
Enterprise IT startup Atomicwork has secured $25 million in Series A funding to scale its AI-powered service management platform. The round was led by Khosla Ventures and Z47, with participation from Battery Ventures, Blume Ventures, and Peak XV Partners, bringing the company's total funding to $40 million.
Key Points:
- Atomicwork's platform aims to replace traditional IT service management systems with an AI-native solution that can be deployed in weeks rather than years
- The company is valued at $150 million following this investment, according to sources familiar with the matter
- Current customers include Zuora, Pepper Money, and Ammex Corporation, with the platform claiming to reduce IT resolution times by 90%
The San Francisco-based company, founded in 2022 by former Nutanix executive Vijay Rayapati and Freshworks founding team members Kiran Darisi and Parsuram Vijayasankar, is taking aim at the established IT service management (ITSM) market dominated by players like ServiceNow. Their approach centers on what they call "agentic service management," which leverages AI to automate routine IT tasks and streamline enterprise workflows.
The platform integrates with common workplace tools like Microsoft Teams, Slack, Intune, and Okta, allowing employees to access services across IT, HR, and finance departments through a unified interface.
Early adopters are reporting promising results. "Atomicwork helped us consolidate three solutions into one platform, improving employee experience, reducing ticket volumes, and cutting costs—all in just six weeks," said Ryder Hampton, Head of Technology at Pepper Money.
The company's timing appears opportune, as enterprises increasingly seek AI-powered solutions to modernize their operations. Kanu Gulati of Khosla Ventures noted, "Atomicwork's AI agents can autonomously handle everyday IT services, and employees can then focus on actually growing the business."
To address data security concerns, the company offers enterprises options to own their encryption keys or use their own model endpoints. The platform uses existing large language models from OpenAI, Anthropic, Cohere, and Meta, alongside proprietary small models for specific tasks like intent detection and routing.
With new backing from industry names and a growing set of enterprise customers, the startup hopes to challenge legacy IT solutions and provide a faster, AI-powered alternative. However, the company faces the challenge of competing in a market where established players are also rapidly incorporating AI capabilities into their solutions.