Industry
Client Overview
A well-funded EV startup aiming to disrupt the commercial van market. Their core differentiator was a modular vehicle platform, but their small design and engineering team was struggling to keep pace with the aggressive product roadmap. They needed a way to rapidly explore and validate design options for vehicle components to reduce weight, maximize battery space, and lower production costs.
Client Testimonial
"CIS didn't just build us a tool; they changed how we design vehicles. The generative AI platform they developed allows our small team to punch way above our weight. We're now exploring design concepts that would have been impossible before, and we're doing it in days instead of months. This partnership has been fundamental to our speed and innovation." - Chief Technology Officer
Problem
The client's traditional CAD-based design process was too slow and linear. Each iteration of a component like a suspension bracket or battery enclosure took weeks of manual work. They needed a way to leverage AI to automate the exploration of the design space and find optimal solutions faster.
Key Challenges
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01
Integrating with Existing Tools : The solution needed to seamlessly integrate with their existing CAD and simulation software (e.g., CATIA, Ansys).
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Multi-Objective Optimization : The AI had to balance competing constraints: weight, strength, manufacturability, and cost.
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Intuitive User Interface : The tool had to be usable by their existing designers and engineers, who were not AI experts.
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Fast Iteration Speed : The platform had to deliver results quickly enough to be useful in their agile development sprints.
Our Solution
CIS's "AI/ML Rapid-Prototype Pod," in collaboration with our "CAD/CAM Drafting Pod," was tasked with building a custom generative design platform.
AI Core with Custom Algorithms : We developed a core AI engine using a combination of topology optimization algorithms and a generative adversarial network (GAN) trained on a library of existing engineering designs.
Natural Language & Sketch Input : We created an interface where an engineer could define constraints using natural language ("design a bracket to hold 500kg with a safety factor of 3, for CNC milling from 6061 aluminum") and provide a rough initial sketch.
Cloud-Based Parallel Processing : The platform was built on Azure and used parallel processing to generate and simulate hundreds of design variations simultaneously, providing the top 10-20 options to the engineer within hours.
Seamless CAD Export : The chosen design could be exported as a STEP file with a single click, ready for detailed refinement and final validation in their existing CAD software.
Implementation & Execution
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Workflow Discovery Sprint
Began with a 2-week "Design Sprint" to deeply understand the client's workflow and define the MVP.
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Core Algorithm Compilation
Developed the core AI engine and optimization algorithms.
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Interface MVP Construction
Built a simple web-based UI for the MVP.
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Automated API Validation
Integrated the platform with the client's Ansys simulation software via APIs for automated performance validation.
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Iterative Engineering Feedback
Worked with a small group of the client's engineers, iterating on the UI and features based on their weekly feedback.
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Handover & Training Delivery
Delivered the final platform and provided comprehensive training and documentation.
Positive Outcome
1. 60% Reduction in Design Cycle Time
The average time to get from initial requirements to a simulation-validated design for a new component dropped from 4 weeks to just over 1 week.
2. Average 15% Weight Reduction
The AI-generated designs were consistently lighter than the human-designed originals while maintaining or exceeding strength requirements, directly contributing to increased vehicle range.
3. Enabled Innovation
The platform freed up the client's senior engineers from tedious iterative work, allowing them to focus on higher-level system architecture and innovation.
4. Significant IP Generation
The client was able to file several patents on the novel component designs generated by the platform.
Why Choose Us
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Unwavering Process Maturity
Bakes comprehensive documentation into CMMI Level 5 processes to guarantee auditable compliance.
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Full-Spectrum AI Expertise
Deploys niche multi-domain specialists spanning computer vision, MLOps, and deep learning algorithms.
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Guaranteed IP & Data Security
Restricts access via isolated environments backed by secure, 100% in-house engineering teams.
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Flexible, On-Demand Scaling
Provisions adaptive, cross-functional engineering PODs that ramp up instantly based on scope.
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Proven Global Delivery
Leverages round-the-clock software engineering workflows designed for seamless cross-border collaboration.
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Deep Automotive Domain Context
Operates with native knowledge of safety-critical embedded systems, vehicle networks, and compliance.
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Risk-Free Engagement Path
Validates engineering capabilities upfront through 2-week paid trials and scoped pilot proofs.
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Zero-Cost Talent Replacement
Mitigates risk with an immediate resource substitution policy featuring fully subsidized knowledge transfers.
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A True Technology Partner
Consults continuously on technical architecture, platform future-proofing, and executive alignment strategies.
Conclusion
This case study highlights our ability to apply cutting-edge AI, like generative design, to solve practical engineering problems. We provided a startup with a force-multiplying tool that leveled the playing field, enabling them to innovate faster and more effectively than much larger competitors.