AI tools for engineering design compared.

Every software vendor now has "AI" on their website. For heads of engineering that makes the choice harder, not easier. Behind the same label sit completely different tools: geometry search, drawing checks, cost calculation, enterprise search.

Anyone looking for an AI assistant for engineering design therefore ends up comparing apples with oranges. And buys a tool that solves a problem they never had.

This comparison sorts six solutions by what they were actually built for. Not a ranking from 1 to 6, but an answer to one question: which tool fits which job?

What we compare against

An AI assistant for engineering design has to stand up to five questions:

1. Purpose: what problem does the tool solve at its core? Finding parts, finding knowledge, checking drawings or calculating cost?
2. Data access: does the tool reach the data where it actually sits? PDM, ERP, file servers, SharePoint, old project folders?
3. Understanding technical content: does it read drawings, standards and geometry, or only running text?
4. Traceability: does it show sources, so engineers can verify an answer?
5. Data protection and hosting: where does the data sit? Is it used for training?

In engineering it does not matter whether an AI sounds clever. It matters whether you can check its answer against the source.

The six tools at a glance

1. KoAssist: the AI platform for engineering design

KoAssist is an AI assistant for engineering departments in DACH machine building. It makes technical knowledge searchable that today sits scattered across file servers, PDM, old projects and the heads of experienced colleagues.

What KoAssist does:

• Knowledge assistant: answers questions about documentation, standards, projects and drawings with a direct source reference. Processing is multimodal, so scans, drawings and images are covered too.
• Drawing check (in beta with customers): automatically checks technical drawings for completeness, consistency and compliance with the company's own design guidelines.
• Similar-part search (early access on request): aims to make existing components findable via the drawing before a part is designed a second time.
• Data protection: hosted in Germany, AI models in European data centres, permissions at room level.

Limits: generative CAD, meaning 3D models created from a prompt, is not part of KoAssist. Nor does KoAssist bring its own catalogue of manufacturer parts. The focus is on finding the knowledge that already exists in your own company.

A fit when: your engineering knowledge is spread across many systems, you want knowledge search and drawing checks in one tool and data residency in Germany matters.

Never search for the same answer twice.

More on this: knowledge assistant, drawing check and similar-part search.

2. Leo AI: the AI copilot from the USA

Leo AI was founded in 2023 and positions itself as an AI built specifically for mechanical engineers. The tool combines its own engineering knowledge base with company data.

Strengths:

• According to the vendor, answers draw on more than a million engineering sources such as standards, textbooks and datasheets, each with a source reference.
• Integrations with common PDM and PLM systems, including SOLIDWORKS PDM, PTC Windchill, Siemens Teamcenter and Onshape.
• Part search in your own PLM and in vendor catalogs, plus engineering calculations.
• SOC 2 Type II certified, processing in line with GDPR principles, no training on customer data in the Business and Enterprise plans according to the vendor.

Limits: Leo is a US vendor focused on the international market. Anyone who requires data to stay exclusively in the EU or Germany should examine the hosting model in detail.

A fit when: you operate internationally, run a large PDM/PLM system and value a broad external engineering knowledge base.

Full single comparison: KoAssist and Leo AI

3. CADENAS: the standard in parts management

CADENAS of Augsburg has been established in strategic parts management for decades. The parts management product is called PARTsolutions; its new web version is Enterprise 3Dfindit.

Strengths:

• The geometric similarity search GEOsearch compares components by their CAD geometry and returns a ranked list of the most similar parts.
• Access to more than 700 manufacturer-certified catalogues of standard and purchased parts.
• According to the vendor, 154 of the top 1,000 German world market leaders rely on PARTsolutions.

Limits: the focus is on parts and catalogues. For questions aimed at unstructured knowledge such as project reports, lessons learned or internal guidelines, CADENAS is not the tool.

A fit when: part variety, duplicates and standard or purchased parts are your main problem and you want to build strategic parts management.

Full single comparison: KoAssist and CADENAS

4. simus classmate: master data, classification and cost

simus systems of Karlsruhe, founded in 2002, specialises in the automatic classification of CAD models, cleaning up master data and cost calculation.

Strengths:

• Finds existing parts via geometric similarity search, including search for sections of models.
• Calculates manufacturing cost while the design is still being made.
• With classmate DRAW, an AI reads technical drawings and assigns attributes such as tolerances and fits to the 3D model.
• Integration into common CAD, PLM and ERP systems such as SAP.

Limits: simus mainly solves problems with structured data. A chat assistant answering questions about documents and project knowledge is not the core of the product.

A fit when: your master data is untidy, you want to build a classification, or cost transparency during design is the goal.

Many AI projects in engineering do not fail because of the AI. They fail because of data nobody ever cleaned up.

Full single comparison: KoAssist and simus classmate

5. CoLab: AI for design reviews

CoLab was founded in 2017 by mechanical engineers and specialises in the design review process.

Strengths:

• AutoReview works as an AI peer checker: it tests 2D drawings and 3D models against your standards and guidelines and marks issues directly in the model.
• A lessons-learned agent finds similar earlier designs and the findings from their reviews.
• CAD models can be reviewed together in the browser, including with suppliers or customers who have no CAD licence of their own.

Limits: CoLab is built around the review workflow. It is not intended as a general knowledge search across all company data.

A fit when: your reviews are slow, feedback gets lost in emails and slide decks, and you want to standardise checks.

Full single comparison: KoAssist and CoLab

6. amberSearch: the company AI for mid-sized firms

amberSearch, now also appearing as amber, is a German business AI platform. It combines AI search, a company assistant and AI agents.

Strengths:

• Connects more than 70 data sources such as Microsoft 365, SharePoint, DMS, CRM and network drives, without moving the data.
• Inherits existing access rights, answers carry source references.
• GDPR compliant, ISO 27001, AI models hosted in Europe.
• References in machine building as well.

Limits: amberSearch is deliberately horizontal, built for every department. Engineering-specific functions such as geometry search or drawing checks are not part of its core.

A fit when: you are looking for an AI for the whole company, from sales to administration, and engineering is only one area among many.

Full single comparison: KoAssist and amberSearch

And what about ChatGPT or Microsoft Copilot?

That is usually the first tool design engineers try. For wording, formula knowledge or small scripts it is genuinely useful.

But: general chatbots do not know your drawings, your reading of the standards or your project history. Microsoft Copilot does reach M365 data, yet understands neither CAD geometry nor technical drawings. And the AI functions of the CAD vendors only work inside their own system.

A general chatbot knows a lot about mechanical engineering. But nothing about yours.

Full single comparison: KoAssist and Microsoft Copilot

Decision guide: which tool for which job?

• "We design the same part twice." CADENAS or simus classmate for established parts management. KoAssist's similar-part search is in early access.
• "Nobody finds the knowledge from old projects." KoAssist or Leo AI.
• "Our reviews take too long." CoLab.
• "Our master data is chaos." simus classmate.
• "We want one AI for the whole company." amberSearch.
• "We want knowledge search and drawing checks in one tool." KoAssist.
• "Our data has to stay in Germany." KoAssist or amberSearch.

How do you test this in two weeks?

A comparison built from datasheets rarely leads to a decision that holds. The following procedure costs a few person-days and produces comparable results:

1. Collect twenty real questions. From everyday work, not invented. Five of them should be questions whose answer demonstrably is not in your document base.
2. Provide a bounded test set. Frequently used standards and guidelines, plus one completed project with drawings and correspondence. The usual mess belongs in it, not a tidied-up special case.
3. Rate every answer on three axes: is it technically correct, does the citation lead to the right page, and how long would the manual search have taken.
4. Evaluate the five trick questions separately. This is where it shows whether a system stays silent or invents. This point separates the candidates more sharply than any feature list.
5. Put the operational questions in writing: hosting, sub-processors, permission model, exclusion from training. A checklist for this sits under GDPR compliant AI, the technical implementation at KoAssist under security and EU hosting.

If you are torn between operating models, the trade-off is set out in the article on on-premise or EU cloud. How the question plays out with the most widely used generic tool is covered by the GDPR check on ChatGPT for internal documents.

Conclusion

There is no single best AI assistant for engineering design. There is only the tool that matches your biggest bottleneck.

Naming the problem precisely saves months of pilot projects with the wrong tool. And anyone facing several problems at once should make sure the solution can grow with them, instead of introducing five isolated systems.

KoAssist is built for engineering departments in machine and plant building that want knowledge search and drawing checks in one platform, with data in Germany. Similar-part search is being added in early access.

All statements about vendors are based on publicly available information, as of September 2026. Features change and should be verified directly with the respective vendor before a decision. If something is no longer accurate, write to us and we will correct it. Sources are listed below the table on each individual comparison.