Uptime’s AI-in-a-box offers turnkey enterprise-grade AI —without the cloud

In a bid to deliver secure, compliant generative AI (genAI) to business teams without the need for a cloud service, Uptime Industries last week unveiled Lemony. It’s a turnkey stackable device that comes preloaded with multiple large language models (LLMs) and can serve up to five users per node, connected directly to a PC or to a LAN with no internet connectivity. As business needs expand, multiple nodes can be connected into a cluster, with automatic failover. Lemony says a four-node cluster can support up to 50 users and comes with six pre-loaded genAI models.

IBM is working with the company to deploy its Granite AI models on Lemony nodes. Other available LLMs include Llama-3.1, Llama-3.2, and Mistral. In addition, JetBrains is integrating its coding models and tools into the Lemony node to allow software developers to leverage its intelligent development features. (For maximum performance, each node contains a neural processing unit (NPU), an AI accelerator cluster and a CPU.)

Other pre-loaded functions include retrieval-augmented generation (RAG), and the ability to create AI assistants to help with tasks such as analyzing documents. 

Data is loaded onto a Lemony node in one of three ways, with only a knowledge graph retained, said Uptime CEO and cofounder Sascha Buehrle. “We are uploading, analyzing, indexing, and deleting the data,” he said. 

Users can also connect to their data via an API, with which the data is indexed, or connectors that integrate directly with business applications.

One early customer, Alexander Göbel, legal tech officer at Niederer Kraft Frey AG in Zurich, Switzerland, called setup quick and easy. “You can be up and running with an on-premises solution within minutes rather than within days/weeks,” Göbel said via email. Transferring documents to the device, where they’re indexed for use via RAG, is done by uploading via the Lemony browser.

 “We are currently working on a SharePoint connector to make the process of uploading even simpler, as the latest version of the node provides for a limited API,” Göbel said.

Because the nodes are not connected to the internet, Lemony updates are provided quarterly via individually keyed encrypted USB keys. Each key will only work with its designated node. The update also resets a secure timer to ensure that the user’s subscription is still valid; if not, the node locks, with data fully encrypted.

Lemony offers a two-week free trial, and Uptime says it already has more than 300 customers in Switzerland, Germany, the UK, and the US. Subscriptions start at $499 per month for a single node accessed by up to five users, billed annually; the setup includes the node, software, apps for Windows and Mac, and technical support. 

Cautious optimism

Analysts found the concept appealing, and were cautiously optimistic about the device itself.

“Uptime is tapping into a real need for any regulated industry,” said Matt Kimball, vice president and  principal analyst for Datacenter Compute & Storage at Moor Insights & Strategy. “And in Europe this is most companies. What we effectively have is a genAI appliance. 

“If I am a CIO or an IT professional at a smaller law firm,” Kimball said, “I immediately see the value in this Lemony platform…. I can see Lemony being attractive at the departmental level [at a larger firm] or for an SMB that values/requires data privacy. And the ability to use AI without the need for IT is super interesting.” 

“The on-prem AI edge is an underserved segment,” said Gartner Vice President Analyst Chirag Dekate. “Most genAI infra[structure] today assumes cloud-first. There is an opportunity for localized solutions, especially if latency, cost, or compliance are concerns. If Uptime provides automated [machine learning] ops, energy optimization, and support for open-source models, it might reduce the complexity barrier enough to attract mid-sized enterprises and public sector clients. Global expansion of AI regulations will make ‘keep your AI local’ more attractive in the next two to three years.”

Wyatt Mayham, lead AI consultant at Northwest AI Consulting, agreed. “We work with clients who refuse to put sensitive data in the cloud, even if it’s Azure + OpenAI, which never touches the public web or trains the models,” he said. “Clients often think they want true on-prem, but actually building an on-prem setup with GPUs, model hosting, orchestration, and RAG infrastructure is expensive, high maintenance, and usually way overkill for what they actually need. 

“This actually looks like a solid middle ground,” Mayham said. “It’s not full-scale enterprise infra, but it gives small teams a path to locally run LLMs, stay compliant, and avoid the cloud.”

“We don’t consider Lemony.ai as a replacement for all cloud-based AI systems,” Göbel said. “For ‘commodity data’ with lower confidentiality requirements, a turnkey cloud solution remains to make sense to us (in this case, access to internet information may be required, too). However, we are dealing with a lot of very sensitive and confidential information for which cloud solutions are not options. As a result, depending on the specific use cases, Lemony.ai and cloud-based solutions work very well in tandem.”

Lemony’s success will be influenced by how it’s positioned in the market, Dekate said. ”Uptime’s Lemony AI strategy will be limited if it’s positioned as a general-purpose AI appliance. But if Uptime focuses on narrow verticals with repeatable workloads — like retail, energy, or industrial monitoring — it may gain traction,” he said.

But there are “fundamental challenges in a packaged AI in a box experience (independent of a vendor): Packaging doesn’t solve talent gaps. Just because it’s in a box doesn’t mean it’s plug-and-play for everyone. AI model management, updates, and troubleshooting are still hard. Without model agility, customers may view it as a closed system, limiting experimentation and extensibility. [And] if Uptime isn’t controlling its hardware supply chain or relies on commodity boards, this may be hard to differentiate long-term.”

Kimball sounded a cautionary note: “I will counter with this one thing: if I were still in IT, I am not sure I would be allowing ‘AI appliances’ to populate my network.  If you thought shadow IT was bad with the cloud — holy moly!”