Engineers evaluating SOLIDWORKS AI face a gap between vendor demos and production reality. Many features shown at conferences remain in beta or tied to platform upgrades. Desktop users often discover that headline capabilities require cloud subscriptions or 3DEXPERIENCE migrations. The gap matters because procurement decisions made on roadmap promises can leave teams without the tools they expected for months or years.
Setting Expectations for CAD AI in 2025: What’s Shipping vs. What’s Still a Demo
Most announced AI features for SOLIDWORKS are not fully available. AURA’s generative assembly tools remain in beta. Design Assistant’s advanced modeling predictions work only in SOLIDWORKS Cloud. Desktop SOLIDWORKS users receive older machine learning helpers like Command Predictor and FeatureXpert, not the conversational copilots shown on stage. Vendors use AI announcements to drive platform migrations, not to deliver immediate value to existing desktop workflows.
The Shift in Value: Biggest Gains Are Knowledge Access, Part Search and Reuse, and Documentation—Not Raw Geometry Creation
Engineers spend more time searching for past designs, answering technical questions, and documenting decisions than drawing geometry. AI delivers measurable ROI in part reuse (reducing custom work by 32% in Leo AI deployments), technical Q&A (cutting search time from hours to minutes), and documentation (auto-generating BOMs and statements of work). Geometry generation remains a niche use case, often producing meshes that require manual cleanup rather than production-ready parametric models.
How to Evaluate Engineering Copilots for Enterprise Security, PLM Integration, and Real Availability
Choosing an AI copilot requires assessing availability, workflow fit, security posture, and enterprise readiness. Teams need tools that ship today, integrate with existing CAD and PLM systems, protect IP, and scale across distributed engineering groups. The evaluation checklist below separates production-ready platforms from roadmap promises.
Availability and Maturity: Shipping Features, Roadmap Transparency, Vendor Support SLAs
Ask vendors which features are generally available versus beta. Request customer references using those features in production. Confirm support SLAs, incident response times, and escalation paths. Leo AI ships with 60,000 engineers in production at HP, Scania, Intel, and Mobileye. SOLIDWORKS Design Assistant is GA in SOLIDWORKS Cloud but limited on desktop. AURA remains beta for 3DEXPERIENCE commercial users. Onshape AI Advisor is GA for all Onshape plans including free tiers.
Workflow Fit: Desktop SOLIDWORKS, 3DEXPERIENCE Cloud, and Onshape—Where Each AI Assistant Actually Runs
Most SOLIDWORKS users run desktop licenses, not cloud or 3DEXPERIENCE. Design Assistant and AURA require cloud connectivity, locking out desktop workflows. Leo AI is platform-agnostic and works alongside desktop SOLIDWORKS, PDM, and PLM systems. Onshape AI Advisor runs only in Onshape SaaS. Evaluate where your team actually works, not where vendors want you to migrate.
Security and Compliance: SOC 2 and GDPR Compliance, Data Residency, SSO, Audit Logging
Enterprise engineering teams need SOC 2 Type II certification, GDPR compliance, and zero training on customer data. Leo AI meets these standards. Ask vendors whether your CAD files and metadata train their models. Confirm data residency options, SSO integration (SAML, OAuth), role-based access controls, and audit logs for IP protection. Cloud-only tools often lack granular data isolation or customer-managed encryption keys.
Enterprise Readiness: Admin Controls, IP Protections, Procurement-Readiness, Pricing/TCO
Enterprise deployments require admin dashboards for user provisioning, usage analytics, policy enforcement, and license management. Confirm IP ownership and indemnification clauses in vendor contracts. Evaluate total cost of ownership including licensing, training, integration, and platform migration costs. Platform-locked tools force infrastructure changes that multiply TCO beyond subscription fees. Leo AI integrates via API and connectors without requiring CAD/PLM replacement.
Desktop vs. Cloud: Features and the 3DEXPERIENCE Lock-In Reality
Dassault uses AI features to push SOLIDWORKS users toward 3DEXPERIENCE subscriptions. Understanding what desktop users receive versus cloud-exclusive capabilities helps teams avoid surprises during procurement. The platform gap affects collaboration, licensing costs, and long-term flexibility.
What Desktop SOLIDWORKS Users Get Today vs. SOLIDWORKS Cloud/3DEXPERIENCE Features
Desktop SOLIDWORKS includes Command Predictor, Fastener Recognition, and Xpert tools (SketchXpert, FeatureXpert). These are legacy machine learning helpers, not conversational AI copilots. SOLIDWORKS Cloud users gain Design Assistant (Selection Helper, Sketch Helper, Mate Helper, Smart Mate). AURA and advanced generative features require 3DEXPERIENCE platform subscriptions. Desktop users do not have access to conversational AI, generative assembly, or auto-documentation features shown in marketing.
Implications for Licenses, PDM/PLM Integration, and Cross-Team Collaboration When Adopting CAD AI
Migrating to 3DEXPERIENCE or SOLIDWORKS Cloud requires new licenses, PDM/PLM integration work, and retraining. Desktop PDM vaults do not sync with cloud collaboration workflows. Teams with distributed desktop workflows face friction when cloud-only AI features are unavailable to half the engineering organization. Platform-agnostic tools like Leo AI avoid this gap by working alongside existing desktop, PDM, and PLM systems without requiring infrastructure changes.
Best SOLIDWORKS AI Copilots Compared: Leo AI, SOLIDWORKS Design Assistant, 3DEXPERIENCE AURA, and Onshape AI Advisor
Four AI assistants serve SOLIDWORKS users and adjacent CAD platforms. Each addresses different workflows, availability constraints, and enterprise requirements. The comparison below clarifies what each tool delivers today, not what roadmaps promise.
Leo AI (Platform-Agnostic, Production-Ready, Widely Adopted)
Leo AI is an engineering copilot built on a proprietary Large Mechanical Model trained on mechanical parts, assemblies, and engineering logic. It understands CAD context without replacing your CAD software. Leo integrates with SOLIDWORKS desktop, PDM, PLM systems, and 120 million vendor parts catalogs. It is SOC 2 certified, GDPR compliant, and in production at HP, Scania, Intel, Mobileye, and 60,000 engineers globally.
Capabilities and Workflow Fit: Technical Q&A, Part Search and Reuse, Calculations, Concept Generation, Documentation Across Toolchains
Leo answers technical questions grounded in 1 million verified engineering sources (books, standards, datasheets). It finds parts from your PLM and external catalogs using natural language (“find stainless steel bracket similar to X project”). It runs engineering calculations with full traceability and exports to Excel. It generates 3D mesh concepts and 2D sketches from text, specs, or hand-drawn sketches. It auto-generates BOMs, statements of work, and manufacturing method documents.
Limitations and Availability: Outputs 3D Meshes (Not Native SOLIDWORKS Files); Enterprise Features and Connectors; Licensing
Leo generates 3D mesh concepts, not native SOLIDWORKS parametric files. Meshes require import and refinement in your CAD tool. Leo is available now via direct purchase and value-added resellers in US, UK, India, France, Germany, Poland, Benelux, and Israel. It deploys via API and connectors without forcing CAD or PLM migration. Licensing is per-seat subscription with enterprise volume pricing available.
SOLIDWORKS Design Assistant (Speeds Selection/Sketch/Mates in SOLIDWORKS Cloud)
Design Assistant is an AI and machine learning toolset built into browser-based SOLIDWORKS Cloud. It learns from individual design habits and offers real-time suggestions for selections, mates, and sketching. The tool is useful for accelerating repetitive modeling tasks but limited to cloud workflows.
Capabilities and Workflow Fit: Modeling Assistance for Selections, Sketch Intent, Mates; Integrated in SOLIDWORKS Cloud
Selection Helper predicts which edges, faces, or bodies you will select next. Sketch Helper analyzes sketch entities and suggests additional instances with dimensions and relations. Mate Helper suggests locations for replication when inserting components. Smart Mate creates fully constrained mates automatically. These features learn your patterns and improve over time.
Limitations and Availability: Desktop Users Receive Partial, Older ML Features; Tied to 3DEXPERIENCE Subscriptions
Design Assistant only works in SOLIDWORKS Cloud, not desktop SOLIDWORKS. Desktop users receive older ML tools (Command Predictor, Fastener Recognition, Xpert helpers) that do not offer conversational or contextual assistance. Full Design Assistant features require SOLIDWORKS Cloud or 3DEXPERIENCE subscriptions, which most desktop SOLIDWORKS users do not have.
3DEXPERIENCE AURA (Beta; Help/Documentation-Centric Today)
AURA was announced at 3DEXPERIENCE World 2025 as a conversational AI companion for design help, task automation, and generative suggestions. It launched in beta for 3DEXPERIENCE commercial users in July 2025. Early user feedback indicates limited functionality compared to demo promises.
Capabilities and Workflow Fit: Knowledge Search, Contextual Help; Early Steps Toward a 3DEX Assistant
AURA answers questions about SOLIDWORKS features and workflows. It summarizes 3DSwym community posts. It provides contextual help within the 3DEXPERIENCE platform. Demos showed generative assembly creation and marketing renders from text, but these features are not yet available.
Limitations and Availability: Many Generative Features Pending; Tied to 3DEX Lock-In; Current Scope Is Guidance, Not Geometry
AURA remains in beta. Generative assembly and design automation features shown in demos are not yet shipping. It requires 3DEXPERIENCE platform subscriptions, which desktop SOLIDWORKS users do not have. Current capabilities focus on help and documentation, not geometry generation or CAD automation. One user on SOLIDWORKS forums noted: “Can’t say I’m terribly impressed with the answer to my first question.”
Onshape AI Advisor (Learning Assistant; Onboarding and Best-Practice Guidance)
Onshape AI Advisor is a learning assistant built on Onshape’s educational content library. It uses Amazon Bedrock to answer questions about Onshape workflows and best practices. It does not generate geometry or understand your designs. It is available to all Onshape users including free and educational plans.
Capabilities and Workflow Fit: Explains Features, Suggests Best Practices; Good for Training and Mechanical Engineering AI Onboarding
AI Advisor answers questions about Onshape features and workflows. It provides guidance on best practices for sheet metal, surfacing, and assemblies. It helps users discover features they did not know existed. It cites sources and links to official documentation. Jon Hirschtick (Onshape founder, PTC chief evangelist) said: “We’re giving much better results than you get if you ask these same questions to ChatGPT.”
Limitations and Availability: Doesn’t Generate Geometry or Understand Your Design Context; SaaS-Only
AI Advisor does not understand your designs, run calculations, or generate geometry. It is a sophisticated help system, not an engineering copilot. It works only in Onshape SaaS. It is best for teams adopting Onshape who want to accelerate onboarding and reduce learning curves.
Practical Uses of CAD AI Today for SOLIDWORKS Teams
AI delivers measurable value in knowledge access, part reuse, calculations, concept exploration, and documentation. These use cases address real bottlenecks in engineering workflows. They do not require abandoning existing CAD or PLM systems.
Part Search and Reuse: Find Existing Components Fast, Reduce Custom Work and Inventory
Engineers waste hours searching PDM vaults and vendor catalogs for parts. AI copilots like Leo enable natural language part search (“find metric M6 socket head cap screw, stainless steel, used in X project”). This reduces custom part creation by 32% and cuts inventory costs. Faster part search also shortens design cycles and improves standardization.
Technical Q&A and Onboarding: Faster Answers to Modeling Questions and Standards, Across Versions
New engineers and contractors spend days searching manuals, forums, and tribal knowledge. AI copilots trained on engineering sources answer questions in seconds with citations. This accelerates onboarding, reduces reliance on senior engineers for routine questions, and ensures consistent application of standards across distributed teams.
Calculations and Engineering Math: Quick Checks, Unit Conversions, Tolerance Stacks in Context
Engineers run repetitive calculations for stress, thermal expansion, tolerance stacks, and unit conversions. AI copilots perform these calculations with full traceability to trusted sources and export results to Excel. This eliminates spreadsheet errors and speeds design validation without requiring separate calculation tools.
Concept Generation and Generative Design Concepts: Idea Exploration and Mesh Previews, Not Final Parametric Models
AI copilots generate 3D mesh concepts from text descriptions, specs, or hand-drawn sketches. These meshes serve as starting points for CAD work, not final production geometry. They help engineers visualize ideas quickly and explore design alternatives before committing to parametric modeling. Meshes require import and refinement in CAD tools.
Documentation Acceleration: Design Rationales, BOM Notes, ECO Summaries, Meeting Minutes
Engineers spend hours writing BOMs, statements of work, manufacturing method documents, and ECO summaries. AI copilots auto-generate these documents from CAD metadata, meeting notes, and project context. This frees engineers to focus on design work and ensures documentation stays current with design changes.
Security and Compliance for Engineering Copilots
Engineering teams handle proprietary designs, customer data, and IP that must remain protected. AI copilots introduce new risks if they train on your data, lack audit logs, or expose files to third-party subprocessors. The checklist below ensures enterprise-grade security and compliance.
Security Checklist: SOC 2 and GDPR Compliance, Data Isolation, Customer-Managed Keys, IP Protection, Retention Policies
Confirm SOC 2 Type II certification and GDPR compliance. Verify zero training on customer data. Ensure data isolation per tenant with no cross-tenant leakage. Request customer-managed encryption keys for data at rest. Review IP ownership clauses in vendor contracts. Confirm data retention and deletion policies including right to erasure. Check for penetration testing, vulnerability disclosure programs, and incident response SLAs.
Questions to Ask Vendors: Training on Your Data, Opt-Out Controls, Model Boundaries, Incident Response, Third-Party Subprocessor List
Ask: Does your AI train on my CAD files, prompts, or metadata? Can I opt out of training? What model boundaries prevent IP leakage? What is your incident response time for security breaches? Who are your third-party subprocessors and where do they store data? What audit logs and access controls are available? These questions expose vendors who lack enterprise security posture.
Alternatives to Platform-Locked Tools and Getting Started Without Migrating Your Entire Toolchain
Platform-locked AI tools force infrastructure migrations, new licenses, and retraining. Platform-agnostic tools work alongside existing CAD, PDM, and PLM systems. Teams can pilot AI copilots without disrupting production workflows or committing to multi-year platform migrations.
Platform-Agnostic Approach: Choose Tools That Work Across SOLIDWORKS Desktop, PDM/PLM, and Other Engineering Systems
Leo AI integrates with desktop SOLIDWORKS, PDM, PLM, and vendor catalogs via API and connectors. It does not require cloud migration or 3DEXPERIENCE subscriptions. This approach preserves existing workflows, licenses, and integrations while adding AI capabilities. Teams avoid vendor lock-in and maintain flexibility to change CAD or PLM systems without losing AI investments.
Getting Started: Pilot Add-On Copilots Alongside Existing CAD/PLM, Use Connectors and APIs, Avoid Forced 3DEXPERIENCE Migrations
Start with a 30-day pilot of platform-agnostic AI copilots. Test part search, technical Q&A, and documentation use cases with a small team. Confirm API and connector compatibility with your PDM and PLM systems. Measure time saved, part reuse rate, and user adoption. Avoid vendors who require CAD or PLM migration as a prerequisite for AI features.
ROI and Pilot Plan for SOLIDWORKS AI
AI copilot ROI is measurable in search time saved, part reuse, documentation throughput, onboarding speed, and defect reduction. A structured pilot plan with clear metrics ensures teams choose tools that deliver value, not just demo well.
ROI Model and Success Metrics: Search Time Saved, Part Reuse Rate, Documentation Throughput, Onboarding Speed, Defect Reduction
Track hours saved per engineer per week on part search, technical Q&A, and documentation. Measure part reuse rate before and after AI deployment. Count design errors caught by AI-assisted design reviews. Calculate onboarding time for new engineers using AI assistants. Leo AI deployments show 5-7 hours saved per engineer per week, 32% increase in part reuse, and 34% reduction in design errors.
30-60-90 Day Pilot Plan and Pitfalls: Secure Data Setup, PLM Integration Checks, Change Management, Avoiding “Demo-Only” Features
Day 0-30: Secure data setup with IP protection, SSO, and audit logs. Confirm API and connector compatibility with PDM and PLM. Select pilot team and use cases (part search, technical Q&A, documentation). Day 30-60: Deploy to pilot team, track metrics, gather feedback. Test PLM integration and part search accuracy. Day 60-90: Expand to broader team, measure ROI, refine workflows. Avoid vendors who require platform migration or who demo features not yet GA.
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