Lean Premise

Many startups fail because they build something nobody wants.
Not because they lack talent. Not because they run out of money first.
But because they skipped market validation.

I've been building (still iterating) Lean Premise to fix this — an AI-powered platform that scans thousands of signals daily across Reddit, Twitter, Hacker News, Product Hunt, and more, then distills them into validated market opportunities with competition density scores, geopolitical risk, demographic fit, and financial projections.

Instead of spending weeks doing manual research, founders get actionable intelligence in minutes:
→ Real whitespace opportunities mapped to specific markets (EU, LatAm, DACH, MENA, and more)
→ Competitor landscape analysis per niche
→ Momentum scoring — is this trend rising or dying?
→ Search intent data to validate demand before you write a line of code

All across 6 languages and 13 regional markets — because the best opportunities are often where English-first tools don't look.

Example:
AI Code Review Agents

Keywords showing rising pull: “AI pull request review”, “automatic code review agent”, “GitHub AI reviewer”.

Who this is for (the real audience):
- CTOs / VPs Eng chasing faster shipping without regressions
- Platform / DevEx leads fighting tooling noise + adoption
- AppSec / Staff engineers stuck in late-stage review bottlenecks
- Teams with 10–300 engineers and constant PR throughput

The pain it solves:
- PRs waiting 24–72h, inconsistent review standards, noisy bots, and security catching issues too late.

The wedge (why this isn’t “just another code review bot”):
An agent that goes end-to-end:
- understands repo context (ADRs, conventions, architecture)
- enforces policy-as-code (deterministic pass/fail)
- proposes commits/patches (not just comments)
- produces measurable ROI: cycle-time + defect + change-failure metrics

This is the kind of output my upcoming SaaS/webapp will generate:
- ranked opportunities + buyer personas + differentiation angles you can actually build on.

If you want early access to the tool (and the next batch of opportunities), join the waitlist → https://leanpremise.com/?ref=indiehackers

And yes — 30% of net profits go toward building a dog rescue sanctuary from scratch. Because why not build a business that does something good too.

#StartupValidation #Entrepreneurship #MarketResearch #AI #Founders #LeanPremise

A lot of founders (me included) have built “cool” things that nobody needed. The fix isn’t more hustle—it’s a better validation loop.

Here’s a workflow I use to go from “maybe” → “evidence”.

1) Where good ideas actually come from

Look for:

• Workarounds (manual processes, spreadsheets, duct-tape automations)

• Non-consumption (people avoid solutions because they’re too heavy/expensive/complex)

• High-friction moments (pain spikes in a specific context)

Christensen’s JTBD research suggests workarounds and non-consumption are especially fertile—people are already signaling dissatisfaction.  

2) Frame the problem as a “job”

I like this template:

When [situation], I want to [progress], so I can [outcome].

This keeps you honest about the who and when, not just the feature list.  

3) Do customer conversations the right way

Avoid: “Would you use/pay for this?”

Use “Mom Test” style questions:

• Ask about the last time it happened

• Ask what they tried already

• Ask what it cost them (time/money/reputation/stress)

The goal is truth, not encouragement.  

4) Validate with behavior (cheap experiments)

Pick one:

• Fake Door / Smoke Test: landing page or in-product CTA → measure clicks/signups (do it ethically + transparently).  

• Pretotyping: “fake it before you make it” to test demand/usage without building the full product.

• Design Sprint-style prototype + user tests: compress learning into days. 

This is basically the Lean Startup idea: maximize validated learning and avoid wasted build cycles.

5) A lightweight PMF check (once you have users)

Ask: “How would you feel if you could no longer use this?”

If 40%+ answer “Very disappointed”, it’s a strong sign you’re on the right track.  

Question for IH:

What’s the best validation experiment you’ve run (or wish you ran earlier)?

The Idea:

Building Lean Premise - AI-powered startup validation platform.

• AI-native (live, not static database)

• Multi-language (6 languages)

• Mission-driven: 30% of net profits → dog rescue sanctuary

The Problem:

90% of startups fail. 42% because of "no market need."

Founders waste months validating bad ideas. I wasted months on 3 failed ideas in 2024 and 2025.

Current solutions:

- Big Ideas DB: static, manual curation, English only

- Manual research: Weeks of work, incomplete, gut-feeling based

- AI tools: Generic, no validation, no geopolitical context

The Solution:

AI that finds 100+ validated market opportunities daily.

What users get:

- Real market gaps (from Reddit, Twitter, forums, reviews, etc.)

- Market sizing with real data

- Competition analysis (who's building this, who's not)

- Geopolitical risk scoring (regulations, political stability, market readiness)

- Regional breakdowns (Spain vs LATAM, US vs UK, etc.)

- Investment requirements

- Recommended approach

Example opportunity:

SME Carbon Accounting Dashboard (Spain/EU)

Problem: EU mandates carbon reporting by 2027

Gap: 23,847 Spanish SMEs need this, no affordable tools exist

Market: €380M (EU-wide) Competition: Low (only enterprise players at €5k+/year)

Geopolitical Risk: Low (EU driving demand)

Investment: ~€35k Recommended: Start Spain → expand Italy/France

Not random ideas. Validated opportunities with actionable intelligence.

The Mission (Why This Matters): 30% of net profits → building a dog rescue sanctuary from scratch. From €0 to operational refuge in 18 months.

The Plan:

• Phase 1 (Months 1-12): Save €60k for land + infrastructure

• Phase 2 (Months 12-18): Build the refuge

• Phase 3 (Month 18+): First dog enters

• 100% Transparent: - Live financial dashboard - Every receipt public - Monthly progress videos

• Why dogs? I'm a founder. I know rejection. I know what needing a second chance feels like. Every abandoned dog deserves one too.

Meanwhile: 20% of the 30% goes to immediate impact - sterilizations, emergency vet bills, food donations. All receipts public.

Current Status

Product:

✅ Backend AI agents testing

⏳ Frontend development (Qwik fullstack, 4-6 weeks)

⏳ Beta launch (6-8 weeks)

Traction: - Waitlist launched: Today

Current signups: 0 (just starting!)

Early bird: 50% off first 3 months

Tech Stack:

• Frontend:

  • Qwik (fullstack) in CloudFlare Pages

  • Backend: Python (agents) - Rust (batch processing)

  • DB: PostgreSQL + pgvector

  • AI: Multi-model approach