Cognyx offers a SaaS platform that ingests PLM and ERP data into a unified knowledge graph and provides a visual, collaborative interface for building, simulating, and controlling Bills of Materials. AI agents help optimize BOMs by suggesting component, process, and material configurations that meet cost, technical, regulatory, and sustainability constraints, accelerating product development for hardware manufacturers.
Funding
$1.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
5OBDFounders
Product
Problem
Manufacturers struggle with slow, fragmented Bill of Materials (BOM) creation and optimization due to disconnected PLM/ERP data, manual processes, and difficulty enforcing engineering constraints, leading to delayed product development and higher non‑recurring engineering costs.
Solution
Cognyx provides a SaaS platform that ingests PLM and ERP data into a unified knowledge graph and presents it through a visual, collaborative interface. Users can build, simulate, and control BOMs as modular building blocks, while AI agents suggest optimal component, process, and material configurations under defined cost, technical, regulatory, and sustainability constraints. The system supports real‑time multi‑BOM alignment (eBOM, mBOM, pBOM) and enforces custom QA rules, enabling rapid concept design, reduced RFQ response times, and continuous compliance checking.
Target Audience
Primary customers are hardware manufacturers and engineering teams that manage complex product development pipelines, including design, sourcing, and production engineering groups.
Features
- Automated ingestion and mapping of PLM‑ERP data into a smart R&D ontology stored in a knowledge graph
- Visual UI for assembling components, processes, tools, and configurations as modular building blocks
- Collaborative environment with real‑time updates, in‑context comments, and multi‑BOM synchronization
- Built‑in MBSE simulation module to run integrity checks and enforce custom design, manufacturing, and economic rules
- AI agents that ingest unstructured “lessons learned” and generate enforceable BOM rules and optimization scenarios
- Constraint‑driven AI optimization recommending component substitutions to improve cost, margin, lead time, and CO₂ impact
- Costing intelligence linking BOM items to supply scenarios for lead‑time and cost minimization