Vishakha Gupta

An agent walks into a repeat problem like it's the first time, every time. Most memory tools treat everything as disconnected text chunks in a vector store, so nothing carries over, not the reasoning, not the context, not what actually happened last time.

Aperture Nexus is our answer. Context, who, what, when, why, and how, is stamped on every commit, so retrieval actually means something later. Enable lineage tracking when you need it, and every commit traces back to its original source. And because it's built directly on ApertureDB (aperturedata.io), the unified graph-vector-multimodal database already running in production, it works the same whether your agents are text-only today or need images, documents, video, or structured records tomorrow. No migration later if that's where you end up. Knowledge and Memory both live together in ApertureDB.

We re wrapping up our Summer of Workflows with something big: Embedding Generation for Videos in ApertureDB!

This workflow lets you generate embeddings for frames and clips so you can finally treat videos as a first-class citizen in your AI applications, just like ApertureDB always supported.

See It In Action

Real-world use cases:

Summer isn t over yet and neither is our Summer of Workflows!

Today s release: Extract Text From Images & PDFs in ApertureDB.

See It In Action

With just a few clicks you can: