Challenges
A leading rental and real estate company in the U.S.—ranked second nationally in its sector—embarked on an enterprise-wide Oracle Financials Cloud transformation. As part of this modernization, the organization faced significant hurdles in extracting critical information from thousands of legacy contracts, customer documents, and billing records. These records, collected over decades, were stored in various formats: PDFs, scanned documents, section of handwritten content, and unstructured text, often maintained locally by field agents.
The extraction of essential master data, customer information, and contractual terms was critical for system readiness. However, relying on manual efforts to interpret inconsistent and often illegible documentation presented unacceptable delays, high costs, and risks of inaccuracy. Many contracts contained hidden or implicit details such as bill-to and ship-to addresses, charging bases, and agreement terms that could not be captured through traditional means without extensive training and manual verification.
The transformation team needed a solution that could interpret complex, inconsistent legal language across document types, extract critical metadata at scale, and prepare it in a structured format compatible with Oracle ERP—all while reducing time, cost, and risk.
About the company
- Industry: Rental and Real Estate
- Employees: Over 3,200
- Market Standing: Second largest in its sector in the U.S.
- Geographic Presence: Operates in the U.S., U.K., and Europe.
- Portfolio Size: Manages over 557 million sq. ft. of property.
- Development Focus: Specializes in office, retail, industrial, and more.
Approach
Trinamix proposed and implemented Documantra, an AI-powered data extraction and document intelligence solution specifically designed for unstructured and semi-structured environments. The engagement began with a proof of concept (PoC) focused on a representative set of contracts spanning three revenue streams. Using OCR to convert scanned documents into machine-readable text, Trinamix then applied Generative AI and prompt engineering techniques to extract and normalize relevant fields such as agreement terms, parties involved, property locations, financial values, and contract durations in required strutured format.
The core of the solution leveraged Retrieval-Augmented Generation (RAG) with vector-based semantic search to identify and extract fields even when terms varied significantly across documents. Prompts were fine-tuned to account for industry-specific legalese and common variations in phrasing. Where contracts provided inconsistent or fragmented information, the AI was trained to infer relationships and recommend logical associations based on historical patterns and contextual clues.
An interactive UI allowed business users to validate and, where necessary, override AI-generated results. The outputs were formatted according to the Oracle ERP data templates, enabling a smooth transition into the master data repositories. Throughout the engagement, the model’s accuracy and efficiency were continually evaluated and improved. Metrics such as precision, completeness, and efficiency were validated using both human feedback and scoring criteria defined in conjunction with the customer’s transformation leadership.
The agile methodology adopted by Trinamix ensured rapid iterations, early visibility into results, and continuous improvement. Within weeks, the AI system was able to produce validated, structured data for over 2,000 contracts—at less than 10% of the cost of a manual approach and with over 90% field accuracy.
Project Objectives
- AI-Driven Contract Intelligence: Automate the extraction of master data, customer details, and key contractual terms using Generative AI—eliminating manual efforts and accelerating ERP readiness.
- Scalable Document Processing: Enable processing of thousands of diverse, unstructured contracts, invoices, and handwritten documents with consistent accuracy and speed.
- Improved Accuracy and Cost Efficiency: Reduce reliance on human intervention while increasing data precision, lowering operational costs, and minimizing errors during data migration.
- Discovery of Hidden Contractual Elements: Identify embedded or previously undocumented data—such as bill-to/ship-to addresses, pricing structures, and agreement clauses—that impact operations and compliance.
- Intelligent Contract Standardization: Leverage AI insights to recommend the best-matching contract templates for different customer segments, enhancing legal consistency and strategic alignment.
Project Highlights
- Rapid Extraction: Completed in a few weeks versus months of manual effort.
- Cost Reduction: Achieved at 10% of the cost compared to manual methods.
- High Precision: Delivered 92% accuracy across multiple revenue streams and document types.
- Scalable Architecture: AI pipeline enabled scalable handling of thousands of contracts.
- Uncovered Hidden Data: Identified fields and clauses previously undocumented or siloed in handwritten notes.
- Model Refinement with Prompt Engineering: Increased efficiency through guided AI interactions with structured feedback.
Results
- 92% accuracy in identifying and extracting structured contract fields, validated across five revenue streams.
- Cost savings, over $50K saved compared to projected manual effort for 2,000 contracts.
- 10x faster turnaround, with weeks instead of months required for extraction and validation.
- Automated detection of bill-to/ship-to discrepancies and clause mismatches.
- Actionable insights that supported customer segmentation and contract standardization.
- Structured outputs integrated seamlessly with Oracle ERP for master data upload.
- Intelligent Recommendations: AI suggested optimal contract templates by analysing customer types and business logic.
- Reduced Labor Dependency: Drastically reduced the need for human data entry and review.
Solution Architecture
How Trinamix Documantra Works
Trinamix Documantra is a smart tool that helps companies quickly and accurately extract important information from contracts, invoices, and other business documents — even when they’re in different formats, scanned, or handwritten.
It uses AI (Artificial Intelligence) to understand and organize data that would take weeks or months for humans to go through manually — and often with errors.
Here’s how it works, in simple terms:
- Reads Different Document Types: Whether it's a clean PDF, a scanned paper, or a photo of a handwritten page — Documantra can understand it.
- Finds Key Information Automatically: It looks for names, addresses, dates, amounts, and other important contract details — even if they’re hidden inside paragraphs.
- Fixes Human Problems: People make mistakes or miss things when reading documents. Documantra is trained to catch and extract accurate data quickly.
- Handles Messy Formats: Even if no two documents look the same, the system still finds what it needs.
- Fills in Gaps with Smart Suggestions: If something is missing, it can suggest likely answers based on patterns — helping business users not miss a thing.
- Saves Time & Cost: What would take months, and many people now takes just a few weeks — and for 10% of the cost.
Let’s take an example – Imagine you work for a real estate company that manages hundreds of rental properties. You’re switching to a new software system (like Oracle Cloud), and need to input all the contract details — like tenant names, rent amounts, lease terms, etc.
But here’s the challenge:
- The contracts are scattered — some with sales agents, some in drawers.
- Some are typed, others scanned, a few even handwritten.
- The wording is inconsistent — no two contracts are exactly alike.
- You don’t know where to find key customer details like billing address or payment terms.
What Usually Happens:
- A team of people spends months reading and typing data into spreadsheets.
- They miss things, make errors, or get confused by old formats.
- Your ERP project gets delayed, and costs rise.
How Trinamix Documantra Helps:
- It reads all the scanned and PDF files using OCR + AI.
- It extracts names, addresses, payment terms, and more — even if the info is spread across pages.
- It groups data by property, tenant, or contract type.
- It flags missing info and even suggests corrections.
- It presents everything in an organized Excel or system-friendly format — ready to upload.
The Outcome
You get your data:
- Faster
- Cheaper
- More accurately
- Without the stress of training or managing large teams
It’s not about doing more work — it’s about working smarter with Trinamix Documantra.
Proven Results – Step-by-Step Progress with Tangible Outcomes
10% – Executive Briefing
Introduction to AI capabilities and alignment with business needs.
20% – Technology Assessment
Hands-on validation using sample contract data.
30% – AI Trial
Pilot on 300 contracts with accuracy benchmarks.
50% – Production Rollout
Full-scale contract extraction for 2,000+ documents at ~$50K.
