Composio Raises $25M to Build AI Agents That Learn From Experience

Artificial intelligence startup Composio has secured $25 million in a Series A funding round to address a critical limitation holding back the widespread adoption of AI agents in the enterprise: their inability to learn from experience.[1][2] The funding round was led by Lightspeed Venture Partners and saw participation from existing investors Elevation Capital and Together Fund.[3][4] Several prominent angel investors, including HubSpot founder Dharmesh Shah and Vercel CEO Guillermo Rauch, also contributed to the round, bringing Composio's total funding to $29 million.[1][3] This significant capital injection will be used to expand the company's engineering and research teams as it tackles the challenge of creating AI agents that can continuously improve and adapt within complex business environments.[4][5]

Despite the considerable hype surrounding AI agents, their deployment in large-scale enterprise workflows has been limited.[1] A core reason for this is that current AI models, while proficient at executing pre-defined tasks, lack the capacity to learn from their mistakes, build context over time, or develop the nuanced understanding that human employees gain through experience.[1][6] This results in static tools that often require extensive manual tweaking of prompts and instructions to function correctly, hitting a wall in their effectiveness.[1] AI agents can be prone to hallucinations and unreliability, with developers spending months trying to optimize their performance for production environments. This inherent lack of adaptability prevents them from becoming truly invaluable assets in dynamic business settings.

Composio, founded by Soham Ganatra and Karan Vaidya, aims to solve this problem at the infrastructure level.[7][8] The San Francisco and Bengaluru-based company is developing what it calls a "shared learning layer" for AI agents.[1][4] This platform is built on the idea that knowledge gained by one agent should be accessible to all others within the ecosystem.[1] When an agent on Composio's platform successfully navigates a complex workflow, such as handling a specific edge case in a Salesforce integration or optimizing a process in GitHub, that acquired knowledge is codified and stored as a "skill."[6] This skill then becomes a reusable component available to other agents, creating a network effect where the entire system becomes more intelligent and capable with each interaction.[1][6] Underpinning this is a reinforcement learning layer that allows the agents to build intuition from their experiences, moving beyond simple instruction-following to a deeper, more contextual understanding of tasks.[9][10]

The company's platform is designed to ease the development and integration of these learning agents into enterprise systems.[11] Composio provides a suite of tools that simplifies complex processes like authentication, which is often a time-consuming hurdle for developers.[11] The platform automates much of the work involved in implementing authentication workflows and managing tokens for the more than 3,000 cloud applications and software tools it supports.[11] This allows developers to connect their AI agents to a wide range of business applications, including Gmail, Slack, and Salesforce, without needing to build each integration from scratch.[4][12] Composio is framework-agnostic, meaning it can work with popular AI development frameworks like OpenAI's Agents SDK, LangChain, and Vercel AI SDK, giving developers flexibility in their technology choices.[11][10][13] This focus on simplifying the developer experience is intended to compress the workflow for building complex agents from days into just a few minutes.[11]

The implications of Composio's approach could be significant for the future of AI in the enterprise. By enabling AI agents to learn and adapt, the technology moves beyond task automation to creating intelligent systems that can act as genuine partners in the workplace.[1] This shift addresses a fundamental gap between the promise of AI and its current capabilities. The ability of agents to accumulate practical knowledge at the scale and speed of software could unlock new levels of productivity and innovation.[1] The platform has already gained traction, with over 100,000 developers and more than 200 paying customers, including notable companies like Glean.[1][4] The company is already generating seven-figure revenue, indicating a strong market demand for solutions that make AI agents more reliable and effective.[1][4]

In conclusion, Composio's successful funding round highlights a crucial area of development in the artificial intelligence landscape. The company's focus on enabling AI agents to learn from experience directly confronts a major obstacle to their enterprise adoption. By building a shared knowledge infrastructure, Composio is not just aiming to make AI smarter in isolation, but to foster a collaborative learning environment where agents continuously improve through practice.[1] If successful, this approach could accelerate the transition of AI from impressive demos to transformative tools that are deeply integrated into the core workflows of businesses, fundamentally changing how work is done. The journey is still in its early stages, but the investment in Composio signals a strong belief that the future of enterprise AI lies in its ability to learn.