Skip to content
View vikrantd's full-sized avatar

Block or report vikrantd

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
vikrantd/README.md

Hi, I'm Vikrant Dubey 👋

Software Engineer building high-quality AI applications, agentic systems, and AI memory & context infrastructure.

I've spent 10+ years taking products from idea to production across AI, fintech, and data platforms — currently building generative voice infrastructure at Resemble AI, where I own model serving and training pipelines for production TTS. Along the way I've shipped full products end to end (frontend, backend, DevOps), led teams, and open-sourced tools used by thousands of developers.

These days my focus is making AI systems that are reliable, fast, and cost-efficient — agentic workflows that actually ship, and memory/context layers that let agents reason over large codebases and data without drowning in tokens.


🧠 What I'm building

🔓 TLDRGraph — AI memory & context reduction (open source · MIT)

See the flow of your spaghetti code.

An AST-based knowledge graph that gives coding agents architectural memory of a repository — tracing semantic call paths across microservices and abstraction layers so an agent can localize a feature or bug without reading the whole codebase.

  • Zero-token extraction — architecture is mapped from the AST, not the LLM
  • 🎯 62.5% Recall@1 on SWE-bench Lite issue localization
  • 💸 ~2,400–3,200 tokens to answer, vs. 8,200–28,500 for comparable approaches
  • 🤝 Agent-agnostic — works with Claude, Cursor, Gemini, and others
  • 🔁 SHA-256 incremental updates + a shared, version-controlled architecture map

🎯 SkillMoksha — AI hiring platform

End-to-end AI-led screening, interviews, and evaluation that cuts hiring cycles from weeks to days. Automated resume screening, AI-conducted interviews, coding assessments, and adaptive AI-fraud/proctoring detection with full audit trails.

🛠️ Krut AI — Agentic app builder

Turns natural-language ideas into working, deployed software. Autonomously generates the UI, builds Docker images, provisions Postgres, and wires in AI capabilities (OCR, speech-to-text/TTS, real-time voice, LLM business logic) — with a human-in-the-loop engineering safety net for production reliability.


🧰 Tech I work with

AI / LLM  Agentic systems · AI memory & context engineering · PyTorch · Model serving (TTS / Generative) · Latency optimization · Model routing

Backend  Python · Node · Django · GraphQL

Frontend  React · Angular · TypeScript

Data  Spark · Elasticsearch · Redis · Druid · Celery

Cloud & DevOps  Docker · Kubernetes · Helm · AWS · GCP · Azure · Jenkins · CI/CD


🤝 Connect

LinkedIn Email  📍 Bangalore, India


⭐ If you're building agents that need memory, check out TLDRGraph — feedback and stars welcome.

Pinned Loading

  1. cuelake cuelake Public

    Forked from cuebook/cuelake

    Use SQL to build ELT pipelines on a data lakehouse.

    JavaScript

  2. TLDRGraph TLDRGraph Public

    Dynamic Multi-Layer Code Flow, Instant Semantic Call Tracing, and Interactive Architectural Navigation.

    Python 4 1