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axiomaticVezper/README.md

Sahil Singh - Generative AI Engineer

LinkedIn    Instagram    Email

"Quantum ideas. Neural intelligence. Real-world impact."


⚡ telemetry // live_metrics

GitHub Streak

GitHub Stats Top Languages

Snake eating my contributions

🛰️ system.whoami

identity:
  name: Sahil Singh
  role: Generative AI Engineer
  base: Chennai, Tamil Nadu, India
  academia:
    - degree: B.Tech Computer Science & Engineering
      institution: Vellore Institute of Technology (VIT Chennai)
      cohort: 2024–2028
      standing: CGPA 8.76
    - degree: B.S. Data Science & Applications
      institution: Indian Institute of Technology Madras (IIT Madras)
      cohort: 2025–2028
mission: Engineering reliable cognitive architectures, agentic pipelines, and quantum-neural hybrids.

🔬 active_research // core_focus

  • Generative AI & Agentic Workflows: Autonomous agents, schema-guided function calling, LangGraph state machine orchestrations, and deterministic guardrails.
  • Advanced Retrieval Architectures (RAG): Hybrid sparse-dense vector retrieval (BM25 + Qdrant), cross-encoder semantic reranking, context compression, and RBAC chunk partitioning.
  • Deep Learning & Representations: Transformer fine-tuning, domain adaptation, embedding geometry, quantization, and systematic evaluation metrics.
  • Quantum Machine Learning: Exploring variational quantum algorithms, parameterized circuits, and quantum-neural fusion layers.

🛠️ technical_matrix

Languages
AI / ML Core
Vector & DB
Backend & Web
Cloud & DevOps

📦 featured_deployments

├── [01] PRODUCTION-GRADE RAG SYSTEM
│    ├── Stack: FastAPI · Qdrant · Ollama · Python · Docker
│    ├── Features: Semantic document ingestion, hybrid Dense + BM25 retrieval,
│    │             cross-encoder reranking, RBAC filtering, citation attribution
│    └── Reliability: Production CI/CD, evaluation benchmarks, structured telemetry
│
├── [02] NATURAL LANGUAGE → API ASSISTANT
│    ├── Stack: LangChain · LangGraph · Tool Calling · OpenAPI
│    ├── Features: Schema-aware cognitive agent, dynamic intent parsing, strict parameter
│    │             validation, dry-run simulation engine, execution confirmation gating
│    └── Safety: Deterministic error recovery and runtime guardrails
│
└── [03] SAFEROUTE ESCROW
     ├── Stack: React · Node.js · Neon PostgreSQL · Ethereum · Hardhat · Stripe
     ├── Features: Blockchain-backed delivery verification, smart contract state machine,
     │             tamper-evident audit logs, conditional escrow release
     └── Security: Webhook signing, multi-party verification, encrypted ledger events

Engineered by Sahil Singh (@axiomaticVezper) · Monitored via GitHub Actions

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  1. rag-system rag-system Public

    In this project production‑grade RAG system is implemented with semantic chunking, RBAC metadata, hybrid retrieval, structured outputs, streaming, CI/CD evaluation, and observability.

    Python

  2. NL-to-api-assistant NL-to-api-assistant Public

    Python