Limy Raises $10M to Build Brand Performance Infrastructure for the Agentic Web
Limy emerged from stealth today with $10 million in funding to address what its founders call the “agentic web” infrastructure gap—the disconnect between traditional user-centric analytics and the AI agent behaviors that increasingly drive online discovery and commerce.
The funding round, led by Flybridge with participation from a16z speedrun, signals investor recognition of a fundamental shift: As AI agents become the primary interface for information discovery, brands need entirely new infrastructure to understand and optimize for agent behavior rather than human clicks.
The Agent Discovery Bottleneck
Traditional digital marketing operates on a user-centric model—tracking page views, clicks, and conversion funnels optimized for human behavior. But AI agents don’t browse like humans. They fetch structured data, synthesize multiple sources, and make recommendations without generating the digital footprints that power existing analytics systems.
“User input is no longer the center of AI discovery,” said Aviv Shamny, Limy’s CEO. “Agent data drives the new era. Most tools today track human clicks, which no longer reflect how AI systems engage with sites.”
The challenge is profound for enterprises. Fortune 100 companies using Limy’s platform report attributing up to 10% of their revenue to agent-driven discovery—a figure that traditional analytics tools cannot capture or optimize for.
Architecture for Agent Intelligence
Limy’s platform takes a fundamentally different approach to AI optimization. While most companies focus on user data, Limy intercepts and analyzes agent behavior at the point where brand domains meet the wider internet.
The system plugs into a brand’s content delivery network to detect agent activity in real-time. It captures what information agents fetch during each interaction, identifies actions taken or ignored, and traces which prompts drive agents into brand domains. This creates proprietary datasets that reflect agentic behavior patterns invisible to traditional analytics.
“What we’re doing is judging potentially hundreds of tool uses and LLM calls to understand composite agent behavior,” explained one technical team member. The platform connects prompts, agent visits, and revenue into a measurable attribution system—what the company claims is the first to link AI agents directly to business outcomes.
Enterprise Adoption and Market Validation
Despite launching billing only recently, Limy has attracted customers across e-commerce, retail, travel, media, finance, and B2B SaaS. The platform offers both self-serve dashboards for marketers and deeper enterprise integrations for large-scale deployments.
Jeff Bussgang of Flybridge characterized the opportunity as a “once-in-a-generation change” in how information is organized on the web. “Limy offers visibility into the black box of AI interaction, converting agentic behavior into discoverability and revenue,” he said.
Troy Kirwin from a16z speedrun emphasized Limy’s positioning “at the forefront of AI optimization,” highlighting its focus on agent behavior rather than traditional user activity as marking “the next evolution of AI-driven advertising.”
Infrastructure for Commercial AI Agents
The platform addresses what may be the enterprise’s most pressing AI infrastructure challenge: measuring and optimizing for systems that operate through digital pathways hidden from conventional analytics tools.
As AI agents increasingly handle discovery, research, and purchasing decisions, brands face a visibility gap that threatens their ability to influence outcomes. Traditional attribution models break down when agents aggregate information from multiple sources and make recommendations without generating trackable user events.
Limy’s tiered subscription model aligns pricing with business size and feature requirements. The company uses a usage-based approach that scales with the volume of agent interactions—recognizing that agentic commerce may operate at different scales than human-driven traffic.
Looking Forward: The Agentic Commerce Era
The funding positions Limy to advance its infrastructure as AI agents become the dominant interface for online navigation and commerce. The company’s technical leadership—including veterans recognized as data experts with deep LLM operations knowledge—suggests capability to handle the complex attribution challenges of multi-agent systems.
As enterprise adoption of AI agents accelerates, the infrastructure to understand and influence agent decision-making becomes critical. Limy’s approach represents a bet that agent-centric analytics will define how brands maintain relevance in an AI-first discovery landscape.
The platform’s ability to connect agent behavior directly to revenue outcomes may prove essential as traditional marketing measurement systems face obsolescence in an agent-driven web.
The infrastructure challenges that emerge as AI agents reshape commerce highlight the need for specialized platforms like Overclock, which provides orchestration infrastructure for enterprise AI agent deployment and management.