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AI-BOOST Challenge 2: Agentic AI for Automated CAD Generation and Autonomous Simulation

Description

This challenge aims to develop an agentic AI system capable of automating key engineering tasks across the CAD design and simulation workflow. Starting from existing CAD assemblies, 2D piping drawings and natural language engineering requirements, the solution should generate compatible parametric 3D CAD models, interpret engineering constraints, and autonomously prepare simulation workflows. The long-term objective is to transition from tool-assisted engineering to AI-driven autonomous engineering while maintaining human oversight and industrial validation.

Funding Amount

The AI-BOOST competition follows a two-stage prize model.

SPARK Phase

  • 5 winners receive €28,500 each.
  • Prize paid in two instalments:
    • 50% after signing the Participation Agreement.
    • 50% after successfully completing the Mid-Term Checkpoint.

ADVANCE Phase

  • The five SPARK winners continue into the Advance Phase.
  • One overall Challenge Winner receives €100,000.

Special Awards

  • Innovation Excellence Award: €12,500
  • Responsible AI Award: €12,500

(A participant may receive both the Challenge Prize and a Special Award.)

Submission Deadlines

  • Call opens: 19 June 2026
  • Application deadline: 25 August 2026 (17:00 CEST)

Submission Conditions

Applications must be submitted through the AI-BOOST F6S platform by 25 August 2026 (17:00 CEST). Proposals must address the Challenge 2 objectives and comply with the AI-BOOST programme requirements.

  • Applications must be completed in English.
  • Only one application per applicant is permitted.
  • Solutions must focus on automated CAD generation and autonomous simulation workflows.
  • Projects must comply with Responsible AI, ethical and EU legal requirements.
  • Selected participants must complete the SPARK and ADVANCE phases, mentoring activities, Mid-Term Checkpoint and Final Live Competition.
  • Human oversight must remain part of the engineering review process.

Eligible Businesses

The competition is open to organisations and innovators capable of developing AI-based engineering solutions, including:

  • SMEs and start-ups
  • Large companies
  • Universities and higher education institutions
  • Research organisations
  • NGOs and non-profit organisations
  • Individual innovators
  • Single legal entities
  • Consortia

Eligible Countries

Applicants must be established in:

  • EU Member States
  • Horizon Europe Associated Countries
  • EU Overseas Countries and Territories (OCTs)

Technology Readiness Level (TRL)

  • Expected starting TRL (competition level): TRL 2–3
  • Target TRL for Challenge 2: TRL 5–6
  • Validation should be demonstrated in representative industrial scenarios with outputs suitable for technical review by experienced engineers.

Expected Outcome

Projects are expected to deliver:

  • A functional Proof of Concept integrating automated CAD generation and intelligent simulation setup.
  • An AI-driven workflow from engineering requirements to validated CAD and FEA preparation.
  • Measurable reduction in manual engineering effort and design time.
  • Automated generation of parametric CAD models compatible with existing assemblies.
  • Automated preparation of structural simulations, including mesh generation and convergence analysis.
  • Validation against expert-defined CAD and FEA processes in representative industrial environments.

Scope

Projects should develop an AI solution capable of supporting the complete engineering workflow from design intent to simulation setup.

The solution should be able to:

  • Interpret engineering requirements expressed in natural language.
  • Extract geometric and assembly constraints from CAD assemblies, 2D drawings and engineering metadata.
  • Generate compatible parametric CAD components and piping models.
  • Respect functional, dimensional and assembly constraints.
  • Automate mesh generation, seed strategy definition and convergence analysis.
  • Identify critical simulation regions and recommend mesh refinement strategies.
  • Produce outputs suitable for expert validation and integration into existing engineering workflows.

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