Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Engineering • 28 Engineers

Case Study 13: Engineering Consultancy

Marketing-optimized case study for Canadian SMBs.

$112,000
Annual Savings
405%
ROI
3.3 months
Payback
Engineering • 28 Engineers
Industry Focus

Executive Summary

Technical Document RAG System: Searchable database of 18 years of technical reports, calculations, drawings, and standards documents. Engineers can ask natural language questions to find relevant precedents and methodologies.

Challenge

Solution

  • Technical Document RAG System: Searchable database of 18 years of technical reports, calculations, drawings, and standards documents. Engineers can ask natural language questions to find relevant precedents and methodologies.
  • Calculation Verification: AI reviews engineering calculations for common errors, unit mismatches, and code compliance. Flags potential issues for peer review.
  • Standards Compliance: Automated checking of designs against ASCE, ACI, AISC standards with citations and interpretation assistance.

Technical Stack

Key Metrics

6
Technical research time reduced from 6 hours to 45 minutes per project
64%
Calculation errors caught before peer review increased 64%
41%
Junior engineer productivity increased 41%
2.3
RFI response time improved from 2.3 days to 0.4 days
8%
Billable hours increased 8% firm-wide ($112k additional revenue)

Implementation Timeline

10 weeks including document digitization, system development, and engineer training

Ready to map your SMB workflow?

We can estimate ROI and scope the right MapleWorkSuite configuration for your team.

Start a Custom Case Study