A functional RAG prototype that analyzes Peruvian regulations to accelerate project viability and mitigate risk. Built for Indra/Minsait.
(No installation required. Deployed on Streamlit Community Cloud.)
(Repository includes instructions for local execution if desired.)
| Metric | Traditional Process | IndraLex (Estimated) | Potential Impact |
|---|---|---|---|
| Analysis Time | 6-8 hours* | <1 minute | ~480x faster |
| Cost per Analysis | $150-200* | $0.02-0.05 | Significant reduction |
| Coverage | Variable | 5 core regulations | Standardized |
*Based on typical legal review cycles in enterprise projects
IndraLex is a functional prototype that demonstrates how RAG (Retrieval-Augmented Generation) can accelerate regulatory compliance analysis for technology projects in Peru. Built specifically for Indra's context.
- Processes 5 key Peruvian regulations: Ley 29733 (Data Protection), DL 1412 (Digital Government), SBS Circulars, and more
- Identifies specific articles relevant to your project description
- Maps regulatory entities (SEGDI, SBS, RENIEC) and their requirements
- Generates actionable compliance roadmaps in seconds
PDF Laws → PyPDFLoader → Text Splitter → OpenAI Embeddings → FAISS Vector Store → GPT-4o-mini → Compliance Report
- Framework: LangChain 0.3.27 (same architecture as Indra's enterprise RAG chatbots)
- LLM: GPT-4o-mini (easily upgradeable to GPT-4o)
- Vector DB: FAISS 1.12.0 with intelligent caching
- Frontend: Streamlit 1.48.1 for rapid prototyping
- Performance: <3 seconds with cache, processes 260+ legal chunks
Input: "Mobile banking platform with biometric authentication and real-time transactions"
Output: Specific SBS circular articles, LPDP requirements, technical controls needed
Input: "Interoperability platform for state entities processing citizen data"
Output: DL 1412 compliance points, SEGDI standards, integration requirements
Input: "Electronic DNI validation system with biometric verification"
Output: Law 27269 requirements, certificate specifications, RENIEC standards
- Python 3.9+
- OpenAI API Key
- Clone the repository
git clone https://github.com/ncarrerakevin/IndraLex.git
cd IndraLex- Install dependencies
pip install -r requirements.txt- Configure environment
echo "OPENAI_API_KEY=your_api_key_here" > .env- Add legal documents
mkdir legislacion
# Add Peruvian law PDFs to this folder- Run the application
streamlit run app.py| Regulation | Coverage | Relevant For |
|---|---|---|
| Ley 29733 | Personal Data Protection | All sectors |
| DL 1412 | Digital Government | Public sector |
| Circular SBS G-140 | Cybersecurity | Banking |
| Ley 30096 | Computer Crimes | All sectors |
| Ley 27269 | Digital Signatures | e-Government |
This MVP is designed to evolve within Indra's ecosystem:
| Phase | Architecture | Value for Indra |
|---|---|---|
| MVP (Current) | Streamlit + Local FAISS | High-impact demo, concept validation |
| Pilot | FastAPI + Azure Functions | Internal API for project teams |
| Production | Docker + Azure Kubernetes | Enterprise-scale solution |
- Immediate value: Can be used tomorrow for real client proposals
- Scalable architecture: Same RAG pattern used in production systems
- Peru-specific: Not a generic tool, but tailored for local regulations
- Integration-ready: Can connect with existing Indra platforms
- Chunk Strategy: 1500 chars optimized for legal articles
- Retrieval: 8 most relevant chunks per query
- Caching: MD5 hash validation for document changes
- Model Config: Temperature 0.2 for consistent outputs
- Dependencies: LangChain 0.3.27, OpenAI 1.99.9, FAISS 1.12.0
- Expand coverage: Add more regulations (OSIPTEL, SUNAT, etc.)
- Enhance accuracy: Fine-tune prompts for specific sectors
- API development: RESTful interface for system integration
- Metrics tracking: Implement usage analytics and accuracy monitoring
Kevin Navarro C.
- 🎓 PUCP - Computer Science (9th semester)
- 💼 LinkedIn: Kevin Antonio Navarro
- 📧 Email: navarro.kevin@pucp.edu.pe
- 🏆 Recent: MediTrace/VeriMed LATAM (blockchain), AI corruption detection (hackathon winner)
MIT License - Open for enhancement and integration
Developed as a proactive demonstration of the initiative, technical skills, and business-oriented mindset I would bring to the AI R&D team at Indra.