Accuris delivers mission-critical intelligence to engineers and supply chain professionals, supporting more than 7,500 customers across aerospace, defense, manufacturing and more in over 100 countries. Accuris empowers innovators to solve complex sourcing and design challenges by unifying the world’s most extensive supply chain data with advanced GenAI capabilities. To address macro trends in AI-driven sourcing, supply chain resilience and digital transformation, Accuris partnered with Databricks to build a GenAI-powered engineering assistant to accelerate decision-making and deliver actionable insights at scale.
Unlocking reliable parts sourcing in a fragmented data landscape
Accuris oversees one of the world’s most extensive catalogs of electronic components, each component is enriched with structured and unstructured data such as parametric data, environmental attributes, pricing and supporting documentation. This data’s sheer volume and variety made it challenging to generate AI-ready insights at scale. Early efforts using traditional machine learning approaches introduced familiar limitations: labor-intensive feature engineering, inconsistent model performance and high demands on compute resources and technical expertise.
The business need became clear as sourcing teams demanded faster, more accurate ways to identify alternate parts and reduce supply chain risk. Accuris needed a solution to unify fragmented data, enable intelligent recommendations and scale with agility. While exploring retrieval augmented generation (RAG) to enhance discovery and search functionality, the team found existing vendor solutions lacked the scalability and intelligence required to serve a massive volume of records.
Accuris made the seamless transition to the Databricks Data Intelligence Platform, bringing trusted, high-performance infrastructure to the forefront of their GenAI strategy. “With traditional ML, it often felt like we were feeding and caring for a dragon — complex, resource-intensive and slower to adapt,” Graham Lammers, Executive Director of Data Intelligence at Accuris, said. “With Databricks RAG, we’re now engaging directly with our data through natural language and intelligent retrieval, unlocking insights at scale with a fraction of the effort.”
Creating the GenAI-powered engineering assistant, marked a turning point. Designed to improve sourcing workflows, cycle times, and digital self-service for customers, this assistant helped solve longstanding discovery challenges and catalyzed a more collaborative development approach.
Unifying data ingestion and transformation with Delta Lake and Unity Catalog
With Databricks, Accuris could integrate and govern vast amounts of structured and unstructured data using Unity Catalog, ensuring secure access and compliance across teams and customers. Delta Lake and Spark Declarative Pipelines brought reliability and scalability to data pipelines, while managed MLflow enabled rapid model development, evaluation and tracking. “Databricks unified our ingestion, transformation and RAG-based workflows. Our AI Assistant wouldn’t be possible without scalable Vector Search, multimodal model integration and governed access to our content and customer data,” Lammers said.
The Mosaic AI suite — comprising Agent Framework, Vector Search, MLflow and Model Serving — empowered Accuris to deliver real-time, domain-specific decision-making. The Accuris AI assistant leverages these tools to provide agentic, traceable responses, integrating structured metadata, datasheets and sourcing intelligence. The platform’s Lakeflow Jobs and Jobs API streamlined orchestration, while MLflow allowed the team to track query health and response quality.
Accuris’ dedicated cross-functional GenAI team led the entire initiative, with strategic support from Databricks experts. “The best practices and deep expertise from Databricks empowered us to accelerate at lightspeed,” Lammers emphasized.
Accelerating AI innovation with Mosaic AI, RAG pipelines and MLflow
While the Accuris AI assistant is currently in early access with customers, the impact on Accuris’ development velocity and innovation capacity is already clear. Thanks to streamlined MLflow-based evaluation and tracking, the company has achieved a 10x increase in speed from concept to delivery. This rapid iteration cycle has allowed Accuris to continuously refine their GenAI solutions based on real-world feedback and evolving customer needs.
AI is central to how Accuris delivers product value in the Supply Chain Solutions business line. The company plans to further scale their capabilities by expanding multimodal understanding — such as combining image and specification analysis — monitoring quality and deploying specialized agents for environmental, sourcing, compliance and pricing use cases. “We’ll continue using Databricks to scale multimodal understanding, monitor quality, drive feature development and deploy specialized agents,” Lammers said.
Looking ahead, Accuris is excited about the potential of new Databricks innovations like Agent Bricks to advance the development and deployment of adaptive AI systems across their platform. The company is also focused on deepening customer engagement by delivering more persona-driven experiences, making every interaction more relevant, efficient and aligned with real-world engineering and supply chain workflows.