Senior Full Stack Engineer

Rippling launches AI Spend Console to track AI usage and ROI across the business. Connects AI spend with workforce data, and closes the loop with AI model controls and routing. Rippling announced AI Spend Console, a new capability that helps companies understand and control AI spend. Unlike other systems that passively report on token consumption, Rippling's AI Spend Console includes advanced employee usage insights and a gateway that actively controls and shapes AI usage in your company. Customers are invited to join the waitlist starting today. The question isn't how much you are spending on AI. It's what your AI spend is producing. Until you can answer that, you're just managing costs - not outcomes. As AI adoption charges forward across every business, leaders urgently need visibility into AI spend: how much, by whom, and whether it's paying off. But there's no way to track these expenses or link them to productivity improvements. Rippling's AI Spend Console provides leaders a clear view of AI spend, showing exactly which models are being used by which departments and teams. Administrators can enforce policies on token spend and AI model access, and route every AI request to the most cost effective models. It's the control layer companies have been missing as AI moves from experiment to infrastructure. Rippling AI brings an entirely new level of insight to the problem. Using the power of Rippling Data Cloud, Rippling AI can answer sophisticated questions about the nature of AI spend in your company. It's far more powerful than the static dashboards of existing solutions. Rippling's superpower of employee identity further amplifies the value of AI Spend Console. It connects AI usage data with employee identity and business data from across your company's systems. It gives leaders a continuous view of spend across tools like Claude, Cursor and Codex, and then measures that spend against signals from systems like GitHub or Salesforce. Rippling identifies not just who is consuming tokens, but what that spend is producing: pull requests, code velocity, and even revenue contributed. "Looking at a dashboard of AI spend shows you a problem, but doesn't offer you a solution. That's a recipe for anxiety," said Matt MacInnis, Chief Product Officer at Rippling. "Our AI Spend Console goes two steps beyond that. First, we give you a way to govern expenses with our AI gateway, so you can keep people from editing slide decks with Fable. And second, we give you a way to map it back to business outcomes, so you know what usage is generating real ROI." AI Spend Console builds on the recently released Rippling Data Cloud, which connects third-party business data to Rippling's Employee Graph, a record of employees, departments, roles and reporting lines. By integrating data from sources such as Salesforce and GitHub with employee information, Rippling AI gains a fuller understanding of the organization and can act on unified data, the foundation for visibility into AI spending. That same foundation generates permissioned dashboards across a company's connected data, so leaders can move beyond a static report: drilling into spend and usage patterns, asking follow-up questions in natural language and customizing charts, all without writing SQL or waiting on a data team. "The question isn't how much you are spending on AI. It's what your AI spend is producing. Until you can answer that, you're just managing costs - not outcomes," said Adam Swiecicki, Chief Financial Officer of Rippling. AI Spend Console is the latest in a series of Rippling product launches over the past four months. The company launched Procurement earlier this week, added Automated Compliance and Business Banking earlier this year, as well as AI-powered Benefits Administration. Rippling introduced Data Cloud in June to connect third-party business data to employee records, and has continued to expand Rippling AI's capabilities across HR, IT, finance, and now AI spending. [To share your insights with us, please write to [email protected]]

AI security firm accuses Rippling of trade secret theft. 5h ago · 0:00 listen · Source: IAM Media Summary. An AI security firm is accusing Rippling of trade secret theft. Runlayer alleges a Rippling employee revealed the company is using Runlayer's trade secrets. This information was reportedly used to build a clone of Runlayer's product. That product is software designed to control how AI agents interact with enterprise systems. This story highlights potential intellectual property disputes in the rapidly evolving AI industry. This is an AI-generated audio summary. Always check the original source for complete reporting.

Runlayer sues Rippling over alleged MCP gateway theft. Published · Jul 29, 2026 Why Relve is watching this The suit is a live test of how much access enterprise customers can get during a product trial before "build it ourselves" crosses into trade secret theft, a risk every AI infrastructure startup selling to tech-savvy buyers now has to price in. Key Takeaways * Runlayer, an MCP security gateway startup, is suing HR software company Rippling over trade secret misappropriation and breach of contract claims. * Runlayer alleges Rippling used nearly a year of deep product trial access, including its source code, to build a competing MCP gateway in-house. * A "Rippling insider" reportedly texted Runlayer's CEO to warn that Rippling's internal project was nearly a one-to-one copy of Runlayer's product. * Rippling confirmed it is launching its own MCP gateway, but its spokesperson denies misusing Runlayer's intellectual property. * Runlayer has raised $42 million since launching in mid-2025, backed by Khosla Ventures and Felicis. What happened. MCP security gateway startup Runlayer has sued HR software company Rippling, alleging trade secret misappropriation, unfair competition, and breach of contract, according to a complaint seen by TechCrunch. Runlayer says Rippling evaluated its product for nearly a year under a mutual non-disclosure agreement and a trial agreement barring Rippling from copying its technology or building derivative works. The two companies could not agree on a price, and Runlayer ended the trial. Runlayer alleges a "Rippling insider" later texted its CEO, Andrew Berman, to warn him about an internal project building a near-identical copy of Runlayer's gateway. Rippling has confirmed to TechCrunch that it is launching its own MCP gateway, while denying it misused Runlayer's intellectual property. Runlayer, which launched in mid-2025 and has raised $42 million from investors including Khosla Ventures and Felicis, has retained law firm Sullivan & Cromwell for the case. Why it matters. The dispute is a cautionary tale for AI infrastructure startups selling into enterprise customers that have their own engineering muscle, since a deep, months-long product trial can double as a blueprint for a competing in-house build. MCP gateways have gotten more crowded since Anthropic open-sourced the underlying protocol in 2024, raising the stakes for smaller vendors trying to lock in enterprise deals before customers build their own version. Runlayer's claims come from its own complaint and remain unproven, and building a similar product after a failed deal is not automatically theft, since ideas and general product categories are not protected the way specific code or trade secrets are. Retaining a marquee law firm signals confidence, not the merits of the case. Runlayer's panicked effort to avoid competition by fabricating claims. Rippling spokesperson Bottom line. Watch how this suit proceeds, since a ruling either way will shape how AI infrastructure startups structure enterprise trials and NDAs going forward. A win for Runlayer could make companies more cautious about extensive hands-on evaluations with competitors-in-waiting, while a win for Rippling would reinforce that enterprises can walk away and build their own version. For startups selling AI infrastructure into enterprise, per Relve, an AI tools intelligence platform, the practical takeaway is to limit source code and roadmap access during trials, and to price and structure NDAs with the possibility of a walkaway build in mind. Neelam Khan. Lead Editor Neelam Khan is a Lead Editor at Relve, covering AI news, tools, product updates, search trends, and business use cases. She filters noise from useful signals for founders and teams, drawing on her previous work in AI SEO, content strategy, and tool research with Wellows and AllAboutAI.