⏰ Still time to join tomorrow’s Lunch & Learn: From RAG to GraphRAG — Smarter AI Retrieval  (Aug 26 @ 11 AM PDT) Our community member, Ayesha Imran, will walk us through automating GraphRAG with Google Gemini and ApertureDB, and explain why GraphRAG outperforms Vanilla RAG for

I wouldn’t miss it!

🌞 The summer season might be winding down, but the #SummerOfWorkflows rolls along! This week’s release ApertureDB Object Detection Workflow, treats bounding boxes and polygons on images as first class citizens making it easy to: Ingest raw images from AWS/GCP Detect &

These are some great examples and we are looking into building more over the coming days ! Devinder Sodhi Namrata Banerjee

I could finally use examples from some shows I really like to explain a concept that's really top of mind and coming up in so many discussions for me lately! Even better is to realize how ApertureData is just built to last through the AI generations!

Teach ‘em young now ! Anthropic at the SF Exploratorium

It’s very disappointing when Dandelion Chocolate runs out of cacao fruit smoothie. Had to fall back on marocchino which was a one time favorite

Featuring talks by Daft & ApertureData, plus a fireside chat on challenges, motivations, and where multimodal data is trending. Register now: luma.com/skmqt8za

☀️ We’re in the final stretch of the Summer of Workflows — only 3 left! This week we are spotlighting Face Detection 👀 Face detection powers everything from: - Organizing massive photo libraries - Enhancing security systems - Personalizing user experiences But building a

𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗯𝗹𝗼𝗰𝗸𝘀 𝗼𝗿 𝗯𝗹𝗮𝗰𝗸 𝗯𝗼𝘅 - 𝘁𝗵𝗮𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻... 👀Why did we launch workflows for generating embeddings, object detection, face detection, and others instead of landing you in our UI with multimodal RAG? 🧠Why SQL compatibility

🦙 Excited to be 1 of 10 startups demoing at Llama Lounge 19 on Sept 11! Huge thanks to Jeremiah Owyang for picking #ApertureDB from 1,000+ applications. Struggling with multimodal data for your AI apps? Text, images, audio, video, embeddings, … memory gaps slowing your agents?

MEET THE SPEAKER: Vishakha Gupta Machine learning began with recognition tasks, then over the last two years generative AI has become woven into our daily lives—bringing interaction and creativity, but largely limited to a single modality: text. Now, with the rise of AI agents,

🔥 Talk about simplify dataset creation 🔥 Even though a lot can be done with foundation models, there is plenty of reasons and circumstances that need fine tuning or still building your own model, and that means labeled datasets. What I find really valuable in this workflow -

: context context context :: who will solve the layers and orchestration ::: ApertureData will keep rocking and here is what Vishakha Gupta-Cledat shared at Llama Lounge 19 at SAP Palo Alto

Last night’s Llama Lounge was awesome and the energy in the room contagious! A huge thank you to Jeremiah Owyang for inviting ApertureData to present and Samuel J. Cummings III for keeping it moving all night. Vishakha delivered a great one-minute pitch, and the conversations at our

Last night at Llama Lounge 19, it was AI in the air with some quality conversations and such intriguing products being built. Thank you Jeremiah Owyang , Samuel J Cummings III, and the SAP AppHaus Palo Alto team for such a vibrant and well-curated gathering. Some highlights and

Sailing at this angle feels freaky and plenty adventurous for the day

🤓My husband and I argue a lot about languages. After all , French Hindi English are languages that give you so many pros and cons to argue over. 📣But this is about SQL, the preferred language in the DB world and some other classic query languages vs. their applicability