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EyeLevel AI

EyeLevel AI is an AI platform for building high-accuracy RAG applications. Ideal for enterprises, it helps eliminate hallucinations using vision-powered parsing.

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May 1st, 2024

About EyeLevel AI

EyeLevel AI is an AI platform that helps developers and enterprises achieve 95% RAG accuracy without the common failures of standard vector search systems.

The platform is powered by GroundX, an ingestion engine that utilizes proprietary vision models trained on over one million enterprise document pages. This technical approach preserves critical spatial context for tables, forms, and complex diagrams that traditional text-based chunking typically loses. By converting visual data into semantic objects, EyeLevel AI provides a robust data pipeline that ensures LLMs receive high-fidelity context for truly grounded generation.

The system supports massive enterprise scale, offering a guaranteed 3-second retrieval time for up to 100 concurrent users in its production configurations. It handles data with extreme security via AES-256 encryption and offers specialized deployment options for air-gapped Kubernetes environments. Whether utilizing the managed cloud or on-premise infrastructure, the platform integrates seamlessly with any LLM, including OpenAI, Groq, and Llama-3, through a streamlined API suite.

Browser / Automation – URL Web Crawling Toolchain – API-first / Python / JavaScript

Capabilities – Vision-powered X-Ray parsing and semantic search

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Who is using EyeLevel AI?

Enterprise DevelopersData EngineersAI Solution ArchitectsCompliance OfficersLegal Tech Teams

Key Features

8 features
  • X-Ray Vision-Powered Parsing
  • 95% RAG Accuracy Benchmarking
  • Air-Gapped Kubernetes Support
  • 3-Second Retrieval Latency
  • Semantic Search API
  • Automatic Data Chunking
  • AES-256 Data Encryption
  • Multi-format Support (PDF, JPG, PNG)

Use Cases

4 use cases
  • Automating financial report analysis
  • Building secure legal research assistants
  • Processing complex technical manuals
  • Enterprise-wide semantic knowledge bases
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