Product
AI agents built for finance.
Msasa’s AI agents are designed for finance workflows such as matching data across systems, performing variance analysis, and generating financial summaries. They can also pull the context they need directly from systems like Xero and QuickBooks.
Why teams use this workflow
- Use agents to build workflows, structure outputs, and summarize findings faster.
- Reduce manual reporting steps without turning finance work into generic chat.
- Keep agent activity attached to real workflows and business outputs.
How agents fit into the workflow
- 1. Use agents for steps that require judgment, interpretation, or summarization.
- 2. Let agents handle work that would otherwise require manual effort.
- 3. Place an agent anywhere in the workflow where context or reasoning is needed.
- 4. Send the final output to Google Sheets, a dashboard, or Slack.
Frequently asked questions
Is this just a finance chatbot? No. The goal is not generic chat. The agents are there to speed up execution inside recurring finance workflows.
What kinds of steps can agents help with? Teams use agents for steps such as matching unstructured data across systems, allocating manual journals to customer invoices, preparing weekly cash flow summaries, and performing flux analysis.
Next step
See how Msasa fits your finance stack
Book a demo to see how AI agents can remove repetitive finance work while staying tied to the workflows, dashboards, Sheets, and Slack outputs your team already uses.