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Case Studies

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Reimagining FDS document generation for industrial automation

Reimagining FDS document generation for industrial automation

How a major industrial automation company cut document time from 60 hours to 30 minutes

How a major industrial automation company cut document time from 60 hours to 30 minutes

60 hours to 30 minutes document generation time

Improved FDS consistency and accuracy

Engineering teams freed for higher-value work

The challenge

The challenge

Manual FDS generation slows down project timelines and strains engineering teams

Manual FDS generation slows down project timelines and strains engineering teams

A major industrial automation company relied on manual processes to generate Functional Design Specification documents for energy sector projects. These documents often exceeded 200 pages, pulling from unstructured sources like historical FDS files, bills of materials, technical proposals, and product manuals. The process took over 60 hours per document, causing delays, inconsistencies, and significant strain on engineering resources.

Key challenges

  • Documents exceeding 200 pages with complex, unstructured data

  • Data pulled from multiple inconsistent sources

  • High error and inconsistency risk from manual processing

  • Over 60 hours spent per document

  • Project delays and rising resource costs

Challenge diagram with FDS generation at the center connected to five pain points

The solution

Gen AI-powered platform to automate FDS document generation

Gen AI-powered platform to automate FDS document generation

Intelligent data extraction

Azure Document Intelligence for data extraction

OCR for capturing tables, images, and text

Processes Excel files, BoMs, PDFs, and proposals

Data indexed in Azure AI Search for fast retrieval

Scalable document building

Semantic matching for contextually accurate content

GPT-4 refines and validates each document section

Multi-stage processing with content iteration

Auto-generates final FDS in formatted Word output

Implementation approach

Implementation approach

1

Data extraction

  • Azure Blob Storage and SQL as source systems

  • OCR and document processing models

  • Structured and unstructured data handling

2

FDS generation

  • Semantic retrieval from indexed data

  • GPT-4 for content refinement and validation

  • Real-time UI feedback and file access

The impact

The impact

Faster, smarter document generation at scale

Faster, smarter document generation at scale

Speed

  • Generation time cut from 60 hours to 30 minutes

  • Faster project timelines

  • Quicker turnaround on client deliverables

Consistency

  • Reduced errors across FDS sections

  • Standardized output quality

  • Minimized manual inconsistencies

Scalability

  • Higher FDS volume without added headcount

  • Handles complex, multi-source documents

  • Built to expand across regions and business units

Engineering productivity

  • Teams freed from repetitive document work

  • More time for client-specific iterations

  • Focus shifted to higher-value tasks

Future readiness

  • Phase 2 to handle new file formats and FDS scenarios

  • Custom models in development for all document types

  • Roadmap includes flowchart extraction and system integration

Transform your document workflows

All rights reserved © 2026 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park, Oberoi Garden City,
Off W. E. Highway Goregaon (E), Mumbai - 400063, Maharashtra, India.

CIN : L72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8

All rights reserved © 2026 Fractal Analytics Inc.

Registered Office:

Level 7, Commerz II, International Business Park,
Oberoi Garden City, Off W. E. Highway Goregaon (E),
Mumbai - 400063, Maharashtra, India.

CIN : L72400MH2000PLC125369

GST Number (Maharashtra) : 27AAACF4502D1Z8