Contract & Legal Document Intelligence
AI that reads contracts, extracts key terms, obligations, dates, and parties — and flags changes between versions or deviations from your standard template. Cut hours of manual review per agreement.
Wizeb — Document AI
Your documents shouldn't require a human to read them.
Every business is sitting on a backlog of contracts, invoices, applications, reports, and forms that require someone to read, extract, and act on the information inside. That work is slow, error-prone, and expensive. Wizeb builds AI document pipelines that process unstructured documents at scale — extracting exactly what you need, flagging what matters, and pushing structured data to the right systems.
What we process
Every project starts with your specific problem
These are the most common document ai systems we build. Most projects combine elements from several areas.
Invoice & Financial Document Processing
Automated extraction of line items, totals, vendor details, and payment terms from invoices and receipts — with validation against purchase orders and automatic posting to your accounting system.
Application & Form Processing
AI that processes application forms, intake questionnaires, and onboarding documents — structuring the data, scoring against your criteria, and routing to the right team based on content.
Built for Usage-Based Efficiency
All our document ai solutions include token optimization as standard — reducing your ongoing API costs by 40-70% through smart routing, caching, and efficient architecture.
Learn about AI Cost OptimizationHow We Work
From problem to production
No slide decks, no vague roadmaps. Here's exactly how a project runs from first call to live deployment.
01
Document audit
We catalogue the document types you need to process, their formats, the data you need to extract, and the downstream systems it needs to reach. This defines the pipeline architecture.
02
Extraction model design
We build and test extraction logic against your real documents — handling variation in layout, format, and language. Accuracy targets are defined upfront and validated before deployment.
03
Validation and exception handling
Every extraction runs through validation rules. Low-confidence outputs and anomalies are flagged for human review rather than pushed downstream silently. Accuracy is auditable.
04
Integration and deployment
Structured outputs are pushed to your CRM, ERP, database, or any downstream system. We handle the integration, document the pipeline, and support you through go-live.
Case Study
What this looks like in practice
A real project, real results. No client name — that's deliberate.
Client Type
Corporate Training Provider
Shipped & live
“44% drop in admin overhead — and a 31% lift in course completion rates”
The Challenge
"Our coordinators were spending more time processing forms, chasing enrolments, and updating spreadsheets than on anything that actually improved learning outcomes. It was completely unsustainable."
The Solution
A document processing pipeline was built to handle all intake forms, enrolment documents, and completion certificates automatically — extracting structured data, validating against programme requirements, and pushing records to the LMS without manual entry.
Key Results
- 44%Reduction in administrative overhead
- 31%Improvement in course completion rates
- 2.4×Documents processed per hour (same team)
Technologies We Use
Model-agnostic. Stack-agnostic.
We pick what's right for the problem — not the most impressive-sounding name.
Claude (Anthropic)Extraction LLM
GPT-4o VisionExtraction LLM
Tesseract OCROCR
AWS TextractOCR
LangChainPipeline
PythonProcessing
PostgreSQLStorage
REST APIs / WebhooksIntegration
Common Questions
Things people ask before starting
Work with Wizeb
Ready to build something?
Tell us about the problem. We'll come back with a realistic picture of what's possible, what it costs, and how fast it can be running.