Eigen Pal - Enterprise AI Solutions

Agentic Automation: Intelligent Document Processing

Transform unstructured documents into actionable data with AI agents that understand context and extract with precision

Production Workflows in Action

Real workflows processing thousands of documents per month for financial institutions

Insurance Contract Extraction

Extract structured data from insurance contracts

Extracts: Policy numbers, addresses, cadastral data, insurance amounts, dates

Handles: Scanned documents, handwritten forms, multiple formats

Output: Structured JSON with 20+ validated fields

Bank Statement Analysis

Analyze salary data for mortgage approval

Identifies: Primary employer, monthly income patterns, transaction types

Validates: Employment continuity, irregular payments, job changes

Output: 6-month salary history with compliance flags

Build Your Own

Customize inputs, outputs, and integrations for your use case

Custom Inputs: Any document type - invoices, contracts, forms, receipts

Custom Outputs: Define your own schema with validation rules

Custom Integrations: Connect to your CRM, ERP, databases, or APIs

>95%

Strong extraction accuracy

$0.01

Cheapest per A4 page

LLM+OCR

Combining best LLM and OCR models

Simple Workflow Definition

workflows:
  - id: insurance_extraction
    name: Insurance Contract Extraction
    steps:
      - type: load_document
      - type: extract_content
      - type: llm_json
        prompt: |
          Extract policy number, address,
          insurance amount, and dates...
        output_schema:
          type: object
          properties:
            policy_number: { type: string }
            address: { type: string }
            amount: { type: string }

Full Observability with Phoenix Tracing

Track every step of your AI workflow execution with detailed latency metrics and error detection

Deploy Anywhere: Cloud or On-Premises

Choose the deployment model that fits your security, compliance, and infrastructure requirements

Cloud Deployment

Fast, managed infrastructure with automatic scaling

Azure OpenAI Integration: Native support for Azure's enterprise AI services
Auto-Scaling: Handle volume spikes without manual intervention
Managed Updates: Automatic security patches and feature updates
Global CDN: Low-latency access from anywhere in the world
Enterprise-grade security certifications

On-Premises Deployment

Full control over your data and infrastructure

Air-Gapped Environments: Deploy in fully isolated networks
Custom LLM Integration: Use your own models or private endpoints
Data Sovereignty: Keep sensitive data within your infrastructure
Container-Based: Deploy with Docker/Podman for easy management
Your Security Controls: Integrate with existing IAM, VPN, and monitoring

Enterprise-Grade Quality & Reliability

Our AI agents are built for production with rigorous quality controls and monitoring

Accuracy at Scale

Structured Output Validation: JSON schemas ensure consistent, parseable results
Field-Level Accuracy Tracking: Monitor performance for each extracted field
Automated Evaluation: Reference datasets validate every workflow change
Confidence Scores: Identify low-confidence extractions for human review

Hallucination Prevention

Source Attribution: Every extracted value includes document references
Strict Schema Enforcement: Only valid enum values and formats accepted
Empty Field Handling: Returns empty strings instead of making up data
Multi-Step Validation: Cross-reference extracted data with document structure

High Uptime & Performance

99.9% Uptime SLA: Production-ready reliability with automatic failover
Async Processing: Process thousands of documents in parallel
Rate Limit Management: Smart throttling prevents API quota issues
Retry Logic: Automatic retries with exponential backoff

Full Observability

Phoenix Tracing: See every step of AI decision-making process
Performance Metrics: Track latency, throughput, and error rates
Audit Logs: Complete history of all document processing
Custom Alerts: Get notified of accuracy drops or system issues

Continuous Improvement

A/B Testing: Compare prompt variations on real data
Error Analysis: Identify patterns in extraction failures
Model Versioning: Track and rollback model changes
Feedback Loops: Learn from human corrections

Security & Compliance

Data Encryption: At rest and in transit with enterprise-grade protocols
GDPR Compliant: Data residency and privacy controls
Role-Based Access: Fine-grained permissions per workflow
PII Detection: Automatically flag sensitive information

EigenPal

Enterprise AI Agents That Transform Your Business