We are building and scaling the new agentic workflow platform to establish a resilient layer for accounting workflows. The team is actively integrating advanced AI tools and large language models to accelerate engineering delivery and design patterns.

A lot of SaaS teams are thinking about adding AI right now. But I think the better question is : **Is the product ready for agentic workflows?** Not just a chatbot or a prebuilt assistant sitting on top of the product. I mean workflows where AI can help move real work forward inside the SaaS: reviewing context, preparing actions, updating statuses, routing exceptions, asking for approval, or escalating when it should not act. Most SaaS products were built around screens, roles, buttons, and fixed workflows. That works when humans are making every decision. But once AI starts participating in the workflow, the system needs clearer boundaries. What context can it access?Which actions can it take? Which actions need approval? What should stay deterministic? What gets logged?What happens when it is wrong? My view: before building agentic workflows, first map one important workflow and check whether the product is structurally ready for AI to assist, act, escalate, or stop. For SaaS founders building with AI, where does this get hardest: choosing the right workflow, giving AI enough context, or defining what it is allowed to do?