The biggest bottleneck in enterprise AI isn't technology — it's the gap between business expertise and technical implementation. Subject matter experts (SMEs) understand the nuances of their domain, but they can't configure AI systems. Engineers can build AI systems, but they lack domain knowledge.
Our SME Workbench eliminates this bottleneck. It provides intuitive tools that let business experts configure, evaluate, and improve AI systems directly — without writing code or filing engineering tickets.
The Workbench includes visual rule builders for business logic, evaluation dashboards for quality monitoring, and feedback mechanisms for continuous improvement. SMEs can define extraction schemas, set validation rules, review edge cases, and tune system behavior — all through a purpose-built interface.
The result is faster iteration and higher quality. When an SME notices that the system is misclassifying a document type, they can add a rule or provide feedback immediately, rather than waiting for an engineering sprint. This tight feedback loop is essential for AI systems that need to handle real-world complexity.
We've seen dramatic improvements in system accuracy and adoption when SMEs are empowered to participate directly. It's not just a better tool — it's a better model for how AI systems should be built and maintained in enterprises.