Serval Unveils AI Agents: $47M Series A to Transform ITSM (2023)

Serval secures $47M to revolutionize IT service management with AI agents, automating routine tasks for enhanced efficiency and innovation.

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Serval Unveils AI Agents: $47M Series A to Transform ITSM (2023)

Serval Unveils AI Agents: $47M Series A to Transform ITSM (2023)

Serval, an enterprise AI startup, has announced a $47 million Series A funding round led by Redpoint Ventures, with participation from First Round Capital, General Catalyst, Box Group, Bessemer Venture Partners, and Chemistry. This funding brings Serval’s total to $52 million, marking a significant step in its mission to automate routine IT operations using AI agents.

Background: The Challenge in IT Service Management

Traditional IT service management (ITSM) systems are often hindered by outdated, manual processes like filing tickets and handling repetitive requests. These inefficiencies slow down IT teams, causing delays in onboarding, employee frustration, and potential security risks due to slow response times.

Serval aims to modernize ITSM by deploying AI-powered agents that automate common support tasks and workflows, allowing IT professionals to focus on higher-value activities.

Serval’s AI Platform: Dual-Agent Innovation

Serval’s approach to AI in ITSM is distinguished by its dual-agent system architecture:

  • Automation Agent: Translates natural language prompts into fully coded automations, handling tasks such as software authorization, device provisioning, and access management. This agent acts like a "vibe-coding" tool, rapidly creating automations that previously required manual scripting.

  • Help Desk Agent: Interacts with end-user requests, utilizing the automated tools created by the first agent to resolve issues efficiently. It follows predefined rules and policies to ensure compliance and consistency.

CEO Jake Stauch emphasizes the platform’s ease of use, stating their goal is to make automation creation so effortless that “it’s easier to automate something forever than do it manually once.”

Market Validation and Customers

Serval’s growing customer roster includes major AI industry players such as Perplexity, Mercor, and Together AI. This clientele not only endorses Serval’s technology but also underscores the growing demand for AI-native ITSM platforms.

Use of Funds and Future Plans

Serval plans to use the $47 million funding to:

  • Expand its AI platform capabilities, enhancing enterprise-grade features.
  • Accelerate migration efforts from legacy ITSM systems to AI-native solutions.
  • Grow the team to sustain rapid product development and customer support.

The company envisions itself as the standard AI-native platform for IT teams, unlocking meaningful work by freeing employees from manual IT tasks.

Industry Impact and Context

As enterprises increasingly deploy AI tools, IT departments face the dual challenge of integrating these technologies while maintaining control and security. Serval’s agent-based system balances automation with oversight, offering a framework that could reshape IT operations management.

This approach aligns with broader trends in enterprise AI that emphasize augmenting human workers rather than replacing them, improving productivity and job satisfaction by reducing repetitive tasks.

Visual Assets

  • Official Serval logo and branding imagery.
  • Screenshots or diagrams illustrating Serval’s dual-agent AI platform architecture.
  • Photos or headshots of key executives, particularly CEO Jake Stauch.
  • Visuals of ITSM workflows automated by Serval agents.

Serval’s $47 million Series A round reflects strong investor confidence and highlights the increasing importance of AI-driven automation in IT service management. By enabling IT teams to build and deploy AI agents quickly and easily, Serval is poised to transform enterprise IT operations, making them more efficient and responsive.

Tags

ServalAI agentsIT service managementSeries A fundingautomationenterprise AIITSM
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Published on October 21, 2025 at 03:48 PM UTC • Last updated last month

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