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arulnidhii/README.md

Hi, I'm Arul Nidhii 👋

Building the memory layer for AI agents

👨‍💻 About Me

I'm the creator of Aegis Memory — an open-source memory infrastructure for multi-agent AI systems.
AI agents forget everything between sessions. I'm fixing that.

As the founder of Quantify Labs Ltd. (UK), I work at the intersection of AI infrastructure, developer tools, and multi-agent systems.

MSc in Big Data Analytics · 10+ years in data engineering & BI · Azure & Databricks certified

🧠 Aegis Memory

Persistent memory for multi-agent systems — because agents that forget can't improve.

GitHub · Docs · Website

  • Persistent memory that survives restarts and sessions
  • Semantic search with PostgreSQL + pgvector (30–80ms at scale)
  • Scoped access — private, shared, or global memories across agents
  • ACE patterns — agents that learn from mistakes and self-improve
  • Framework integrations — CrewAI, LangChain, LangGraph
pip install aegis-memory

✍️ Writing & Content

I write about AI agent memory, multi-agent coordination, and building in public.

  • Blog — Tutorials on CrewAI + LangGraph memory, ACE patterns, and more
  • DEV.to — Cross-posted guides and comparisons
  • LinkedIn — Weekly posts on agent memory and AI infrastructure

🎓 Certifications

  • Microsoft Certified: Azure Data Engineer Associate
  • Databricks Generative AI & Data Engineering
  • Oracle Cloud Data Management
  • DBT Fundamentals

🌐 Other Projects

⚡ Fun Facts

  • 🎵 Music + long walks = my brainstorming combo
  • 🧠 Currently exploring generative agent research (Stanford Smallville and beyond)

📫 Connect

Pinned Loading

  1. Data-Engineering-with-Databricks Data-Engineering-with-Databricks Public

    Transform data Spark, Manage Data with Delta Lake, Build Data Pipelines with Delta Live Tables, Manage Data Access with Unity Catalog.

    Python

  2. Controllable-RAG-Agent Controllable-RAG-Agent Public

    Forked from NirDiamant/Controllable-RAG-Agent

    This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.

    Jupyter Notebook

  3. dbt-coverage dbt-coverage Public

    Forked from slidoapp/dbt-coverage

    One-stop-shop for docs and test coverage of dbt projects.

    Python

  4. RAG_Hack RAG_Hack Public

    Forked from microsoft/RAG_Hack

  5. RAG_Techniques RAG_Techniques Public

    Forked from NirDiamant/RAG_Techniques

    This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…

    Jupyter Notebook

  6. RagBot RagBot Public archive