ApertureData Resource Library

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Reflecting on 2024:  ApertureData's Journey and What's Next for Multimodal AI Data Management in 2025.
Reflecting on 2024: ApertureData's Journey and What's Next for Multimodal AI Data Management in 2025.
Happy holidays and wish you 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.
Blogs
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Blogs
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.
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Lessons Learned Building a Cloud-Agnostic Database‍
Case Studies
Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
'The company uses ApertureDB to enhance vector search performance on their library of embeddings, achieving a 2.5x improvement in
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Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
Blogs
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.
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Building Real World RAG-based Applications with ApertureDB
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What’s in Your Visual Dataset?
Blogs
What’s in Your Visual Dataset?
CV/ML users need to find, analyze, pre-process as needed; and to visualize their images and videos along with any metadata easily...
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Product
Usability and Debugging
Visual Data
Dataset preparation and management
Are Vector Databases Enough for Multimodal Data?
Videos & Podcasts
Are Vector Databases Enough for Multimodal Data?
AICamp talk with user examples showing the need to go beyond vector database...
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Events
Vector / similarity / semantic search
Multimodal / Generative AI
Knowledge graph and graph databases
Dataset preparation and management
Usability and Debugging
ApertureDB 2.0: Redefining Visual Data Management for AI
Blogs
ApertureDB 2.0: Redefining Visual Data Management for AI
A key to solving Visual AI challenges is to bring together the key learnings of...
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Product
Visual Data
High performance
Dataset preparation and management
Usability and Debugging
Machine Learning
Find Matching Faces: Metadata and Vector Search in ApertureDB
Videos & Podcasts
Find Matching Faces: Metadata and Vector Search in ApertureDB
See how to search for faces based on metadata constraints and facial similiarity matching...
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Product
Dataset preparation and management
Vector / similarity / semantic search
Visual Data
Knowledge graph and graph databases
Simplifying Image Recognition using ApertureDB and Python
Videos & Podcasts
Simplifying Image Recognition using ApertureDB and Python
Datacamp code-along session to learn about workflows for image and video data stored in ApertureDB ...
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Product
Visual Data
Machine Learning
Dataset preparation and management
AI for Visual Data: Computer Vision in Business
Videos & Podcasts
AI for Visual Data: Computer Vision in Business
Datacamp panel on high value use-cases for image & video data, best practices for managing and analyzing visual data ...
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Industry Experts
Visual Data
Machine Learning
The Power of A Growth Mindset
Videos & Podcasts
The Power of A Growth Mindset
Rising tide podcast with Margaret Weniger on journey from start to ApertureData...
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Industry Experts
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ApertureDB Data Sheet
Data Sheets
ApertureDB Data Sheet
This one pager provides an overview of ApertureDB
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Product
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Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
Case Studies
Badger Technologies Uses ApertureDB to Solve "Wrong Product" Placement Problems at Scale
'The company uses ApertureDB to enhance vector search performance on their library of embeddings, achieving a 2.5x improvement in
Read More
Watch Now
Industry Experts
Vector / similarity / semantic search
High performance
Infrastructure and Deployment
Data privacy and security
Retrieval augmented generation (RAG)
Usability and Debugging
Multimodal / Generative AI
Machine Learning
High performance
Dataset preparation and management
Knowledge graph and graph databases
Visual Data
Vector / similarity / semantic search
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