Composio သည် အတွေ့အကြုံမှ အမှန်တကယ် သင်ယူနိုင်သော AI ကို တည်ဆောက်ရန် ဒေါ်လာ ၂၉ သန်း စုဆောင်းခဲ့သည်။

Composio has secured $29 million in funding to address a long-standing limitation in AI: the inability for agents to improve through repetition. The $25 million Series A round, led by Lightspeed Venture Partners, brings total funding to $29 million and includes support from prominent industry leaders such as Guillermo Rauch (Vercel), Dharmesh Shah (HubSpot), and Soham Mazumdar (Rubrik), alongside firms like SV အိန်ဂျယ်, Blitzscaling Ventures, အော်ပရေတာ မိတ်ဖက်များနှင့် Agent Fund. Existing backers မြင့်မားသောမြို့တော် နှင့် စုပေါင်းရန်ပုံငွေ also returned for the round.

While AI agents have become more sophisticated in generating text and automating tasks, they remain fundamentally static—incapable of learning from past actions or adjusting their behavior over time. Composio aims to change that by developing an infrastructure layer that enables agents to accumulate knowledge, share it across systems, and improve continuously through real-world use.

AI That Doesn’t Just Act — It Learns

At the core of Composio’s technology is a shared skill layer that connects thousands of AI agents. When one agent learns how to handle a Salesforce edge case, debug a GitHub workflow, or scaffold a database using Supabase MCP, that knowledge doesn’t stay isolated. It becomes available to every other agent on the platform, creating a powerful network effect where the entire ecosystem improves collectively.

This marks a shift away from the isolated, one-off use of AI agents toward something more dynamic: a system that grows more capable with every interaction. Backed by a reinforcement learning layer tailored for enterprise software, Composio’s agents build intuition, not just follow instructions. As Ganatra explains, “The challenge isn’t making AI smarter in isolation—it’s giving AI the ability to accumulate practical knowledge the way humans do, but at the scale and speed only software can achieve.”

The infrastructure powering this includes support for multi-agent coordination, cross-platform authentication, and real-time scalability. It’s already processing millions of requests daily and serves more than 200 companies—among them Y Combinator-backed startups like April, Dash, and OpenNote, and growth-stage enterprises like Glean. Over 100,000 developers have already adopted the platform, and the company is generating seven-figure annual revenue.

A Shift in Enterprise Expectations

For years, AI has been sold as the future of work, yet most enterprise deployments remain underwhelming—capped by limitations in adaptability and context. Composio directly addresses this by enabling agents that don’t start from scratch each time but instead build on prior experience and community-contributed skills.

This shared intelligence significantly reduces the time it takes to build and deploy useful AI-powered tools. Developers no longer need to spend weeks building authentication flows or debugging integration edge cases. Instead, they can launch sophisticated agents in days—agents that arrive with embedded knowledge drawn from thousands of previous interactions.

Raviraj Jain of Lightspeed believes this model has massive implications: “They’re building the foundation for AI agents to become genuinely useful by learning from experience at scale. This is the missing piece between impressive demos and transformative deployments.”

AI လုပ်ငန်းအပေါ် ပိုမိုကျယ်ပြန့်သော သက်ရောက်မှု

Composio’s emergence signals a new direction for the AI ecosystem—one where progress is no longer confined to model size or prompt engineering, but instead hinges on how effectively systems can learn from use. By turning one agent’s success into another’s starting point, Composio introduces a compounding feedback loop that accelerates the usefulness of AI across industries.

This model could lay the groundwork for agent-to-agent collaboration, reusable skill libraries, and interoperable intelligence layers across platforms. In the future, developers might plug into a continuously evolving ecosystem where agents don’t just automate tasks—they become trusted digital collaborators that improve alongside the teams they support.

Much like the transition from raw infrastructure to cloud platforms reshaped software development, Composio’s shared learning layer has the potential to redefine what’s possible in applied AI. As enterprises seek more than just flashy demos, platforms that deliver true, evolving expertise will set the new standard.