Futura AI
it

Industry & Manufacturing

Manuals, bills of materials and technical knowledge concentrated in a few experts: here AI reduces search time and dependency on specific people.

Problems

  • Hundreds of technical manuals, bills of materials and quality procedures scattered across different formats
  • Long search times for technical information in production and technical support
  • Critical knowledge concentrated in a handful of expert technicians, at risk with turnover
  • Errors or downtime linked to technical information that is outdated or hard to find

Relevant systems

  • Document Intelligence over technical manuals and bills of materials
  • Enterprise Search across procedures, quality records and historical documentation
  • AI Agents as technical assistants for operators and support staff
  • AI Integration with existing MES and ERP systems

KPIs

  • Time spent searching for technical information
  • Reduction in downtime and errors linked to documentation
  • Training time for new operators
  • Share of technical documentation digitized and searchable

Related case study

IndustryVerified project

Automated extraction of dimensions from CAD drawings and ISO conformity checks

A precision mechanical components manufacturer receives technical CAD drawings in inconsistent formats and graphic standards across clients and suppliers. Reading dimensional data, tolerances and checking conformity against the applicable ISO standards was done manually by the engineering office: slow, repetitive work exposed to transcription errors, with direct impact on quoting and quality.

Analysis

Inventory of incoming drawing types, graphic formats in use and the ISO standards relevant to each product family. Identification of the critical dimensional fields (dimensions, tolerances, finishes) and of the points where a reading error has the greatest downstream impact, in quoting and in production.

Solution

An automated CAD drawing reading pipeline based on OCR and Vision-Language models, which extracts dimensions and tolerances directly from the technical drawing and checks them against the relevant ISO standard requirements, flagging deviations and low-confidence cases for review by the engineering office.

Architecture

Vision-Language models for interpreting the technical drawing, OCR for text and tables present on the sheet, a structured knowledge base of applicable ISO standards for automated comparison, and a review interface for human confirmation of low-confidence cases.

Implementation

Started on a subset of drawings and the most frequent ISO standards, validated accuracy with the engineering office against a sample of real drawings, calibrated the system on the errors found, and progressively extended to other product families.

Results

  • 86% accuracy in automatically extracting dimensional data from CAD drawings, measured on the client's real technical drawings
  • Quote preparation time cut from 4-5 person-hours to a few minutes, with automatic regulatory checks and access to centralized company knowledge
  • Fewer transcription errors on dimensions during quoting
  • More systematic ISO conformity checks, with uncertain cases flagged instead of missed in manual review

ROI: Value is measured in person-hours freed from quote preparation — from 4-5 hours down to a few minutes per quote — alongside lower risk of non-conformities caught late in production.

Client: Project delivered for Gruppo SAG. sagtubi.saggroup.com/en/