Easy, cost-effective and
Xailient’s mission is to make Computer Vision easy, cost-effective, and safe. Our solutions support technical, governance, and revenue operations teams with integrated technology and quantitative dashboards.
Learn more about Xailient products, industry best pratices, and regulatory requirements.
Industry Reports
Park Associates Whitepaper:
Face Recognition and the Smart Home
Park Associates Whitepaper:
Video at the Door
Whitepapers
How to Enter and Win the Smart Video Doorbell Market
Face Recognition and Casinos
Navigating Biometric Privacy Regulations
Videos
Xailient Casino Eye-D
Stop Card Fraud
Find the Hidden VIPs in your uncarded play
Card-Free VIPs for a more natural experience
Xailient: Manageable, Privacy Safe Edge AI
Xailient and Sony on the Future of Edge Computing: A Documentary
Strategies for Recurring Revenue in Consumer Electronics
Customer Lifetime Value
Case Studies
Xailient with Movidius on Raspberry 3B – Better Together
Unlock Significantly Smaller Carbon Footprint with Xailient over Cloud AI
Xailient Reduces Drove Data Usage by 94%
Eval Kits
For tech engineers and product managers to evaluate implementation of Xailent’s Orchestrait™ solution.
Ingenic Eval Kit
Ingenic Sales Kit
Face Recognition Eval Kit
Camera Providers: Add Privacy-safe Face Recognition, over-the-air update, and remove manageability to your cameras in 7 days.
Xailient supports a wide range of camera hardware. Our SDKs provide AI optimized for specific constraints and fine-tuned to customers’ use cases. Orchestrait unifies management of diverse fleets while optimizing for each SKU.
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Run Edge AI on your existing device in 1 week
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Deploy Face Recognition in 1 month
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Develop & win with your AI “secret sauce”
Blogs
Learn How to Create a Simple Face Tracking System in Python
Face tracking is detecting a set of faces in frame 1 of a video, establishing a correspondence between the frames, and maintaining a unique ID for each of the faces throughout...
How to Set Up Real-Time Face Detection on Raspberry Pi
A step-by-step guide to implement real-time face detection on a Raspberry Pi running 24 frames per second. In this post, I will guide you through a step-by-step process of...
Cloud Computing versus Real-Time Edge Computing
“Edge computing market size is expected to reach USD 29 billion by 2025” In this decade there has been a transformational movement from on-premise computing to cloud computing,...