Manufacturing Use Case

Unlock BOM Optimization with AI

Reduce engineering time by 95% and cut material costs by 30%

Discover how Captivix helped a leading manufacturer streamline their Bill of Materials, reduce costs, and improve efficiency using cutting-edge AI technology.

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Navigating Complexities of BOM in Manufacturing

A leading industrial equipment manufacturer, known for delivering custom-built machinery, faced a recurring challenge: generating complex Bills of Materials (BOMs) for each order. With high variability and customization, the engineering team spent weeks manually creating accurate BOMs for every project.

Each order required 6–7 engineers and 2–4 weeks to finalize the BOM

Engineers had to assess part availability, vendor lead times, and cost feasibility—all manually

The process was labor-intensive, error-prone, and significantly impacted delivery timelines

BIM Bill of Materials

Component Assembly

Sub-Assembly A

Sub-Assembly B

Raw Materials

Fasteners & Hardware

Steps to Success

Captivix initiated the engagement with an AI Innovation Workshop, bringing together key stakeholders to identify pain points and opportunities. The BOM creation process stood out as a high-impact, automation-ready use case.

AI Innovation Workshop

We kicked off the engagement with a cross-functional AI Innovation Workshop involving engineering, IT, and operations teams. The goal was to align business challenges with AI opportunities.

Mapped the full lifecycle of BOM creation

Identified inefficiencies, manual dependencies, and data gaps

Evaluated AI readiness (data quality, systems, workflows)

Prioritized BOM optimization as the most impactful and feasible use case

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Data & Process Analysis

Our team conducted a deep dive into existing engineering workflows and data ecosystems to understand the full scope of BOM complexity.

Collected historical BOMs, vendor catalogs, and procurement data

Reviewed ERP integrations and engineering design tools

Identified variables influencing BOM decisions like lead times, part specs, and costs

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AI Model Design & Development

We selected a hybrid AI model architecture based on the complexity of the BOM structures, combining multiple AI techniques for optimal results.

Used Transformer-based NLP models (GPT, BERT) for text and spec parsing

Applied Graph Neural Networks (GNNs) to understand part dependencies

Introduced Reinforcement Learning (RL) for adaptive optimization of parts selection

Leveraged AutoML frameworks to accelerate model tuning and performance testing

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Proof of Concept (PoC) Execution

A prototype AI system was developed and integrated into the existing BOM toolchain. The AI-generated BOMs were reviewed by a senior engineer for validation, enabling a human-in-the-loop workflow that balanced automation with quality assurance.

Generated BOM drafts based on customer requirements and historical patterns

Pulled live data from vendor systems to optimize selections

Conducted multiple test cycles to validate speed, accuracy, and usability

Pilot Development

Integration & Scalability Planning

Following PoC success, Captivix designed a plan to scale the solution across the organization. This phase ensures long-term sustainability and continuous improvement.

Integration with broader ERP systems

Expansion to multiple product lines

Continuous learning loop to improve the AI engine with each order processed

Full Agentic AI Implementation

Significant Cost Reduction and Efficiency Gains

Our AI-driven BOM optimization solution delivered substantial results for the client. We achieved a 30% reduction in material costs, a 35% improvement in production efficiency, and a 15% decrease in time-to-market for new products. These improvements directly contributed to increased profitability and a stronger competitive position.

95%

Reduction in planning time

30%

Reduction in material costs

35%

Improvement in production efficiency

15%

Decrease in time-to-market

95% reduction in planning time

Improved accuracy and cost control

15% decrease in time-to-market

Frequently Asked Questions

Common questions about AI-driven BOM optimization

Success Stories

Real Results, Real Impact

See how leading companies have transformed their operations with ATLAS.

Featured Case Study

TechCorp

SaaS Company • 200+ employees

“ATLAS completely transformed our revenue operations. What used to take our team 40 hours per week now takes just 10. The AI handles all the repetitive follow-ups, data entry, and lead enrichment.”

75%

Less Admin Time

Meeting Bookings

$2M+

Pipeline Generated

Read Full Case Study

BuildRight Construction

Construction

Automated vendor follow-ups and RFQ tracking across all projects.

20 hrs

saved per week

Finova Group

FinTech

Enriched leads instantly and automated personalized outreach sequences.

pipeline velocity

MedHealth Solutions

Healthcare

Streamlined patient onboarding and reduced administrative overhead.

50%

faster onboarding

Client Reviews

What Our Clients Say

Hear directly from the leaders who've transformed their businesses with ATLAS.

“It feels like having an extra teammate that never gets tired. Our follow-up rate went from 40% to 95%. We’re closing deals we would have lost before.”

Sarah Johnson

VP Sales, TechCorp

“We stopped losing deals to slow follow-ups. ATLAS keeps every opportunity moving without us having to chase. Our team can focus on closing, not admin.”

Mike Rodriguez

CEO, BuildRight Construction

“The ROI was obvious within 30 days. We’re booking 3x more meetings with the same team size. ATLAS pays for itself many times over.”

Amanda Lee

Head of Growth, Finova Group

“We tried three other automation tools before ATLAS. Nothing else could handle our complex workflows. This is the real deal.”

James Park

COO, MedHealth Solutions

Ready to Optimize Your Manufacturing Operations?

Let's discuss how AI-powered BOM optimization can transform your engineering workflows and reduce costs.

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