Zaro has launched with $5.1 million in pre-seed funding to build what it describes as a shared memory platform for AI agents. The round was led by Cherry Ventures, with participation from Flourish Ventures, The Players Fund, Octopus Ventures, Evertrue Capital, and a group of angels. The company aims to help businesses retain and grow the institutional knowledge created by their AI systems, rather than allowing that intelligence to remain locked inside third-party software platforms.
Founders Bring Enterprise AI Experience
Zaro was founded by Michael Bajwa and Qian Zheng, two early team members at Convergence who helped build Proxy, an AI agent designed to operate across software without relying on API integrations. Bajwa was the company’s first product hire and helped scale Proxy from zero to $1 million in annual recurring revenue within ten weeks. Zheng, Convergence’s first engineering hire, built the production system behind the product from the ground up.
Convergence was acquired by Salesforce less than a year after launch, after which the team contributed to Agentforce. The product has since become a major part of Salesforce’s AI strategy and is now generating $1.2 billion in annual recurring revenue, according to the announcement. That experience shaped the founders’ view that enterprises are helping vendors accumulate valuable operational intelligence while failing to preserve it for themselves.
Building a Company-Owned Context Layer
Zaro’s central thesis is that company knowledge should compound inside the organization that creates it. The platform is designed to act as a shared context layer where agents, applications, and company data can operate in a closed loop. In a LinkedIn post announcing the launch, Bajwa described this context layer as future infrastructure that every company will need, comparing it to the role databases play today.
The company argues that most AI agent systems still work in fragmented ways. One agent completes a task and passes an output to another, but useful context often gets lost between systems, tools, and workflows. Zaro is attempting to replace that relay-style model with a shared space where agents can read from and write to the same pool of organizational knowledge.
Moving Beyond Connectors
A key part of Zaro’s approach is reducing dependence on traditional software connectors. Many enterprise AI tools rely on integrations between customer relationship management systems, email platforms, messaging tools, document repositories, and other applications. Zaro instead positions the company itself as the central environment into which agents plug, allowing emails, call recordings, Slack conversations, and documents to exist in one shared layer.
Cherry Ventures said this approach stood out because it addresses a practical barrier to AI adoption in the workplace. The firm noted that many enterprises are experimenting with agents, but far fewer are deploying them at scale because real business work depends on messy, distributed, and historically rich context. Without shared memory, agents may perform well in isolated tasks but struggle when asked to operate across the full complexity of a company.
Investor Conviction and Early Use
Cherry Ventures said it was impressed by the speed of Zaro’s development, noting that Bajwa and Zheng showed a working product only three weeks after the firm invested. The venture firm also became an early user of the platform and said Zaro helped it replace several internal tools. According to the announcement, Cherry used the product for workflows including event research and eventually cut 15 long-running software subscriptions.
For investors, the funding round is also a bet on where value will accumulate in enterprise AI. As models become more widely available and interchangeable, Zaro argues that the durable advantage will sit in the proprietary context companies build around their own operations. Zheng summarized the company’s position with the phrase, “Context compounds. Models commoditise. The platform does not.”
Zaro is entering a crowded enterprise AI market, but it is targeting one of the sector’s most persistent problems: how companies preserve and reuse the knowledge generated by agents. By building a shared memory layer owned by the business, the company wants to shift the benefits of AI-driven learning away from software vendors and back to customers. With fresh funding, experienced founders, and early investor adoption, Zaro is positioning itself as infrastructure for the next phase of enterprise AI.