Agentic AI will change how payroll runs. But an agent is only as good as the information it can reach, and most payroll knowledge lives in people's heads, in Word and scattered drives. Paytools is the structured, governed layer that makes AI useful in payroll, and that foundation pays off long before the agents.
Paytools has an MCP server, the open standard most AI assistants support. If your organisation uses Claude, ChatGPT, Copilot or another assistant that speaks MCP, you can connect it to Paytools with your existing login and permissions.
Your assistant reads Paytools to gather all the knowledge about your pay cycles, checklists, processes and who owns what. It writes the orientation guide you never had time to: how this payroll function actually runs, in the order a new person needs to learn it.
Your assistant reads the Activity Log for the whole period, every check completed, every template changed, every employee record touched. It turns a month of individual events into the pattern you actually wanted: who carried the load, what ran late every cycle, and what changed in your configuration.
Your assistant finds every check still sending work to the old folder and shows you the list before it touches anything. You approve, it makes the changes, and every edit lands in the Activity Log under your name.
The work that makes AI useful later will make payroll calmer today. Once you've seen it you'll wish you had done it sooner.
Every task owned, every check evidenced, pay day finishing on time. The structured record of how your payroll runs starts here.
Explore Payroll Processing →Starters, leavers, adjustments and recoveries as employee actions with an owner, a pay period and a state. Structured work an agent can pick up.
Explore Employee Actions →Obligations, risks, controls and a complete audit trail. The governed evidence that an agent, and an auditor, can rely on.
Explore Governance →