers t1 t2 t3 sample report typically 40 sources cited per report runs on openai s gpt 5 4 family anthropic for live web search 1 verdikt score a numerical verdikt score 0 to 100 decision grade never a maybe 3 four facts problem market moat risk each with a defensible number 5 sourced every claim footnoted to a tiered source click the number get the receipt verdikt score 78 indie hackers will pay 9 mo for streak accountability that lives where they build not in another app problem indie hackers drop habits at week 3 notion templates feel like homework market 45m reachable pool indie ai builders wtp 9 mo named risk notion ships a native habit tracker template within 6 months 30 probability source 12 reddit r saas habit tracker pricing thread public vendor pricing pages reddit com r saas comments habit tracker wtp tier 1 source tiers t1 t2 t3 1 verdikt score a numerical verdikt score 0 to 100 decision grade never a maybe 2 the lede one sentence you can quote in twelve seconds no hedges 3 four facts problem market moat risk each with a defensible number 4 named risk the single fact that would reverse this verdict named upfront not buried 5 sourced every claim footnoted to a tiered source click the number get the receipt 6 confidence calibrated on source quality and tier mix not vibes from idea to evidence how your verdict gets built three stages from your one sentence pitch to a memo you can defend in any room 01 brief 12 calibrated 02 research 42 per verdict 03 verdict one page memo 01 brief pin down the claim a loose pitch becomes testable assumptions buyer price wedge and the evidence that would change your mind start a brief brief pitch in testable assumptions out guided 12 questions buyer indie hackers shipping side projects wedge streak accountability for ai builders price 9 mo risk notion ships a native template in 6 months 02 research every source checked in the open sources are tiered checked and logged as the pipeline runs the reasoning trace is auditable not a black box see the methodology research tier graded source ingestion live 28 of 42 sources t1 primary filings 14 t2 analyst review 9 t3 operator signals 5 03 verdict a one page memo evidence ready one page the score four facts named risks and a footnote on every claim see a sample verdict verdikt score sourced one page cited 78 100 indie hackers will pay 9 mo for streak accountability that lives where they build market 45m reachable pool confidence high 14 t1 sources top risk 30 notion 6mo what you get what every report ships with every claim cited refund or re run if we fail to deliver a verdict guided brief guided questions targeted questions that shape the research voice deck or one sentence in v which buyer do you win in the next 90 days indie hackers shipping to their first launch v what band would they pay in today under 5 5 to 15 15 4 of 12 pitch any way you want voice on a walk a deck one sentence in a textbox voice note whatever you d say out loud deck or doc pdf upload one sentence we ask the rest a price signal not a guess triangulated from buyer language comparable pricing and substitute cost illustrative signal 7 to 12 mo confidence 4 of 5 comps 5 9 mo stack tools and a starter prompt when the score lands high you get a build outline not a pep talk stack lovable supabase tailwind checkout resend starter prompt paste in 1 2 3 build a lovable habit tracker for indie hackers one tap log public streak page checkout at 9 mo tools cursor lovable bolt claude code launch channel notes not a pep talk where early users already gather and which messages the report found indie hackers strong product hunt moderate build in public x strong three ideas in one side by side view out each verdict laid out side by side with score differences and evidence ai twitter scheduler for indie founders 72 mkt 7 8 bld low wtp strong highest score habit tracker for indie hackers 78 mkt 8 0 bld low wtp strong lovable build streak tracker 42 mkt 5 4 bld med wtp weak trust audit the verdikt on three concerns founders raise about tools like this here s what we say back not a wrapper just another gpt wrapper five research steps a real pipeline not one big prompt methodology no training on payloads what about my data we rely on our model vendors standard api terms accessed via the vercel ai gateway under which api payloads are not used to train their models provider clauses refund or re run what if it s wrong every verdict names the risks triggers and pivot signals that would change the call if we miss it refund or re run your choice accountability vs the alternatives a quick answer is not the same as cited evidence get a verdict approach buyer pain stated plainly traced sources numbers tied to named sources risks first surfaced before the call hardens what to test next pivot criteria and signals to watch output format verdikt buyer pain segment pain price named traced sources typically 40 tiered t1 to t3 risks first named risks stated up front what to test next pivot criteria named output format cited report segment pain price named typically 40 tiered t1 to t3 named risks stated up front pivot criteria named cited report generic chatbot buyer pain generic no segment traced sources no citations risks first reads like a disclaimer what to test next none proposed output format chat thread generic no segment no citations reads like a disclaimer none proposed chat thread diy research buyer pain founder knows them cold traced sources real links manually gathered risks first only if you keep the discipline what to test next buried under spreadsheet sprawl output format notes doc founder knows them cold real links manually gathered only if you keep the discipline buried under spreadsheet sprawl notes doc outside research buyer pain sharp distant from operators traced sources tier 1 well sourced risks first listed rarely weighted what to test next usually requires follow up output format deck slides sharp distant from operators tier 1 well sourced listed rarely weighted usually requires follow up deck slides verdikt is the only row that completes the contract cited decision file tiered sources t1 to t3 named pivot signals source library where the numbers come from primary filings and official statistics from sec edgar and fred operator signals public vendor pricing and live web and news retrieval the kind of cited primary source evidence base a researcher would assemble typically 40 sources cited per report every claim numbered every link live every source tier graded sec edgar fred st louis fed bls labor statistics bea bureau of economic analysis us census world bank eurostat usgs sec edgar fred st louis fed bls labor statistics bea bureau of economic analysis us census world bank eurostat usgs hacker news reddit r saas fda filings federal register vendor pricing pages product hunt web news exa tavily firecrawl wayback machine hacker news reddit r saas fda filings federal register vendor pricing pages product hunt web news exa tavily firecrawl wayback machine plus open web retrieval data fetched live at run time source library versioned manifesto pre launch dispatch filed may 2026 we kept seeing the same four needs in early founder research one clear research read numbered claims live links and the falsifier that would change the score so we built it tuaha jawaid and farzan ansari cofounders verdikt founder note pending named customer testimonials appear here only after customers approve them until then this stays a founder note featured on launched on tiny startups tinystartups com launched on tiny startups tinystartups com faq the questions every founder asks before paying us straight answers scope sources what we won t do q 1 how do i know what evidence supports my startup idea verdikt runs the structured research a founder would skip otherwise bottom up market sizing competitor mapping demand signals and a 10 claim test the output is a verdikt score 0 to 100 with the named risks that would change it if the evidence is strong you also get a build outline stack options and launch channel notes read the methodology q 2 should i validate before building on lovable bolt or v0 yes most ideas die because no one named the risks early enough to redesign around them every verdict returns a verdikt score 0 to 100 with the named risks and the evidence behind them see a sample verdict q 3 how is verdikt different from chatgpt or claude chatgpt and claude can give you opinions they cannot pull live competitive data run a structured 5 stage research pipeline or back every claim with a tier graded source verdikt does all three and ships a research report you can defend how sources are tier graded q 4 is this just a gpt wrapper no five step pipeline market sizing competitive map 10 claim test risk synthesis and score generation different model and guardrails per step the source pipeline and falsifier check are both visible in the report read the methodology q 5 where do your sources come from tier 1 sec edgar fred and public statistical registries bls census world bank tier 2 trade press and case studies tier 3 hacker news reddit and other public user conversations context never fact every citation is tier marked how sources are tier graded q 6 what if you get the verdict wrong every report names what would change the score if something is wrong on our end a broken citation a hallucinated number no source supports or a score that contradicts the evidence we ourselves surfaced refund or re run your choice email support tryverdikt app within fourteen days with what specifically went wrong we review each request on the evidence disagreement with a supported research read is not refundable how the falsifier loop works q 7 will you train on my idea no we do not train models on your briefs or reports we rely on our model vendors standard api terms accessed via the vercel ai gateway under which api payloads are not used to train their models we retain submitted briefs while your account is active and delete them on request privacy tryverdikt app security trust q 8 is this for ideas or for startups already running both the same pipeline runs either way you get a verdikt score 0 to 100 with named risks and the evidence behind them whether the idea is pre revenue or already running it is the same memo applied to defensibility and positioning see pricing q 9 who s behind verdikt verdikt is built by tuaha jawaid and farzan ansari every report is generated by the same pipeline they use on their own ideas with the same tier graded sources and the same falsifier loop questions go straight to the cofounders at hello tryverdikt app about the cofounders enough reading submit an idea get a verdict paid from 14 99 refund or re run if we fail to deliver a verdict get my verdict see a sample first beta research for founders and ai builders who want cited evidence before they build verdikt is a product of kastling verdikt is a self serve research product it is not investment financial career legal or business advice outcomes are not guaranteed and decisions made using a report are the reader s own see terms for full detail product pricing sample verdict methodology changelog compare vs validatorai vs ideaproof vs ideabrowser vs chatgpt all validators 2026 resources blog how to validate tam sam som company about security trust contact terms of service privacy policy verdikt newsletter stay in the loop occasional drops on what we re learning no daily blast email address subscribe by subscribing you agree to receive updates from verdikt see our privacy notice 2026 kastling made by tuaha and farzan