A SaaS firm approached us with a support operation that had become difficult to manage at scale. Tickets were arriving into a single, unstructured queue and being sorted manually by staff each day. Without a consistent prioritisation process, high-urgency issues were getting lost in the backlog, customers were waiting longer than they should, and the support team was spending a disproportionate amount of time on triage rather than resolution. Our agentic AI development team analysed the existing workflow, identified intelligent ticket routing as the right solution, and built a triage agent that reads each incoming ticket, categorises it instantly, and directs it to the correct team without any manual input.
Software as a Service
AI Agent Development
We reviewed the client’s current ticket handling process in detail, documenting the volume of daily requests, the range of issue categories, and the criteria the team used to manually sort and prioritise incoming support queries.
Our team defined the routing rules and category taxonomy the agent would need to follow. We ensured the logic was built around how the support team actually operated, rather than introducing a new structure they would need to adapt to.
We connected the agent to the client’s existing helpdesk platform, ensuring the routing logic operated within their current environment without requiring changes to established workflows or tooling.
We deployed the triage agent into the live inbox, monitored early performance closely, and refined category thresholds to ensure accurate, consistent routing from the point of go-live.
Many tickets combined technical and billing language, making clean categorisation difficult. A key part of our work was training the model on representative examples across each category so it could distinguish intent accurately and route accordingly, even when a ticket touched on more than one issue type.
The agent needed to classify and route tickets the moment they arrived, without introducing a new delay into the process. We optimised the model and the underlying infrastructure to ensure real-time processing matched the client’s incoming ticket volume without creating a bottleneck.
The client already had established tooling in place, and replacing it was not an option. We designed the agent to integrate with their existing helpdesk platform, ensuring the routing logic operated within their current environment rather than requiring teams to change how they worked.
