Hatz AI has raised $24 million in Series A funding as the company looks to accelerate its growth in the managed service provider (MSP) market and expand the AI tools available to small and midsize businesses (SMBs) through channel partners.
Announced November 12, the funding round was backed by Nadia Partners, Vestigo Ventures, and The Private Shares Fund, with Josh Schertzer, partner at Nadia Partners and former Blackstone CTO, leading the investment.
The announcement follows a year of significant expansion for Hatz AI. The company said its active MSP partner count has tripled year over year, with revenue growing even faster. Its workforce has also expanded from 14 to nearly 60 employees.
Hatz now reports a partner network spanning thousands of MSPs across all 50 U.S. states, nine Canadian provinces, and nine countries.
Hatz AI plans platform and engineering expansion
Hatz positions its platform as an AI control plane that enables MSPs to deliver branded AI services while managing customer security, governance, spending, and access to multiple foundation models.
The company said it has issued more than 15,000 AI certifications globally as it works to help MSPs develop the technical expertise needed to build AI practices.
The new investment will support further development of Hatz’s automated model-routing technology, benchmarking capabilities, and internal engineering infrastructure.
Hatz AI also plans to expand its forward-deployed engineering team, which works directly with partners, as well as its research and optimization teams.
“AI transformation is existential for small and medium-sized businesses, but technology alone won’t make a business AI native — SMBs need help from people they trust,” said Jimmy Hatzell, CEO and co-founder of Hatz AI.
“By giving MSPs full control over governance, spend, and deployment, we’re making it possible for every small business to become AI native,” Hatzell continued.
Hatz builds on a year of MSP-focused AI launches
The funding follows several product announcements aimed at helping MSPs move beyond AI experimentation and establish recurring managed AI services.
In August, Hatz AI introduced its Activate platform to help providers assess customer AI readiness, identify shadow AI risks, and develop adoption strategies.
Earlier this month, the company launched Hatz Spaces, adding collaborative AI workspaces that allow SMB employees to share conversations, workflows, and project information under MSP-managed governance controls.
The product expansion reflects a strategy Hatzell outlined in an August interview with Channel Insider, when he warned that customer AI adoption was advancing faster than formal security and management practices.
“Business integration is happening before security and controls,” Hatzell said at the time.
“At the beginning of 2026, an end customer might have said, ‘Hey, we tried AI,’ or ‘We’re interested in it.’ Now it’s hard to find a customer who has never used an LLM,” said Hatzell.
MSP AI services present growth and execution challenges
Hatz’s expansion comes as more MSPs pursue recurring revenue from AI deployment, governance, automation, and advisory services.
According to Informa’s 2026 MSP 501 research, 57% of surveyed MSPs expect AI to rank among their largest revenue growth areas over the next year, compared with 37% the previous year.
However, adoption does not necessarily translate into measurable returns. Recent Nerdio research covered by Channel Insider found that only 12% of surveyed MSPs reported measurable productivity improvements attributable to AI.
That gap creates an opportunity for vendors like Hatz that are building platforms specifically around MSP delivery requirements, including multi-tenant management, customer governance, and repeatable workflows.
For MSPs, the longer-term opportunity extends beyond reselling AI subscriptions. Providers that can demonstrate business outcomes, manage AI risks, and support ongoing adoption may be better positioned to build profitable managed AI practices.
Hatz’s latest funding suggests investors see potential in that channel-led model, although its continued growth will depend on whether partners can turn expanding AI adoption into sustainable services revenue.
READ MORE: Howard M. Cohen breaks down how MSPs can enable AI adoption in this guide to best practices.