How It Works —
GenAI-Native Document Orchestration
A deterministic processing pipeline powered by the latest AI models. No templates, no training — production-ready from day one.
Processing Pipeline
Import
Upload documents via UI, API, or watched folder. Supports PDF, images, TIFF, fax — any format.
OCR
Premium optical character recognition extracts text, tables, handwriting, and spatial layout from every page.
Split
Intelligent document splitting separates multi-document packets into individual logical documents.
Classify
AI classifies each document by type — no templates, no training data. Just a description of what to expect.
Extract
Structured field extraction with confidence scores. Schema-driven, deterministic, and auditable.
Validate
Business-rule validation catches errors, flags exceptions, and ensures data quality before downstream delivery.
Two-Agent Architecture
A deterministic runtime agent processes documents at scale, while an intelligent supervisor agent continuously improves accuracy.
Document Processing Agent
Executes the processing pipeline deterministically. Handles OCR, classification, extraction, and validation with reproducible results at any scale.
- ✓ Deterministic execution
- ✓ Real-time processing
- ✓ Full audit trail
Supervisor Agent
Analyzes processing results, identifies patterns in errors, and suggests prompt and configuration improvements. Learning happens through controlled feedback — never uncontrolled fine-tuning.
- ✓ Continuous improvement
- ✓ Controlled learning loop
- ✓ Human-in-the-loop approval
GenAI-Native Setup Flow
Three steps to production. No templates, no training datasets, no labeling.
Define Document Intent
Describe your document types and the fields you need in natural language. No schemas to learn.
Start Processing Immediately
Upload documents and get results right away. The AI understands your intent from the description.
Improve Via Feedback
Review results, correct errors, and the Supervisor Agent learns from your feedback to improve accuracy.
Enterprise-Grade Controls
Deterministic Execution
Reproducible pipeline runs with full audit trail. Same input always produces the same output.
Business-Rule Validation
Define rules that check extracted data against business logic — cross-field validation, format checks, range constraints.
Explainability & Audit
Every extraction decision is traceable. See which model produced each result, with confidence scores and source text.
Secure Deployment
Deploy on-premises, in your own Azure tenant, or as a managed service. Your data never leaves your control.
Controlled Learning
Supervisor Agent improves prompts and configurations over time through a feedback loop — not uncontrolled fine-tuning.
Model Agnostic
Bring any model. Orchestrate across GPT, Claude, Gemini, Llama, and open-source models. Evaluate and compare on your own documents — pick the best model for each task.
Deployment Options
Cloud Managed
Fully managed on Azure. We handle infrastructure, scaling, and updates.
On-Premises
Deploy in your data center. Full control over data residency and compliance.
Self-Hosted
Run in your own Azure tenant or Kubernetes cluster. Docker-based, single-container deployment.
Try it yourself
See the platform in action on your own documents.
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