2026-05-12 · DATA ROOM
Venture Lens Api
Ship Spring Boot APIs at the speed of thought
ELEVATOR PITCH
AI-powered code generation platform that transforms natural language into production-ready Spring Boot microservices in seconds.
VALUE PROPOSITION
10x faster backend development by eliminating boilerplate and automating architecture decisions.
EXPLAINER.md
VentureLens AI — Explainer
Concept
AI-powered business validation platform for Fintech/Edtech founders. Submit an idea → get a structured feasibility report in minutes, not weeks. Replaces expensive manual market research with an automated LLM + web-search pipeline.
Target users: early-stage entrepreneurs, incubators, angel investors. Monetization: freemium SaaS — 1 free report, then Founder ($29/mo · 5 reports) or Investor ($99/mo · unlimited + collaboration).
Architecture
┌──────────────┐ JWT ┌────────────────────────────────────────────┐
│ Frontend │────────▶│ Spring Boot 4.0.4 / Java 25 │
│ (any SPA) │ │ │
└──────────────┘ │ AuthController ──▶ AuthService │
│ ValidationController ▶ ValidationService │
│ DashboardController ▶ ValidationService │
│ │
│ @Async (virtual threads) │
│ AnalysisService │
│ ├── SearchClient (SerpApi / Feign) │
│ └── LlmClient (OpenAI / Feign) │
│ │
│ JPA / Hibernate 7 │
│ ├── User │
│ ├── BusinessIdea │
│ └── ValidationReport │
└───────────────┬────────────────────────────┘
│
┌──────────▼──────────┐
│ H2 (dev) │
│ PostgreSQL (prod) │
└─────────────────────┘
Key design decisions:
| Concern | Decision |
|---|---|
| Auth | Stateless JWT via jjwt 0.12.6 |
| Async AI pipeline | %%INLINE0%% + %%INLINE1%% |
| External APIs | Spring Cloud OpenFeign 4.2.1 declarative clients |
| Serialisation | Jackson 3 (%%INLINE2%%), pre-configured %%INLINE3%% |
| Validation | Jakarta Validation (jakarta.validation.*) |
| Persistence | Spring Data JPA + H2 (dev) / PostgreSQL (prod) |
Endpoints
Auth (public)
| Method | Path | Body | Response |
|---|---|---|---|
| %%INLINE5%% | %%INLINE6%% | %%INLINE7%% | %%INLINE8%% (JWT) |
| %%INLINE9%% | %%INLINE10%% | %%INLINE11%% | %%INLINE12%% (JWT) |
Validation (Bearer token required)
| Method | Path | Body | Response |
|---|---|---|---|
| %%INLINE13%% | %%INLINE14%% | %%INLINE15%% | %%INLINE16%% |
| %%INLINE17%% | %%INLINE18%% | — | %%INLINE19%% or %%INLINE20%% |
Dashboard (Bearer token required)
| Method | Path | Query | Response |
|---|---|---|---|
| %%INLINE21%% | %%INLINE22%% | — | List<DashboardSummary> |
| %%INLINE24%% | %%INLINE25%% | %%INLINE26%% | %%INLINE27%% |
Example ValidationReportResponse
{
"reportId": "...",
"ideaId": "...",
"ideaTitle": "AI Invoice Automation for SMEs",
"feasibilityScore": 78,
"executiveSummary": "Strong market pull in the Fintech SME segment...",
"competitorAnalysis": "[\"Stripe: broad payments platform\",\"Xero: accounting-first approach\"]",
"marketSizeAnalysis": "{\"tam\":\"$14B\",\"sam\":\"$2.1B\",\"som\":\"$85M\"}",
"strengths": "Clear ROI, low switching cost, recurring revenue model",
"weaknesses": "Crowded market, integration complexity",
"opportunities": "Open Banking mandates, AI-native incumbents absent",
"recommendations": "1. Conduct 20 customer interviews. 2. Build no-code MVP...",
"generatedAt": "2026-05-12T14:32:00"
}
Analysis Pipeline
POST /api/v1/validate
└─▶ ValidationService.submit()
├── Persist BusinessIdea (status=PENDING)
└── AnalysisService.analyzeAsync() ─── virtual thread
├── status → PROCESSING
├── SearchClient.search() ← SerpApi (competitor signals)
├── LlmClient.complete() ← OpenAI (structured JSON report)
├── Parse + persist ValidationReport
└── status → COMPLETED
Client polls GET /api/v1/reports/{ideaId}:
204 No Content→ still processing200 OK→ report ready
Business Analysis
Problem
- Early-stage founders spend 40-80 hours on market research before validating an idea.
- Angel investors review 100s of pitches with inconsistent diligence frameworks.
- No affordable, automated tool exists for Fintech/Edtech vertical intelligence.
Solution
Automated feasibility report in < 2 minutes, combining:- Web intelligence — real-time competitor discovery via SerpApi.
- LLM reasoning — GPT-4o / Claude structured analysis (TAM/SAM/SOM, SWOT-style).
- Persistent dashboard — manage and compare ideas over time.
Unit Economics (projections)
| Tier | Price | Reports/mo | LLM cost/report | Gross margin |
|---|---|---|---|---|
| Free | $0 | 1 | ~$0.08 | — |
| Founder | $29 | 5 | ~$0.08 | ~86% |
| Investor | $99 | Unlimited | ~$0.08 | Scales with usage |
Competitive Moat
- Vertical knowledge: prompt templates tuned for Fintech/Edtech.
- Report history: switching cost grows with user's idea portfolio.
- Network effects: aggregate anonymised data → proprietary benchmark scores.
How to Run
Prerequisites
- Java 25
- Maven 3.9+
Dev mode (H2 in-memory database)
cd solutions/2026-05-12-venture-lens-api
# Run with dev profile (H2, no external APIs required)
SPRING_PROFILES_ACTIVE=dev mvn spring-boot:run
With real AI (optional)
SPRING_PROFILES_ACTIVE=dev \
OPENAI_API_KEY=sk-... \
SERPAPI_KEY=... \
mvn spring-boot:run
Compile check
mvn clean compile
Quick API smoke test
# 1. Register
curl -s -X POST http://localhost:8080/api/v1/auth/register \
-H 'Content-Type: application/json' \
-d '{"name":"Alice","email":"alice@example.com","password":"secret123"}' | jq .
# 2. Submit idea (use token from step 1)
TOKEN="<token>"
curl -s -X POST http://localhost:8080/api/v1/validate \
-H "Authorization: Bearer $TOKEN" \
-H 'Content-Type: application/json' \
-d '{
"title": "AI Invoice Automation for SMEs",
"description": "A SaaS tool that uses AI to automatically extract, categorise and reconcile invoice data for small businesses, reducing manual bookkeeping by 80%.",
"problemStatement": "SMEs waste 5-10 hours per week on manual invoice processing.",
"targetAudience": "Small business owners and their accountants",
"industry": "Fintech"
}' | jq .
# 3. Poll for report
IDEA_ID="<ideaId from above>"
curl -s http://localhost:8080/api/v1/reports/$IDEA_ID \
-H "Authorization: Bearer $TOKEN" | jq .
# 4. Dashboard
curl -s http://localhost:8080/api/v1/dashboard \
-H "Authorization: Bearer $TOKEN" | jq .
H2 Console (dev only)
Open: http://localhost:8080/h2-console JDBC URL: %%INLINE32%% Username: %%INLINE33%% Password: (empty)Production (PostgreSQL)
# application-prod.yml
spring:
datasource:
url: jdbc:postgresql://localhost:5432/venturelens
username: ${DB_USER}
password: ${DB_PASS}
jpa:
hibernate:
ddl-auto: validate
database-platform: org.hibernate.dialect.PostgreSQLDialect
References
MVP FEATURES
- 01Natural language to REST endpoint generator
- 02JPA entity scaffolding
- 03OpenAPI spec auto-generation
- 04Docker Compose export
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