We combine deep industrial automation domain knowledge with hands-on expertise in leading AI tools and platforms to help OEMs engineer products faster, with higher quality and lower cost. Our engineers use AI coding assistants such as GitHub Copilot, Cursor, Claude, ChatGPT across PLC, firmware, HMI and application development.
We build custom AI accelerators and engineering copilots on enterprise AI platforms such as Azure OpenAI, AWS Bedrock and Google Vertex AI, using frameworks like LangChain and LlamaIndex for retrieval-augmented generation (RAG) over technical manuals, standards and engineering data.
For OEMs with strict IP and data-privacy needs, we deploy open-source models such as Llama and Mistral on-premise or at the edge, so sensitive product code and designs never leave the client’s environment. We also work with vendor-specific AI engineering assistants emerging in the automation ecosystem to help OEMs get the most from their platforms.
Every AI-assisted workflow follows a human-in-the-loop approach: engineers review, validate and own all AI outputs, and safety-critical work goes through the standard IEC 61508 / IEC 62443 verification and validation process. Our AI governance practices cover data security, IP protection and responsible use, with alignment to our customer’s frameworks.
With help of AI assisted Engineering, we offer
- Engineering Knowledge Assistants
- Predictive Maintenance Models
- Automated Documentation
- Diagnostic AI Tools
- Workflow Optimization