Lumeo, a designer of computer vision solutions, announces the launch of its FREEmium self-serve environment. Starting immediately, users can signup for a free Lumeo Starter account and start building vision AI solutions without permission, and without significant time, cost, or hardware investments.
Vision AI & video analytics platform
Lumeo looks to significantly accelerate AI analytic deployment by offering developers, solutions engineers, and technical security teams a “no-code”/“low-code” vision AI & video analytics platform that helps transform, analyse, and act on video data.
The FREEmium self-serve environment unlocks permission-less innovation for teams building and delivering video and vision AI solutions.
Security challenges
Security teams and integrators are often limited to reselling existing solutions because of the technical hurdles
Currently, development teams that want to embed computer vision or video analytics into their products have no choice but to build in-house or cobble together a “vision stack” from various vendors, capabilities that include: camera management, moving & storing the video between local storage/cloud/end-user devices, edge processing, training & inferencing using AI models, and business logic. This drives up the cost of innovation and time to market.
On the other hand, security teams and integrators are often limited to reselling existing solutions because of the technical hurdles & high price points of tailor-made analytics.
Video analytics builder
Lumeo makes this easy with a video analytics builder that provides web-based drag-and-drop tools, pre-made and custom vision AI models, and third-party integrations to create custom vision AI solutions for various use cases without requiring any code.
Lumeo also supports APIs, custom code, and OpenCV to meet unique needs. These solutions can process video in real-time from any camera or stream, and run on-prem, on the edge, or in the cloud.
Applications in various fields
Teams that are building AI models for video analysis can also use Lumeo to capture data from the field
Lumeo currently powers a wide range of use cases for large retail malls, parking facilities, commercial buildings, and critical infrastructure installations.
Lumeo makes it easy to track occupancy; monitor traffic flow; check vehicle speed; recognise human faces, licence plates, and vehicle makes/models; and identify loitering, crowd gathering, and line crossing, just to name a few of the building blocks.
Teams that are building AI models for video analysis can also use Lumeo to capture data from the field, deploy resulting models in the field and connect them to business logic.
Cloud GPU trial
Lumeo’s new freemium model is designed to help builders of all sizes, including independent developers, R&D teams, startups, small businesses, and large enterprises, to experiment with AI and see its potential.
Every new Lumeo account comes with a cloud GPU trial to enable solution builders to get started building in the cloud, and then continue running analytics in the cloud or deploy on-site.
Starter, business, and enterprise plans
For Enterprises and as volume scales, businesses can upgrade to annual, committed-pricing plans
The Starter plan (free forever) allows you to develop, tinker and experiment with vision AI, while the pay-as-you-go Business plan adds a robust set of capabilities for commercial deployments without long-term commitments.
For Enterprises and as volume scales, businesses can upgrade to annual, committed-pricing plans, and unlock Enterprise-grade capabilities.
Modern compute engine
"At Lumeo, we are building the ‘modern compute engine’ for video and making it accessible to builders without deep technical expertise or deep pockets," said Shah.
“Lumeo’s Lego®-like building blocks shrink development time from months to hours or minutes. Experimentation is a prerequisite to innovation, and Lumeo’s ultimate goal is to lower the barrier to experimenting and building with video and vision AI which we believe will drive the industry forward, accelerate growth and application towards new use cases,” added Shah.
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