Risotto raises $10M seed to use AI to make ticketing systems easier to use

AI Summary4 min read

TL;DR

Risotto raised $10M in seed funding to develop AI-powered help desk automation that sits between ticketing systems and internal tools. The startup focuses on infrastructure that ensures AI reliability and has automated 60% of tickets for some clients.

Key Takeaways

  • Risotto secured $10M seed funding led by Bonfire Ventures to enhance AI-driven help desk automation between systems like Jira and internal tools.
  • The startup's core value is its infrastructure, including prompt libraries and eval suites, which manage AI reliability and are trained on real-world examples.
  • Risotto automated 60% of support tickets for payroll company Gusto, demonstrating practical efficiency gains in current ticketing systems.
  • The company is positioning for industry shifts where LLMs become primary interfaces, with integrations already developed for ChatGPT for Enterprise and Gemini.
  • Risotto addresses the complexity of existing IT systems, noting that some customers employ multiple staff just to manage platforms like Jira, highlighting immediate value in streamlining operations.

Help desk automation is a billion-dollar industry, and one of the most likely to be disrupted by tech built upon AI. Major players like Zendesk, ServiceNow and Freshworks currently dominate the space, but lots of smaller startups are betting that reshuffling workflows will give them a chance to cut in.

Risotto is one of those startups, and after today, it will have plenty of runway to test its theory. The company on Tuesday said it has raised a $10 million seed round led by Bonfire Ventures, with participation from 645 Ventures, Y Combinator, Ritual Capital, and Surgepoint Capital.

Designed to autonomously resolve help desk tickets, Risotto sits between ticket management systems like Jira and the complex internal tooling needed to resolve them. The product is built on a third-party foundation model, but CEO Aron Solberg says the core of the business is the infrastructure that sits between the model and the customer, keeping the non-deterministic nature of the model in check.

“Our special sauce is the prompt libraries, the eval suites, and the thousands and thousands of real-world examples that the AI gets trained on to ensure it actually does what it’s expected to do,” Solberg told TechCrunch.

Working with the payroll company Gusto, Risotto was able to automate away 60% of the company’s support tickets. Its current work is focused on conventional ticketing systems, but Risotto is also positioning itself for a more radical shift in the industry, as AI triggers more fundamental changes in the way help desks function.

“With 95% of our customers, humans still solve tickets the traditional way,” Solberg said. “But we see the newer companies shifting to have the primary interface between humans and the technology be an LLM.”

In practical terms, this would mean tasks are managed through tools like ChatGPT for Enterprise, which coordinate help-desk tickets alongside a range of other professional tasks. Solberg says his team has already worked on integrations with ChatGPT for Enterprise and Gemini, connecting Risotto over MCP.

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If that approach becomes more common, it would mean significant changes for the industry at large. Risotto and similar products would function as tools that would be called by a central AI, offering more focused and reliable service than a general-purpose system could perform on its own. It’s a new paradigm for thinking about SaaS products — one where reliability and context-management are more important than human-friendly interfaces.

In the meantime, Risotto’s most immediate value proposition comes from taming the mess of different IT systems. As Solberg sees it, there is still plenty of value in making it easier to use existing ticketing systems.

“One of our customers has four full-time employees just to manage Jira,” Solberg says. “And that’s to say nothing about implementing AI. That’s just to wrangle the platform itself.”

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