🔥See ApertureDB's Multimodal AI Workflows in action with CTO Luis Remis at Seattle Startup Summit 2025, Friday 3/28 at 8AM PST – Reserve Your Spot!
Case Studies
Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
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 with ApertureDB and HuggingFace SmolAgents
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.
Lessons Learned Building a Cloud-Agnostic Database‍
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.
Building Real World RAG-based Applications with ApertureDB
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.
Building Real World RAG-based Applications with ApertureDB
Combining different AI technologies, such as LLMs, embedding models, and a database like ApertureDB that is purpose-built for multimodal AI, can significantly enhance the ability to retrieve and generate relevant content.