ApertureData Resource Library

ApertureData and Realm Labs help developers build secure RAG chatbots by combining advanced permissions management with graph-vector storage, ensuring data protection and efficient access control.

Agentic RAG is the future of LLM applications! This blog article shows you how to build a powerful research paper search engine using ApertureDB & Huggingface SmolAgents.

Happy holidays and an exciting 2025 ahead as we shift from LLMs to AI agents, guardrails, and multimodality! Thank you for your continued support, and we look forward to partnering with you in the new year to tackle evolving challenges in AI and multimodal data management with ApertureDB.

Building cloud-agnostic software poses some challenges. Because we ran into some while building ApertureDB, a cloud-agnostic database specifically built for multimodal data and metadata, we discuss our learnings.

This panel of experts got together to demystify the various AI tools and technologies, understand how the technologies interplay, and help our audience understand both the similarities and differences, across various industries.

LLMs, RAGs, Chatbots, Agents. All hot topics! 🔥 But what does it mean to implement these and make them work well? See some real examples built on ApertureDB's purpose-built multimodal vector db.

AI Innovation Summit talk on the how we designed and developed ApertureDB to...

Explore Aperture\s mission to simplify the work of data scientists, engineers, and machine learning teams...

We asked our chatbot questions like "Can ApertureDB store pdfs?" and the answer it gave..