Eyelevelai: Enterprise RAG and Document Processing
Eyelevelai helps software companies and enterprises build RAG-based AI applications. It is designed for teams that need to process visually complex documents with options for on-premises deployment to support data privacy.
At a glance
- Best for
- Software development firms, Enterprise companies, Organizations with strict data privacy requirements, Businesses with complex, non-standard document layouts
- Pricing
- Cloud plans include a free tier and a Pro tier starting at $500/month. On-premises pricing ranges from a free version for non-commercial use to $15K/year for production deployment.
- Key use cases
- Building RAG Applications, Legal Document Analysis, Customer Support Automation, Insurance Fraud Detection, E-commerce Knowledge Bases
- Integrations
- Salesforce, Hubspot, Slack, Zapier, Google Drive
- Official website
- Visit Eyelevelai official website
Eyelevelai offers a platform called GroundX designed to sit between private enterprise data and large language models. The software focuses on the ingest phase of AI development, using a vision model to convert PDFs, scans, and complex layouts into a format for AI use.
The tool is designed for software developers and enterprise operations managers in sectors such as legal, healthcare, and finance. It supports a data pipeline including ingestion, parsing, extraction, and a final correction stage to verify data accuracy.
Buyers can choose between a managed cloud environment or deploying the software on their own Kubernetes clusters, including air-gapped setups for high-security needs. It also includes no-code tools for building AI bots.
Before choosing this tool, buyers should confirm if they require a managed service or a self-hosted environment and whether their specific document types require the custom fine-tuning available in enterprise plans.
Key Features
GroundX Data Pipeline
A four-stage process consisting of Ingest, Parse, Extract, and Correct to turn documents into structured data.
Double-Model Vision System
A system trained on over one million pages to identify tables, layout regions, and visual hierarchies.
Flexible Deployment
Supports managed cloud, on-premises installation, and air-gapped environments using Kubernetes.
No-Code Bot Builder
Tools to upload content, design bot themes, and launch AI assistants on websites, SMS, or via QR codes.
RAG Evaluation Tools
Diagnostics to help users identify where errors originate in the ingest, retrieval, or completion stages.
Source Linking
Provides citations within AI answers so users can verify the source material.
Use Cases
Building RAG Applications
Converting complex enterprise documents into data for use in LLM-powered apps.
Legal Document Analysis
Analyzing transcripts, medical files, and police reports to find answers within legal files.
Customer Support Automation
Ingesting contact center decision trees and manuals to support human agents or customers.
Insurance Fraud Detection
Using the FraudX tool to identify insurance fraud through AI agents.
E-commerce Knowledge Bases
Training bots on product catalogs and instruction manuals to assist customers.
Best For
- Software development firms
- Enterprise companies
- Organizations with strict data privacy requirements
- Businesses with complex, non-standard document layouts
Integrations
- Salesforce
- Hubspot
- Slack
- Zapier
- Google Drive
- Dropbox
- Box
- Microsoft OneDrive
- MailChimp
- Marketo
- Segment
- Heap
- Intercom
Pricing
Cloud plans include a free tier and a Pro tier starting at $500/month. On-premises pricing ranges from a free version for non-commercial use to $15K/year for production deployment.
FAQ
What is the difference between Eyelevelai Cloud and On-Prem?
- Cloud is a managed service where Eyelevelai handles the compute, while On-Prem allows users to run the platform on their own Kubernetes cluster, including air-gapped environments.
Does Eyelevelai offer a free version?
- Yes, there is a free cloud tier with a 5M token ingest limit and an open-source on-premises configuration for non-commercial use.
How does the platform handle complex document layouts?
- It uses a vision model trained on over one million pages to identify tables, headers, and visual hierarchies.
Source category: Software Development
Source subcategory: AI Development Platform
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Categories
Software Type
How AI is used
Eyelevelai is an enterprise RAG platform that converts complex documents into LLM-ready data using the GroundX engine. It supports both cloud and air-gapped on-premises deployments. Advanced features like custom fine-tuning are reserved for enterprise tiers.
Pros & Cons
Pros
- Supports air-gapped on-premises deployment
- Handles visually complex documents like tables and decision trees
- Includes a free tier for initial testing
- Provides source citations for AI-generated answers
Cons
- Custom fine-tuning and premium ingest are restricted to enterprise plans
- On-premises production deployment requires an annual fee
- The free cloud plan has token and search limits
