Gumloop has raised $50 million in a Series B funding round as it looks to scale its enterprise AI agent platform and expand workplace automation capabilities. The round was led by Benchmark, with participation from Nexus Venture Partners, First Round Capital, Y Combinator, BoxGroup, The Cannon Project and Shopify Ventures.
Founded in 2023 by Max Brodeur-Urbas, the startup develops a platform that allows employees across an organisation to build autonomous AI agents without needing to write code. These agents can automate complex workflows such as employee onboarding, invoice reconciliation, support ticket triage, CRM updates and request-for-proposal preparation.
The platform is designed to reduce repetitive operational work so that teams can focus on higher-value tasks. Gumloop combines a drag-and-drop workflow interface with access to multiple AI model providers and enterprise-grade security features, enabling companies to deploy AI agents safely and at scale.
The product began as a workflow automation tool and has since evolved into a broader enterprise AI platform structured across three core offerings: Gumloop Agents, the core Gumloop platform and Gumstack.
Gumloop Agents enable employees to create proactive AI agents that can connect to hundreds of business applications and operate across workplace tools such as Slack, Microsoft Teams and email. The core platform focuses on collaboration and orchestration, allowing teams to build, share and manage AI agents and automation workflows across an organisation.
Gumstack, the company’s security-focused product layer, is designed for enterprise security teams. It provides monitoring and governance tools that track how AI agents access and use data. The system can log and audit AI tool activity across platforms including Claude Code, ChatGPT and Cursor, as well as internally developed agents.
The company’s approach addresses a major concern among enterprises adopting generative AI: data governance and visibility. Many corporate security teams want to understand how employees are using AI tools and what data those systems can access.
According to the company, it has spent the last two years building authentication layers, observability features and security controls alongside improvements to the user experience. At the same time, rapid advances in large language models over the past year have accelerated the platform’s development.
Gumloop says its platform is deliberately model-agnostic, allowing teams to route tasks across multiple AI providers including OpenAI, Anthropic and Google’s Gemini, as well as open-source alternatives. This flexibility allows organisations to optimise for performance, cost and data sensitivity while making use of existing AI credits.
The platform has already been adopted by several high-growth technology companies, including Shopify, Ramp, Gusto, Samsara, Instacart and Opendoor. Employees within these organisations can share the AI agents they build with colleagues, encouraging faster internal adoption of automation tools.
Brodeur-Urbas noted that once teams begin using the platform, adoption often spreads quickly across departments. “They get addicted, they start building more agents, and then all of a sudden, the whole company is AI native.”
The Series B funding will support Gumloop’s next phase of growth, including expanding its engineering and sales teams to meet increasing enterprise demand.
Everett Randle, General Partner at Benchmark, led the investment and said the platform enables employees across organisations to build AI capabilities that can significantly improve productivity.
During due diligence, Benchmark observed strong organic adoption among users. In one case, a client tested Gumloop alongside two competing products. After six months, employees were actively using Gumloop on a daily basis while the other platforms saw little engagement.
“You can go in and start making agents and workflow automations immediately,” Randle said.
The investment reflects a broader shift in the enterprise software market as companies compete to become the standard infrastructure layer for AI usage. Vendors are increasingly expanding beyond individual tools to build integrated platforms that support deployment, monitoring, governance and automation across organisational workflows.
