Practical AI for Engineering

We’re building an engineering platform that combines specialized generative models with proven machine learning for validation. Our vision is to provide full end-to-end AI‑native engineering workflows.

• Compose AI agents into pipelines for analysis, design, and documentation
• Pair domain‑specific generative models with history data ML models for quality checks
• Keep full visibility with traceable runs and reviewable steps in real time
• Build on open components and formats to reduce vendor lock‑in

We turn engineering data into specialized models and evaluation suites that perform in production. Foundation models are adapted to your domain and integrated into agent pipelines with clear guardrails and provenance.

• Data curation and alignment from past projects (with anonymization where needed)
• Fine‑tuning and adapters for domain terminology, geometry, text, and tables
• Benchmarks aligned with engineering constraints and acceptance criteria
• Deployment into agent workflows with observability, versioning, and rollback

Research and consulting to bring agentic and generative methods into real engineering work. Plan, prototype, and roll out with clear milestones, quality checks, and handover.

• Strategy, architecture, and governance: build/buy/partner choices; data, models, and safety guardrails; metrics and oversight
• Pilots and enablement: scoped experiments with clear success criteria, phased validation, training, and workflow change
• Looking ahead: interfaces to robotics and on‑site automation, and exploration of quantum techniques for hard optimization problems