SynapCores – AI-native database (vector, graph, SQL, AutoML, LLM)
Replaces the pgvector plus AGE plus model server stack with a single binary and query.

Company brain for AI agents when Prism and GBrain already exist.
Engineering teams building AI agents
Prism · GBrain · Mem
I've been working on a company brain project for fun so engineers like myself can stop rebuilding the same context retrieval, memory management, and app integrations for each job or project they start on. I started by building a context retrieval system like prism-coder and GBrain for my local agents. When I connected 10+ apps, the dedicated MCP servers at each project would work fine, but the agent itself would struggle to find and understand cross-application context when trying to take a meeting transcript of the product + engineering decisions -> jira ticket -> PR and using that to help it debug or enhance it through an end to end epic. Then I started toying with the idea of ingesting individual app data into a centralized DB but I was still having to create a custom ingestion solution for each app I integrated with which sucks up so much time getting an OAuth client + secret set up for each app so that all of my teammates and I could use the same DB for their agents.
It's been a fun project to try and figure out these memory management and context retrieval problems like ensuring that query responses are grounded in some truth and citations, but you also don't just get every piece of data you have returned on every query.
I figured developers could save some time and effort in building this stuff themselves (or with their Software Factories) and should just be able to pull it off the shelf and reduce the idea -> building time frame so they can focus on making their agents actually do things to help them at work. Since then, I've been able to expand on it and connect mine and my friends' Paperclip agent teams to it via an MCP server to really test out the shared intelligence aspect of a swarm of agents.
Thinking about open sourcing it or making it self hostable since companies probably don't want their entire company data synthesized and stored into one third-party SaaS offering, but it's still the easiest way to make it something you can play around with. Would love feedback on it for why it's dumb.
Replaces the pgvector plus AGE plus model server stack with a single binary and query.
SaaS boilerplate with auth and payments, but identical to dozen others (Wasp, Shipfast, Refine).
Yet another AI memory layer competing with Mem.ai and Notion AI.
Navigation-over-search architecture sounds great until you realize it's just another RAG wrapper.
Replaces PostgreSQL + Redis + Neo4j + ClickHouse with one Rust binary.
Knowledge graphs beat vector similarity for structured relationship queries.