ApertureDB Multimodal AI Workflows

Automate common AI tasks for multimodal data

Developer Tools

Artificial Intelligence

GitHub

Database

Hello, Product Hunt Community 👋, I’m Vishakha Gupta, CEO and Co-founder of ApertureData. I am excited to do my very first Product Hunt Launch, for ApertureDB Multimodal AI Workflows. If we want AI to think like humans, it needs all the signals a human brain processes to form our stories, which means multimodal data. Having worked with AI and data for years, I understand the immense challenge users face when trying to leverage multimodal data. Real world data is messy and hard to access. Why? It’s scattered in silos, there are different databases or data tools built based on the modality of data, and how on earth do you talk to all those data types through one language? Teams spend countless hours wrangling images, text, and other data types, trying to build AI applications that truly deliver value. This leads to delayed deployments, increased costs, and missed opportunities. Sounds familiar? 🙄 That’s exactly why we built ApertureDB — a purpose-built database that unifies multimodal data management, vector search, and knowledge graphs into a single backend, delivering up to a 10x productivity boost and accelerating AI deployments by 6-9 months on average. Building on this foundation, we’re excited to launch ApertureDB Multimodal AI Workflows today — the easiest way to manage multimodal datasets with just a few clicks on a scalable cloud platform. 🚀 What are ApertureData Multimodal AI Workflows? Workflows provide a way to automate the execution of a commonly-performed task, when managing multimodal datasets for AI. You can use preconfigured sample sets or your own data when executing the workflows. Here’s a breakdown of the workflows for today’s launch: ✅ Ingest Datasets: Ingest datasets into ApertureDB, from a selection of preconfigured public datasets and explore how it can be used with real data. ✅ Automated Embedding Generation: Generate embeddings for images, then use these embeddings to search for similar images or classify them based on the embeddings. ✅ Detect Faces: Add bounding boxes for faces detected within images in ApertureDB. ✅ Detect Object: Add labelled bounding boxes for objects detected within images in ApertureDB ✅ Direct Jupyter Notebook Access: Run Jupyter notebooks with seamless access to your ApertureDB instance. 🔥 Why ApertureData Multimodal AI Workflows stand out? To deliver a meaningful AI solution built on rich data, today’s infrastructure requires stitching together disparate a number of tools. ApertureDB workflows offer a unified approach. 💸Use Cases From e-commerce, smart retail, to inspection and life sciences, whether you are building classic ML, analytics or Generative AI applications, these workflows empower users to build advanced AI applications with ease. 😍 Want to Try it Out? Sign Up for a free 30-day trial of ApertureDB - https://cloud.aperturedata.io/si... We’d love your feedback — share your thoughts at [email protected] Have questions or need help – we are available on Slack A special perk for the Product Hunt community: Join our Virtual Lunch and Learn today (March 13th, 2025 @ 9AM PST ) for a deep dive into Workflows. There is still time to Save Your Spot - https://lu.ma/vnabtolp! What’s Coming Next? We’re continuously expanding our workflow library (available to the community on Github) to cover more use cases and integrations. 📢 Soon, you’ll be able to: * Integrate with more data sources and AI models * Launch embedding, graph, and attribute classification for other data types beyond images * Access advanced customization options for specific business needs. Huge thanks to this amazing community — your support is invaluable! Let’s build the future of multimodal AI together. 🚀 Best Regards, Vishakha Gupta CEO, ApertureData