Activeloop-L0 is a compound AI system that ingests and answers questions from your unstructured, multimodal data. It delivers accurate, traceable answers with clear source citations, ensuring trust and transparency through visual reasoning.
[Quickstart](https://docs.activeloop.ai/setup/quickstart) or [Request a Demo](https://www.activeloop.ai/contact/)
## Key Capabilities: Go Beyond Basic RAG
All thanks to [Deep Lake](https://docs.deeplake.ai/latest/), Activeloop provides unique advantages over traditional RAG systems, enabling deeper understanding and control of your data.
π‘ **Native Multimodal Understanding**: Leverage advanced Visual Language Models (VLMs) to intrinsically understand PDFs, PowerPoints, images, audio, and more **without** brittle OCR or complex pre-processing.
βοΈ **Your Data, Your Cloud, Your Control**: Deploy entirely within your secure cloud infrastructure. Connect private data sources and bring your own models (BYOM), ensuring sensitive data never leaves your perimeter.
β **Trustworthy & Explainable Results**: Deliver highly accurate, grounded answers backed by clear citations directly to the source data, ensuring reliability, auditability, and user trust.
Activeloop-L0 achieves overall 84% 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 Alibabaβs ViDoRAG by +5% on their own ViDoSeek benchmark
## Why Activeloop? Achieve Tangible AI ROI
π **Accelerate & Automate Workflows**: Seamlessly embed deep knowledge retrieval and reasoning into core business processes like compliance checks, research synthesis, and customer support.
π§βπ» **Free Your AI Team to Innovate:** Eliminate the infrastructure bottleneck. We automate parsing, chunking, embedding, and indexing, letting your team focus on high-value AI applications, not data plumbing.
β¨ **Unlock Actionable Insights**: Discover hidden connections and analyze trends across disparate data types. Extract meaningful insights previously buried in your complex multimodal data assets.
## Use Cases Across Industries
* **Financial Services:** Analyze quarterly reports alongside market news videos and earnings call audio.
* **Pharma & Life Sciences:** Accelerate R\&D by connecting research papers, clinical trial data, and lab notes.
* **Technology:** Gain holistic customer understanding by correlating support tickets, call audio, and user session recordings.
* **Legal & Compliance:** Perform deep analysis across case law, contracts, and internal communications with full audit trails.
* **Insurance:** Streamline claims processing and enhance fraud detection by correlating claim forms, incident reports, damage photos/videos, repair estimates, and policyholder data.
### Overcoming Traditional RAG Limitations
Basic RAG struggles where enterprise needs are greatest:
* **Agentic Scaffold:** predefined loops and rigid agent scaffolds.
* **Multimodal Data:** Difficulty processing and relating information beyond plain text.
* **Infrastructure Burden:** High cost and effort to build/maintain complex pipelines.
* **Integration Challenge:** Difficulty embedding insights into meaningful workflows.
* **Control & Security:** Concerns over data leaving secure perimeters with SaaS RAG.
### Activeloop Knowledge Agents vs. Traditional RAG
| Feature | Traditional RAG | **Activeloop Knowledge Agents** |
| --------------------------- | ------------------------------- | ---------------------------------------- |
| **Data Support** | Mostly text-only | β **Native Multimodal** |
| **Reasoning** | Limited keyword/semantic search | β **Advanced relationship & multi-step** |
| **Integration** | Basic retrieval | β **Deep workflow integration** |
| **Data Pre-processing** | Manual/Complex (OCR often) | β **Automated / Native understanding** |
| **Infrastructure** | High complexity, manual mgmt. | β **Automated, streamlined** |
| **Deployment/Security** | Often SaaS, limited control | β **Your Cloud, Secure Private, BYOM** |
| **Accuracy/Explainability** | Variable, opaque sourcing | β **High accuracy with clear citations** |
***
### Get Started with Activeloop
Ready to unlock the true potential of your enterprise data?
1. [**Explore the Documentation**](https://docs.activeloop.ai/user-guide)**:** Dive deeper into concepts, architecture, and API references.
2. [**Try the Quickstart**](https://docs.activeloop.ai/setup/quickstart)**:** Set up a basic instance and index your first multimodal data.
3. [**Talk to Us**](https://www.activeloop.ai/contact/)**:** Discuss your specific use case and see a tailored demonstration.
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# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.activeloop.ai/activeloop.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
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