AI Document Processing for Construction Teams Leads to 50% Faster Document Retrieval
An AI-powered document processing solution for construction and facility operations that enables teams to quickly find, interpret, and use the information hidden across thousands of technical documents.
Industry: Construction
Service: Product Discovery, Digital Product Development, AI/ML Implementation and Integration
Region: Europe
Project Highlights
- Built an AI copilot for construction and facility documentation
- Delivered a semantic search engine capable of indexing and retrieving over 1.2M+ documents
- Added a conversational AI interface for natural-language access to technical files
- Automated summarization and accelerated information retrieval, reducing knowledge silos
About the Client
The client is a global provider of digital asset management solutions for large construction and facility operations. Their platform centralizes tens of thousands of documents per project, serving teams across Europe and beyond. Critical project knowledge was stored, but increasingly difficult to retrieve. To stay competitive and support enterprise clients, the company needed a new, AI-driven approach to document intelligence.
The company turned to 8allocate to build an AI powered document processing solution that helps users quickly find the right documents, understand their content, and eliminate time-consuming manual search.
Challenges and Objectives
The company had to solve three major challenges:
- Enable fast, accurate retrieval across 1.2M+ construction documents
- Automate the interpretation and summarization of large technical documents
- Break down knowledge silos and provide an AI for document processing
Technologies We Use
Solution Delivered
8allocate delivered an AI document processing solution integrated into the client’s digital asset platform, combining search, summarization, and business logic in one unified experience.
- AI Search Layer with Azure Cognitive Search + Azure OpenAI: Implemented a semantic search engine that indexes document content, metadata, relationships, visual text extracted from PDFs, and terminology variations. Users can now find documents even when they don’t know correct filenames or terminology.
- Implemented Conversational AI Interface: Built with Azure OpenAI GPT, the interface allows users to ask natural-language questions and instantly retrieve the right documents or answers. Follow-up queries refine results without restarting the search, eliminating the need to browse folders or interpret inconsistent file names.
- Automated Summarization and Accelerated Information Access: Introduced an automated summarization pipeline generating consistent previews for new uploads within two minutes. This removes the need to open and skim lengthy PDFs, drawings, or manuals. The pipeline supports all major document types, reducing time spent on document review.
Results Obtained
Automated Data Processing
The AI Copilot generated concise summaries for drawings and technical documents, significantly reducing manual review effort.
Enhanced Data Availability
By applying AI-driven cognitive search, the solution increased the number of accessible documents by 15%, resolving terminology inconsistencies and eliminating information silos.
Increased Accuracy and Efficiency
Time spent searching for information decreased by 50%, while search interactions dropped by 30%. Teams relied far less on manual spreadsheet workflows.
Improved User Experience
By removing common pain points in document handling, the platform enabled smoother project workflows and reduced delays. Workflow satisfaction increased from 3.6 → 4.5, and 92% of users reported they “can find what they need faster.”
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How to automate document processing with AI?
To automate document processing with AI, your system ingests large volumes of unstructured documents and uses AI models to understand their content, classify them, and extract the key information. The AI then turns this content into searchable, structured knowledge that flows directly into your enterprise tools. AI powered document processing removes the need for manual review, reduces errors, and makes the right information available instantly when teams need it.
What is AI document processing?
AI document processing is the use of artificial intelligence technologies to pull information out of documents automatically, such as invoices, contracts, forms, emails, all the stuff people normally have to type in by hand. Instead of someone reading line by line, AI can extract the key details, sort them, and send the data where it needs to go. It reduces manual data entry, accelerates workflows, and improves accuracy by leveraging AI capabilities like natural language processing (NLP), computer vision, and machine learning.
How can I use AI to automate document processing?
To automate document processing with AI, you can follow a simple flow:
- Digitize documents. Scan paper files or pull in digital ones so everything starts in a clean, readable format.
- Apply AI models. Use NLP, computer vision, and machine learning to pull out key fields, understand the document type, and interpret the content.
- Integrate your systems. Send the extracted data straight into the tools you already use (e.g., ERP, CRM, or database) without manual typing.
- Automate workflows. Set rules so the data triggers the right actions, like approvals, alerts, or updates.
- Keep improving. Refine the AI with new examples over time so accuracy goes up and it handles more document types.
How does AI enable automated document processing?
AI enables automated document processing by using NLP, machine learning, and computer vision to understand and extract information from all kinds of documents both structured and unstructured. Unlike traditional rule-based systems, AI adapts to diverse document formats and languages, recognizing patterns and key information without extensive manual configuration.