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Bullish +75

OpsMill raises $14m Series A to make IT infrastructure data trustworthy enough for AI agents

AI-generated analysis

πŸ’° OpsMill has raised $14 million in a Series A funding round led by IRIS Capital.

πŸ“ The startup is based in Paris with an additional office in London, France.

🀝 Existing investors Serena and Partech joined the round alongside new partner BGV.

πŸ› οΈ The funds will be used to expand engineering and product teams to develop their Infrahub platform.

🧠 Infrahub provides AI agents and engineering teams with a single trusted view of enterprise IT infrastructure.

πŸ“‰ It addresses the issue where infrastructure data is currently scattered across spreadsheets, scripts, and CMDBs.

πŸ€– Inaccurate infrastructure data can cause errors to cascade through production systems when AI agents act on it.

πŸ“Š Gartner forecasts 30% of enterprises will automate over half their network activities by 2026.

πŸ’Έ Enterprises risk losing an average of $300,000 per hour of downtime according to the ITIC 2024 report.

πŸ—ΊοΈ The platform uses a graph database to map connections between infrastructure elements and their configurations.

βœ… All proposed changes are validated through a DevOps-style review process before deployment.

🏒 CEO Damien Garros notes that automation is ultimately a data problem requiring a complete network view.

πŸ“¦ Infrahub is offered in both free open-source Community and licensed Enterprise editions similar to GitLab's model.

🀳 TikTok has deployed the platform, alongside European cloud provider Eurofiber which reduced deployment times from five days to 15 minutes.

πŸ›‘ IRIS partner Julien-David Nitlech stated that AI-driven operations cannot function without clean, structured data.

Bullish Signals
  • OpsMill raised a strong $14 million Series A round led by IRIS, with participation from BGV and existing investors Serena and Partech.
  • The funding will directly support the growth of engineering and product teams while continuing the development of the Infrahub platform.
  • Infrahub is already in production at major enterprises like TikTok and a European cloud provider (Eurofiber), demonstrating immediate market traction.
  • Eurofiber has achieved significant efficiency gains, cutting service deployment times from five days down to just fifteen minutes since adopting the platform.
  • Gartner forecasts that 30% of enterprises will automate more than half of their network activities by 2026, creating a massive tailwind for OpsMill's automation-focused solution.
  • The company addresses a high-impact problem where enterprises risk losing an average of $300,000 per hour of downtime, positioning Infrahub as critical infrastructure protection.
  • OpsMill offers a flexible go-to-market strategy with both free open-source Community and licensed Enterprise editions, similar to the successful GitLab model.
  • The platform is already adopted by a diverse set of industry leaders including hyperscalers, global retailers, fintechs, insurers, and manufacturers.
Risk Factors
  • A failure in the OpsMill Infrahub platform at TikTok or other clients could lead to cascading errors in production systems, as highlighted by the Gartner forecast that 30% of enterprises will automate more than half their network activities by 2026.
  • The ITIC 2024 report indicates that average enterprise downtime costs around $300,000 per hour before reputational damage, making reliance on new infrastructure data tools like Infrahub a single point of failure for critical operations.
  • While Infrahub is free for open-source Community editions, Enterprises must pay for governance and compliance features, creating potential friction for large-scale deployments compared to existing integrated solutions.
  • Most current enterprises still rely on scattered spreadsheets and ad-hoc scripts for infrastructure data, suggesting that adoption of OpsMill's graph database approach may require significant restructuring of existing workflows.
Full Analysis
OpsMill, a Paris-based infrastructure data management company headquartered with operations in London, has raised $14 million in a Series A funding round led by IRIS, with participation from BGV and existing investors Serena and Partech. The capital will be utilized to expand engineering and product teams while advancing the development of its flagship Infrahub platform. This software is designed to provide AI agents and engineering teams with a single, trusted view of an enterprise's IT infrastructure, addressing the industry-wide challenge where automation spreads through applications while underlying infrastructure data remains scattered across spreadsheets, configuration databases, and ad-hoc scripts. The article highlights that incomplete or inaccurate infrastructure data can cause cascading errors when acted upon by AI agents. To contextualize the scale of this problem, the company cites a Gartner forecast predicting 30% of enterprises will automate more than half their network activities by 2026, a significant rise from under 10% in mid-2023. Additionally, ITIC data indicates an average enterprise loses approximately $300,000 per hour of downtime, not including reputational costs. OpsMill's solution utilizes a graph database rather than traditional table-based asset registers to map connections between hundreds of thousands of infrastructure elements and validate proposed changes through a DevOps-style review process before deployment. Infrahub is available in two editions: a free open-source Community version and a licensed Enterprise edition, with customers including hyperscalers like TikTok and various European cloud providers such as Eurofiber. Eurofiber reported cutting service deployment times from five days to fifteen minutes after adopting the platform. Co-founders Damien Garros and Karen Gallantry bring extensive operator-side experience from companies like Juniper, Roblox, and Network to Code. The investment is framed by IRIS partner Julien-David Nitlech as essential for organizations attempting to build AI-driven operations on foundations not designed for it, emphasizing that clean, structured data is a prerequisite for scaling AI in enterprise infrastructure.