Designing a AI Access Layer for Systems of Record
The article discusses the development of an AI access layer for TeamPlanner, a custom-built system used for capacity planning and staffing visibility. The goal is to simplify access to data without the need for extensive manual filtering and navigation. The first version of the AI agent will be read-only and will respect existing user permissions while providing quick answers to staffing-related questions.
- ▪TeamPlanner is used to track people, projects, assignments, and other staffing-related attributes.
- ▪The AI access layer aims to reduce the effort required to obtain answers from TeamPlanner during live discussions.
- ▪The first version of the AI agent will only provide read-only access and will not alter any data.
Opening excerpt (first ~120 words) tap to expand
There’s no need to guess — you’re definitely using systems of record: ERPs, financial systems, capacity planners, CRMs, HRIS, ITSM tools. For us at MEV, those systems hold the answers: who is available when, who owns which account, where a ticket is stuck, and who will be on the bench next month. The issue is the cost of access: every question turns into several screens, filters, and a context switch, which breaks the flow of a call.We ran into this problem ourselves long before we started thinking about an AI agent. Inside MEV, we use an internal custom-built system called TeamPlanner for capacity planning and staffing visibility. TeamPlanner tracks people, projects, assignments, time off, departments, levels, locations, and related attributes.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Mev.
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