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$ whoami
Aneesh Venkatesha Rao — B.Tech @ NIT Warangal
$ focus --areas
- AI/ML product engineering
- Full-stack application architecture
- Distributed data + automation pipelines
- Human-in-the-loop developer tooling
$ currently
Building systems that turn ambitious ideas into reliable, user-ready products.I enjoy bridging research-minded experimentation with production-ready software.
My approach combines AI/ML capability, backend rigor, and clean frontend execution to ship products that are both technically strong and genuinely usable.
ContextCraft · AST-aware codebase search engine
- Built a hybrid search engine that parses codebases with tree-sitter — functions and classes as atomic chunks, never mid-function splits
- Implemented Reciprocal Rank Fusion merging pgvector cosine similarity + PostgreSQL BM25, with per-repo RRF normalization for multi-repo queries
- Added Cohere cross-encoder reranking (20 → 10 candidates) and 1-hop dependency graph expansion with cycle detection across file boundaries
- Enriched every chunk with git blame author metadata; benchmarked at 80% source hit rate at 3.88s P50 latency across 30 queries
- Published to PyPI (
pip install contextcraft-py); CI enforces mypy strict, ruff, and pytest before every merge - Tech: Python, FastAPI, PostgreSQL, pgvector, tree-sitter, Cohere, Next.js, Docker
🔗 Repository: github.com/AneeshVRao/ContextCraft
Dev-Saarathi · Voice-first AI coding assistant
- Built a voice-to-code pipeline in 11 Indian languages through transcription + intent detection
- Designed an AI orchestration flow (Intent Detection → Guardrails → Execution Router) for safe automation of code actions
- Implemented context-aware reasoning over 50+ files / 100k+ characters via RAG to reduce hallucinated outputs
- Added human approval controls while keeping 3–6s voice-to-response latency
- Tech: TypeScript, Python, AWS (Bedrock, Transcribe, S3), RAG
🔗 Repository: github.com/ashb155/dev-saarathi
ShabdSetu · AI-powered multilingual learning platform
- Built an end-to-end learning system for 10+ Indian languages using IndicTrans2 + Whisper
- Developed fuzzy pronunciation scoring for real-time speaking feedback
- Engineered layered caching (in-memory + Firestore) for sub-50ms response paths
- Added gamification with XP, streaks, and achievements synced across authenticated sessions
- Tech: Next.js, React, FastAPI, IndicTrans2, Whisper, Firestore
🔗 Repository: github.com/AneeshVRao/ShabdSetu
- Build for clarity, then optimize for scale
- Treat performance as a core product feature
- Keep architecture modular and maintainable
- Use AI where it delivers measurable utility
- Design developer experiences that reduce friction
- 🥇 Smart India Hackathon 2025 — National Finalist (Top 5 in problem statement, selected from 75,000+ submissions)
- 📜 13 professional certifications across cloud, software engineering, and data science (Google, Meta, IBM)
- 🏅 65+ Olympiad medals in national-level Mathematics and Science competitions
- Building AI-assisted developer tools with strong guardrails
- Optimizing backend systems for latency and throughput
- Applying systems thinking to end-to-end product design
- Shipping practical AI integrations that solve real user problems
- Backend / Full-Stack internships
- AI product engineering roles
- Summer 2026 opportunities
- Open-source collaborations in AI tooling and productivity systems
If you're building something meaningful in AI, full-stack systems, or developer tooling, I'd love to connect.