From Trying AI to Running on It
AI use is now mainstream. What most people and businesses lack is AI that works across their models, tools, data and sites — privately, and without a specialist team to run it.
AI Is Everywhere.
The Intelligence Is Scattered.
Most AI users now juggle several assistants, each with its own subscription, chats and memory. Businesses use AI widely but have rarely woven it into how they work.
What This Means
Each assistant keeps its own chats, projects and memory. Files, CRM, email and messaging sit behind more connectors, and the same context is re-explained in every tool. Switching models, tools or infrastructure shouldn’t mean rebuilding your intelligence.
For businesses the gap is sharper: three in four small businesses use AI, but only about one in seven has it fully integrated. Chat is not the same as integrated work.
Model Choice, Privacy
and Managed Help
Organizations blend open and frontier models, worry about where their data goes, and find self-hosting hard. Their IT partners see the demand but rarely capture it.
Each Signal Maps to a Customer
🏢 Business Teams
76% use AI but 14% are fully integrated. They need agents working inside their CRM, inbox and campaigns — not another chat window.
👤 Individuals
Three assistants per user and 55% paying for AI means subscription and data sprawl.
💻 Builders
81% of large enterprises blend three or more model families. Builders need open and frontier models on the same services.
🔒 Owners
Privacy concerns and a self-hosting skills gap create demand for private and hybrid AI that someone else runs.
🤝 Partners
AI is the top client need for 48% of MSPs, yet only 13% monetize it. They need a platform they can resell and support.
Capacity Near Users Matters
AI has moved from pilots to production, and inference — running models every day — is now the recurring cost. Power and data-center build-outs lag that demand.
Workloads Run Where They Fit
No single location serves every AI workload well. Frontier models answer the hardest questions; open models on dedicated GPUs keep sensitive work private; on-site devices handle network services and latency-sensitive analytics close to users.
RevoFi combines all three: edge devices plus central GPU servers, on one account and one bill in dollars. Every 1,000 devices ships with a full AI server configured with 4× NVIDIA H200 NVL.
Large, Established
Customer Populations
Each segment RevoFi serves already exists at scale. These are counts of potential customers, not revenue estimates.
The Demand Is for Integrated AI
People and businesses have already adopted AI. What they are missing is one environment that keeps their context across models and tools, offers private options, and comes managed — directly or through the partners they already trust.
That is what RevoFi brings together: model choice, persistent knowledge, coordinated agents, connected services and private compute, on one account.
See How RevoFi Answers It
Explore the platform, or see why the timing matters now.
Research Sources
- Menlo Ventures — State of Consumer AI 2026 · 5,067 U.S. adults
- Goldman Sachs 10,000 Small Businesses — Survey of 1,256 participants · Jan–Feb 2026
- Andreessen Horowitz (a16z) — CIO survey · 100 Global 2000 companies · Jan 2026
- Cisco — Data Privacy Benchmark · 2,600 privacy and security professionals · Apr 2025
- Nutanix — Enterprise Cloud Index · 1,500 IT decision makers · Feb 2025
- Kaseya — State of the MSP · more than 1,000 MSPs · Apr 2026
- International Energy Agency (IEA) — Energy and AI · Apr 2025
- U.S. Census Bureau — Statistics of U.S. Businesses (SUSB) · 2022
- GitHub — Octoverse · Oct 2025