Hatz AI Raises $24M Series A for MSP AI Builders

Jimmy Hatzell once expected small businesses and their IT providers to spend much more time fine-tuning their own AI models. In a February discussion published by Hatz AI, the CEO described how improving general-purpose models and tool use had changed that expectation, moving the company's work toward choosing and applying technology that kept changing around it.

Hatz AI now has a $24M Series A to expand that work through managed service providers, or MSPs, serving small and medium-sized businesses. Announced November 12, 2026, the New York company's financing is backed by Nadia Partners, Vestigo Ventures and The Private Shares Fund, with Nadia partner Josh Schertzer leading the deal.

Hatz's distribution choice puts the existing IT provider between changing AI capabilities and the business trying to use them. The new capital will support engineering, research and platform development around that relationship, including specialists who work alongside partners on implementation.

An AI business built around the service provider

Hatz AI sells the means to run an AI practice through an organization that already has customers to support. Its partners deliver the service under their own brands, while Hatz supplies the underlying platform and specialist help. The company says it has no competing direct-to-enterprise sales motion, a consequential commitment for a provider considering how much effort to invest in the relationship.

That arrangement gives the MSP several jobs at once. It must understand the client's work, choose an appropriate application, establish access and spending rules, and remain available as the deployment develops. These are operating responsibilities that can survive several changes of foundation model. The provider's knowledge of the business has somewhere to go besides another recommendation about which subscription to buy.

The Hatz partner program describes training, internal use, customer pilots and broader deployment as parts of getting started. Its support model includes recurring learning opportunities and help behind the partner, with the provider continuing to serve the customer. An MSP employee learning to implement a workflow is therefore developing a capability the firm can bring into its next account conversation.

The financing expands the resources behind that work. In a CRN interview, Hatzell described plans to double a roughly 60-person workforce, concentrating hiring in engineering, AI research and forward-deployed engineering. He also emphasized helping MSPs train builders within their own organizations.

The permission question follows the product home

Hatz AI combines access to multiple models with routing, workflows and controls for organizations using the platform. The value of that combination depends on decisions made inside the customer's business: which work the software handles, whose information it can reach, and how the resulting activity is supervised. A useful model becomes one ingredient in a service somebody has to operate.

Hatz's integration-access documentation makes the ownership issue concrete. Sharing an agent or workflow does not automatically share its creator's credentials for an external application. Access depends on Hatz permissions and the authority granted by the connected account, with connection patterns varying by integration.

For an MSP, that detail belongs in the implementation discussion with the client. An employee authorized to run a shared workflow may still need a separate connection to the system supplying its information. Making a feature available and deciding who may use an outside account are different administrative decisions, even when the person requesting the work experiences them as one task.

This is also where AI governance becomes a service relationship. The customer needs someone who can explain the intended behavior, configure the access and help diagnose a failure. Hatz's specialist engineers can support that process, while the partner retains the context of the account. The design places practical judgment close to the customer without requiring every provider to build the underlying AI platform.

Funding history gives the strategy a longer timeline

Jimmy Hatzell and Aidan Kehoe are identified as co-founders on the company's current leadership page. Hatz publicly launched in January 2024 alongside a $2.5M seed round led by Vestigo Ventures. That launch already centered the MSP as the route through which smaller businesses would receive AI services.

A February 2025 issuer filing reports $2,767,785 sold in an equity offering and records incorporation in 2023. These disclosures describe different moments in the company's history. The current announcement does not provide a reconciled lifetime financing total or a valuation, so neither figure can be constructed safely by simply adding the visible announcements together.

The company reports that its active MSP partner count has tripled year over year and that it has issued more than 15,000 AI certifications. These measures describe channel expansion and training activity; they leave the financial outcome inside each customer account largely undisclosed. Revenue in absolute terms, retention and partner-level profitability are absent from the announcement.

What can be seen is continuity in the route to market alongside changes in the technology being delivered. Hatzell's earlier expectation about custom models has evolved, while the partner remains central. Maintaining that relationship gives Hatz a place to introduce new capabilities without requiring the small business to reconstruct its implementation support each time the available models improve.

Where the next implementation gets staffed

DevCuration's coverage of Kindo's enterprise AI agent controls and Nebuly's work on enterprise AI ROI provides adjacent questions for this market: who can direct the software, and how does the organization understand the value of using it? Hatz approaches those questions through an intermediary responsible for helping a smaller business put the tools to work.

For an MSP owner, building that practice entails choices about staff time and the kinds of assignments the firm can accept. Training needs room in the working week; a promising workflow needs someone capable of implementing it. Those decisions connect the service menu offered to the client with the skills available inside the provider.

Hatz AI's new funding is intended to expand the technical support behind that transition. Its partner employees will still meet clients whose permissions, work habits and expectations differ, carrying more implementation knowledge into the next conversation about what the business wants its software to do.