Activeloop (@activeloopai) 's Twitter Profile
Activeloop

@activeloopai

Deep Research with AI on Your Multi-Modal Data

linktr.ee/activeloop

Store any AI data.
Train/Fine-tune LLMs.
Deploy AI Knowledge Agents

ID: 1255533785485119493

linkhttps://activeloop.ai/?utm_source=twitter&utm_medium=social&utm_campaign=bio calendar_today29-04-2020 16:26:01

1,1K Tweet

3,3K Followers

202 Following

This Week in Startups (@twistartups) 's Twitter Profile Photo

This is EXACTLY the kind of AI stuff that I can get nerdy about. There's no way a human being could sift through all these documents! Let the computers do it! That's a perfect job for them.

Activeloop (@activeloopai) 's Twitter Profile Photo

“cia followed oswald for a long time. How could he kill jfk without being noticed by cia. That suggests cia involvement. Whats the info on this?”

Global AI Community (@globaicommunity) 's Twitter Profile Photo

Excited to share our latest episode with Davit from Activeloop! Dive into the world of AI search, large language models, and self-driving impacts on daily life. Join us for an engaging chat! 😊 Watch here: youtube.com/watch?v=usr87W… #AI #Activeloop

Davit (@dbuniatyan) 's Twitter Profile Photo

(1/7) Rushing from RAGs to Agents before even fully solving RAG? 🚀 Introducing Activeloop-L0: Agentic Reasoning on Your Multimodal Data

Davit (@dbuniatyan) 's Twitter Profile Photo

(2/7) Here is a complex query on 4 large NASA pdfs. ChatGPT o3 failed having full context, while Activeloop-L0 nailed it, available starting today on chat.activeloop.ai

(2/7) Here is a complex query on 4 large NASA pdfs. ChatGPT o3 failed having full context, while Activeloop-L0 nailed it, available starting today on chat.activeloop.ai
Davit (@dbuniatyan) 's Twitter Profile Photo

(3/7) Analyzing corporate documents in 2025 still very hard. Here is why? → Struggles with tables, charts, images, and other multimodal data. → Overcomplicated prototypes that can't scale beyond initial pilots. → Lack of reliable solutions for precise, grounded answers

Davit (@dbuniatyan) 's Twitter Profile Photo

(4/7) Activeloop-L0 ingests your unstructured data and returns sourced answers with relevancy scores and visual reasoning. Deep Lake indexes neural representations at scale, then fuses “thinking tokens” with high-precision retrieval for fast multi-hop reasoning.

(4/7) Activeloop-L0 ingests your unstructured data and returns sourced answers with relevancy scores and visual reasoning. Deep Lake indexes neural representations at scale, then fuses “thinking tokens” with high-precision retrieval for fast multi-hop reasoning.
Davit (@dbuniatyan) 's Twitter Profile Photo

(5/7) Activeloop-L0 achieve a state-of-the-art 85.6% accuracy on ViDoSeek, it surpasses traditional RAG approaches by 20%+ and Alibaba's ViDoRag by +6% on their own benchmark.

(5/7) Activeloop-L0 achieve a state-of-the-art 85.6% accuracy on ViDoSeek, it surpasses traditional RAG approaches by 20%+ and Alibaba's ViDoRag by +6% on their own benchmark.