How Semor.ai Replaced Manual Document Review With AI-Powered Engineering Intelligence
Manufacturing engineers were spending hours reading specifications page by page. easy.bi built the AI microservice and chatbot behind Semor.ai - a system that analyzes engineering documents, generates drafts, flags contradictions, and delivers enterprise search across technical documentation.
The Challenge: Engineers Drowning in Documentation
In manufacturing, every machine and component comes with documentation - specifications, requirements, compliance documents, maintenance manuals, safety protocols. For a single production line, that can mean thousands of pages across hundreds of documents. And before any engineering decision can be made, someone has to read them.
That someone is usually a senior engineer. The person with the most valuable technical judgment in the organization spends a significant portion of their week doing what amounts to a manual search engine: reading through documents page by page, looking for specific requirements, cross-referencing specifications between components, and checking whether Document A contradicts Document B.
This manual review process creates three problems. First, it's slow - engineering decisions that could take minutes with the right information take hours or days because the information is buried in PDFs. Second, it's error-prone - humans miss contradictions, especially across documents they read hours or days apart. Third, it doesn't scale - as production complexity grows, the documentation volume grows faster than the engineering team.
Semor.ai had the vision for an AI-powered solution. They needed a development partner who could turn that vision into a production-ready system that manufacturing engineers would actually use.
“Our engineers were spending hours reading specs page by page. Now they ask a question and get the answer with the source document cited. That's a fundamental shift in how we work.”
Why Semor.ai Chose easy.bi
Semor.ai's concept required more than AI expertise - it required building a complete product around the AI. That meant a document upload and processing pipeline, an enterprise search interface, a chatbot for natural-language queries, and an Angular frontend that manufacturing engineers (not tech workers) would find intuitive.
easy.bi was selected because the team could own the full product development: the AI microservice architecture, the frontend application, the Oracle database layer, and the integration work connecting them. Semor.ai brought the domain expertise and AI strategy; easy.bi brought the engineering capacity to ship working software incrementally.
“easy.bi didn't just build the AI - they built the product around it. The upload pipeline, the search interface, the chatbot. The AI is powerful, but the product makes it usable.”
The Approach: Building an AI Assistant for the Factory Floor
Document analysis microservice. The core of the system is a microservice that processes uploaded engineering documents. When an engineer uploads a specification or requirements document, the system analyzes its content, extracts structured data, identifies key requirements, and makes everything searchable. The microservice handles multiple document formats and normalizes the content into a consistent model for downstream analysis.
Contradiction detection across documents. One of the highest-value features is automated contradiction detection. When a new document is uploaded, the system cross-references its requirements against existing documents in the system. If Specification A says a component must withstand 200°C and Specification B says 150°C, the system flags it immediately - something a human reviewer might miss if they read the documents days apart.
Enterprise search with natural-language queries. The enterprise search interface lets engineers ask questions in plain language: "What are the temperature requirements for Component X?" or "Which documents reference the hydraulic system in Line 3?" The system returns relevant passages, source documents, and confidence scores - turning hours of manual searching into seconds of query-response interaction.
Draft generation from existing documentation. Engineers frequently need to create new documents that draw from existing specifications. The system can generate draft documents based on existing content - compiling relevant requirements, specifications, and standards from across the document library into a structured first draft that engineers then review and refine.
Angular frontend designed for engineers. The user interface was built in Angular with a focus on the workflows manufacturing engineers actually perform. Document upload is drag-and-drop. Search results highlight relevant passages within their source context. The chatbot interface supports file attachments alongside text queries. Every interaction was designed to feel faster than the manual alternative.
“Contradiction detection alone justified the platform. We found specification conflicts that had been sitting in our documentation for years, undetected.”
The Results: Engineering Decisions Backed by Complete Information
The Semor.ai platform transformed how engineers interact with technical documentation. Instead of reading documents sequentially, they query the system and get answers in seconds. Contradiction detection catches conflicts that manual review would miss. Draft generation accelerates document creation by compiling relevant source material automatically.
For manufacturing organizations using the platform, the impact is measured in engineering hours recovered. Senior engineers who previously spent substantial time on document review now redirect that time to engineering judgment - the work that actually requires their expertise. The AI handles the information retrieval; the engineer handles the decision-making.
The ongoing partnership between Semor.ai and easy.bi continues to expand the platform's capabilities. Each release adds new analysis features, improves search accuracy, and extends the types of engineering documents the system can process.
“The draft generation feature saves us days on document creation. It pulls the right requirements from the right sources - we just review and approve.”
Key Takeaways
- AI is the engine, but the product is the car. The AI analysis capabilities are powerful, but they only create value when wrapped in a product that fits engineering workflows. Upload, search, chat, and draft generation are the interfaces that make AI accessible.
- Contradiction detection is the killer feature. Manual reviewers miss cross-document conflicts because they process documents serially. Automated cross-referencing catches what humans cannot - and the cost of a missed contradiction in manufacturing can be enormous.
- Design for the actual user, not the tech enthusiast. Manufacturing engineers are not AI researchers. The Angular frontend was designed for their workflows, their vocabulary, and their expectations. If the AI feels like using a search engine, adoption follows naturally.
- Incremental delivery proves the concept faster. Rather than building the complete platform before launch, easy.bi delivered the document analysis and search features first, then added contradiction detection and draft generation in subsequent releases. Early user feedback shaped later features.
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