Davra has been named in the 2026 Gartner® Magic Quadrant™ for Global Industrial AIoT Platforms. It is our seventh consecutive appearance, and we are one of only four vendors named in all seven of these reports. It is also the first in which AI sits at the centre of how Gartner defines this market. Sixteen vendors are named this year, three of them for the first time, and three from last year's report are absent.

From IIoT to AIoT

The most significant change from previous years is that Gartner has renamed the market. Until this year the report covered Industrial IoT platforms. This year it covers Industrial AIoT platforms, and the new name reflects the broader change happening in the market.

For most of the last decade, connectivity was the hard part. Pulling data off a mixed estate of controllers, meters, gateways and vehicles, across a dozen proprietary protocols, was the project. The data was the deliverable and a dashboard was the reward.

With the emergence of large language models and MCP servers, IoT has shifted to an enabling technology. Gartner now describes the industrial AIoT platform as the place where AI models are deployed and run against live operations, taking over work that legacy historians and dedicated OT analysis tools used to own.

IoT is now the enabler for AI; still playing an essential role, but no longer the end goal. Point an AI model at raw tags and it guesses. Point it at live asset data, where every reading is bound to its digital twin paired with detailed contextualisation, and you can hold it to an answer.

This year's criteria reward the vendors who have that running in production, with weight on AI agents, agentic orchestration and MCP support. Gartner listed market responsiveness as a Davra strength, referencing Glora, our no-code agentic AI service, and our native MCP server which are both generally available:

 "Davra has adapted to evolving market demands by shipping native agentic AI (Glora) with MCP integration, point-and-click anomaly detection, and on-premise SLMs for air-gapped environments."

A maturing market

Other significant changes in 2026 include the evaluation criteria. Marketing strategy dropped to its lowest ever weighting, citing a growing scepticism among industrial buyers towards vendor messaging. Buyers are instead placing value in measurable, demonstrable outcomes, proven ROI, and validated deployments.

Which makes one line in our write-up quietly satisfying. In the same year Gartner discounted vendor messaging across the market, it credited ours for being specific:

 "ROI-focused messaging supported by verified, numbers-backed case studies and co-marketing programs with key alliances like AWS, Cisco, and the European Space Agency."

Sales strategy came down too. Direct selling matters less as buyers leverage integrated partner ecosystems more. Vendors are now judged on how well they enable and co-sell through systems integrators, OEMs and technology partners.

Overall viability went up, because buyers want evidence of ten-year investment horizons before committing an operation to a platform. Pricing transparency and partner-friendly terms now count for more than sales muscle.

Read together, that is a market leaving the pilot phase. Gartner has cut the weight on marketing and raised the weight on whether you will still be here in a decade. Those are the criteria of buyers who have been sold plenty and now want proof.

Deploy anywhere, including offline

Gartner described our deployment footprint like this:

 "The platform features a deploy-anywhere footprint, operating with identical functionality across public clouds (AWS, Azure), private in-region clouds (Alibaba Cloud in China), on-premises datacenters, and fully air-gapped or disconnected edge environments."

"Identical functionality" is the phrase that matters. Most platforms out there offer a cut-down edge version with fewer capabilities, no models, and no agents.

We do not run a cut-down version. The same platform, the same applied AI models and the same governed agents run in public cloud, in a dedicated in-region private cloud, in your own datacentre, and on a site with no connection at all. Davra self-manages its own bundled data stack rather than renting one from a hyperscaler. There is no managed cloud service underneath to swap out when you go offline.

Both ends of that range are in production today. LI-COR runs its entire cloud service on Davra, including a dedicated in-region deployment in China, while a US federal agency runs governed alert triage in a fully air-gapped environment.

What Gartner rated strongest

Gartner named customer experience as one of three Davra strengths, citing "automated customer self-service support" delivered through a "product-grounded generative AI assistant".

Two findings from the companion Critical Capabilities research stood out.

• Predictive maintenance - Gartner identified this as Davra's strongest use case, "powered by asset-centric digital twins, multivariate machine learning, and closed-loop workflow automation." Finding the fault is half the job. Our platform also writes the pre-filled, prioritised work order into SAP, IBM Maximo or ServiceNow.
• Application enablement - Gartner found this to be Davra's strongest capability of all. It is the layer OEMs and partners use to build and sell their own branded industrial software on Davra.

Outlook

Davra is positioned as a Niche Player in this Magic Quadrant. As small company in a field of very large ones, our customers buy us for three things: operational outcomes, the freedom to build anything and deploy it anywhere, and governed AI at the leading edge.

As we look to 2027, our roadmap is incredibly exciting: more capable agentic AI through Glora, wider MCP tooling, small language models close to the asset, and satellite Earth observation through the ESA-co-funded Anganode programme.

If you want to see what this could look like for you, talk to us about your operation (opens new window).

Read the full Gartner report on gartner.com.

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