HomeCompaniesActiveloop

Database for AI

We provide a simple API for creating, storing, versioning, and collaborating on multi-modal AI datasets of any size. With Activeloop's open-core stack, you can rapidly transform and stream data while training models at scale. Deep Lake powers foundational model training by acting as a vector database with significant benefits, such as (1) the ability to use multi-modal datasets to fine-tune your own LLM models, (2) storing both the embeddings and the original data with automatic version control, so no embedding re-computation is needed (3) truly serverless service with no vendor lock-in. How cool is that? GitHub loves us - we're one of the fastest-growing libraries there, and we're used by little-known companies like Google, Waymo, and Intel. No big deal. Our founding team hails from places like Princeton, Stanford, Google, and Tesla, and we're backed by Y Combinator & other Silicon Valley heavyweights. Activeloop is hiring, and we want you! Check out our open roles on our YC page and join the fun. 10-min demo: https://activeloop.wistia.com/medias/aibvo0dst2 Whitepaper: https://www.deeplake.ai/whitepaper
Active Founders
Davit Buniatyan
Davit Buniatyan

Davit Buniatyan, Founder

Founding CEO Activeloop, PhD on leave from Princeton, AI/ML, Data and Infra, Y Combinator S18, UCL 16’ Working on Data 2.0
Jobs at Activeloop
Mountain View, CA, US
$120K - $200K
6+ years
Mountain View
$120K - $200K
6+ years
Mountain View
$160K - $250K
6+ years
California
$200K - $300K
11+ years
Activeloop
Founded:2018
Batch:Summer 2018
Team Size:15
Status:
Active
Location:Mountain View
Primary Partner:Diana Hu
Company Launches
Activeloop L0: State-of-the-Art RAG Accuracy on Your Data
See original launch post

Hey! Davit here form Activeloop. While working on Deep Lake, I have seen many RAG systems collapse when exposed to production-scale corporate data. They often rely on predefined loops, custom logic and rigid agent scaffolds. Activeloop-L0 provides your agent with highly precise and answers grounded on your multimodal data.

https://youtu.be/pnU9yd4KWy0

Why can’t we reliably analyze corporate documents?

  • Architectural hurdles: messy data integrations, unexpected infra costs, and reliability/safety constraints.
  • Commodity RAG lacks depth for multimodal enterprise data (documents, images, audio).
  • Infrastructure burden: parsing, chunking, embeddings, indexing, vector DBs, and agent loops slow teams.

But wait, is RAG still relevant despite large context models?

Let’s consider four extensive NASA documents [1, 2, 3, 4], each between 80 to 100 pages, containing visual descriptions, and pose a highly complex question.

ChatGPT with o3, despite having full PDFs in context, failed after 11 minutes of reasoning. Now, imagine you have thousands of corporate documents that can’t be contained in a context. In contrast, Activeloop-L0 provided the correct answer in 4 minutes and can scale to a million documents.

What is Activeloop-L0?

Activeloop-L0 is a compound AI system that ingests your unstructured data and returns grounded answers. Behind the scenes, Deep Lake indexes neural representations at scale, then fuses “thinking tokens” with high-precision retrieval for fast multi-hop reasoning.

It is available on chat.activeloop.ai now.

How is it different compared to a traditional RAG?

  • Multimodal: Built-in support for images, PDFs, audio, and spreadsheets.
  • Integrated Reasoning & Retrieval: Eliminates the need for loops.
  • Deep Indexing: Cost-effective multi-layer indexing for richer context early on.
  • Simple: Focus on innovation, not maintaining infrastructure.
  • Grounded and Accurate: Clear citations for trustworthy insights.

How accurate is Activeloop-L0?

Activeloop-L0 achieves overall 85.6% state-of-the-art accuracy on 1,142 multimodal questions (292 PDFs, 5.5K pages). It outperforms text only RAG by +20%, visual RAG by +10%, and Alibaba’s ViDoRAG by +6% on their own ViDoSeek benchmark.

Is there an OpenAI-compliant API?

Yes, Activeloop-L0 is available with an OpenAI-compliant API. You can easily plug into your agents for providing high relevant context. You can get started here. https://docs.activeloop.ai/setup/quickstart

Ready to Deploy on Your Data?

Activeloop is trusted by F500 including the likes of BayerFlagship Pioneering, Matterport (W12 acquired by CoStar).

  • Your Cloud: Deploy on your cloud, ensuring data never leaves your infrastructure.
  • Your Models: Integrate your LLMs.
  • Your Security: SOC2 compliance, fine-grained access control, and SSO.

Book a call to discuss enterprise deployment.