Runlayer and Rippling End Legal Battle Over AI Gateway

Startup Runlayer and established enterprise Rippling officially dismissed their ongoing lawsuits against each other on Wednesday night. Court documents reviewed by reporters indicate that no financial settlement was paid, and neither party covered legal fees. The dismissal cleared the path for Rippling to immediately launch its own MCP gateway, which serves as a direct competitor to Runlayer's core offering in the enterprise AI space.

The genesis of the dispute dates back to an extended testing period where Rippling evaluated Runlayer's software. According to the original lawsuit, the engineering teams collaborated for over a year before Rippling opted against becoming a paying customer. Instead, an internal communication tipped off Runlayer that Rippling was developing a proprietary alternative. Runlayer subsequently initiated legal action alleging contractual violations during the product testing phase, which prompted Rippling to file a countersuit citing patent infringement claims.

Runlayer is an early-stage company that emerged from stealth in November 2025. Led by serial founder Andrew Berman, the startup secured forty-two million dollars in venture backing from prominent investors including Khosla Ventures and Felicis. The core technology at the center of the dispute, an MCP gateway, acts as a secure intermediary for enterprise AI agents requesting sensitive data from various corporate software systems.

Rather than granting automated agents direct, unrestricted access to internal tools, an MCP gateway manages data retrieval securely. It incorporates essential enterprise features such as role-based access control, ensuring that managers and interns view different permission tiers, alongside comprehensive logging and usage tracking. This infrastructure layer has become increasingly vital as businesses deploy generative tools that interact with multiple third-party applications simultaneously.

The sudden rivalry underscores a growing vulnerability for early-stage enterprise software developers. Extended pilot programs and technical evaluations, traditionally used by large corporations to vet startup vendors, carry renewed risks in an era where software development cycles have accelerated dramatically. Large platforms can observe market demand through trials and rapidly pivot to build competing native solutions before a startup can solidify its market position.

Rippling, known primarily for its payroll and HR management software, has now expanded aggressively into artificial intelligence tooling. The newly released gateway routes traffic across various foundational models while monitoring token consumption by individual employees. This puts Rippling in competition with financial and infrastructure giants like Stripe, Ramp, and Databricks, while its security features pit it against specialized startups and cloud providers.

Meanwhile, Runlayer continues to pitch a broader security suite designed specifically for autonomous workflows. Beyond the core routing gateway, its platform includes tools for agent creation and the detection of unauthorized shadow AI deployments within corporate networks. The company maintains that its comprehensive bundle provides differentiation beyond a simple routing proxy.

The rapid resolution of the lawsuits without monetary exchange highlights the pragmatic nature of the dispute, but the underlying tension remains a clear warning for the broader ecosystem. As software creation becomes more trivial, boundaries between customers, partners, and competitors continue to blur. Founders navigating long enterprise sales cycles must carefully weigh the proprietary risks of close technical collaboration with industry giants.

Observers and startup founders will likely view this episode as a defining case study in modern platform competition. As traditional software providers race to embed AI infrastructure natively into their systems, early-stage developers must find defensive moats that extend well beyond single-feature utilities. The future of enterprise AI tooling will depend heavily on how startups protect their intellectual property against deeply capitalized incumbents.