Building the memory layer for AI agents
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
Persistent memory for multi-agent systems — because agents that forget can't improve.
- 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-memoryI 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
- Microsoft Certified: Azure Data Engineer Associate
- Databricks Generative AI & Data Engineering
- Oracle Cloud Data Management
- DBT Fundamentals
- RagBot — Scalable RAG bot with Google Drive, OneDrive & Slack connectors
- Mindful Moment — Mindfulness app on Google Play
- YouTube Watch Later Organizer — Chrome extension
- 🎵 Music + long walks = my brainstorming combo
- 🧠 Currently exploring generative agent research (Stanford Smallville and beyond)