Latent AI unveils platform to speed & secure edge AI rollout

Latent AI has announced the launch of Latent Agent, an edge AI platform designed to simplify the management and security of deploying artificial intelligence models at the edge.

Built upon the Latent AI Efficient Inference Platform (LEIP), Latent Agent is designed to automate optimisation and deployment tasks, enabling developers to iterate, deploy, monitor, and secure edge AI models at scale. The company states that the new platform addresses the complexity issues that have made enterprise adoption of edge AI challenging.

Complexity of traditional MLOps

Traditional machine learning operations (MLOps) force developers to manually optimise models for specific hardware, often without a comprehensive understanding of device constraints. This can create pressure on teams, as optimisation workflows typically demand multiple specialists per hardware pipeline, and the complexity multiplies with each additional hardware target.

According to Latent AI, this challenge has extended go-to-market timelines to as much as twelve weeks and led to substantial resource overhead for many organisations, particularly those looking to scale across diverse edge devices such as drones and sensors.

"The rapid shift to edge AI has exposed gaps in traditional MLOps, slowing innovation and scalability," said Sek Chai, CTO and Co-founder of Latent AI. "Latent Agent eliminates the model-to-hardware guessing game, replacing weeks-long deployment cycles and scarce expertise with intelligent automation. This is a game-changer for enterprises racing to stay competitive."

Platform features

Latent Agent aims to streamline the lifecycle of edge AI, spanning exploration, training, development, and deployment across a range of hardware platforms. A key feature is its natural language interface, which lets developers set their AI requirements while receiving model-to-hardware recommendations from Latent AI Recipes. This knowledge base draws on 12TB of telemetry data compiled from over 200,000 device hours.

Within the platform, a Visual Studio Code (VS Code) extension has been introduced to incorporate these agentic capabilities into developer workflows, providing an interface for requirement gathering and deployment. Other capabilities highlighted include an adaptive model architecture that can autonomously detect performance drift in deployed models and take remedial actions, such as retraining or over-the-air updates, without human intervention.

Latent Agent's Recipes leverages automatically benchmarked model-to-hardware configurations, aiming to enable faster iteration and model deployment. The company states this accelerated approach will remove bottlenecks caused by manual processes and facilitate secure management of AI infrastructure at scale.

"The biggest barrier to edge AI at scale has always been the complexity of optimising models for constrained hardware environments," said Dan Twing, President and COO of Enterprise Management Associates, and Principal Analyst for Intelligent Automation. "Latent Agent addresses that challenge head-on. It streamlines the hardest part of edge AI—getting high-performance models running on diverse devices—so teams can move faster and scale confidently."

Business focus

Latent Agent is being presented as a tool to accelerate development timelines, allow autonomous operations, and support scaling. By reducing the need for deep machine learning or hardware expertise, the company claims deployment times can be shortened from twelve weeks to a matter of hours. The agentic platform's compile-once, deploy-anywhere function is said to support any chip, operating system, or form factor, thereby assisting in the management of thousands of edge devices simultaneously.

Furthermore, Latent Agent incorporates security measures such as model encryption, watermarking, and compliance with Department of Defence (DoD) security standards, designed to protect sensitive deployments.

"At Latent AI, we've always believed that edge AI should be as simple to deploy as it is powerful to use," said Jags Kandasamy, CEO and Co-founder of Latent AI. "Latent Agent represents the natural evolution of our mission—transforming edge AI from a specialised engineering challenge into an accessible conversation. By combining our proven optimisation expertise with agentic intelligence, we're not just making edge AI faster; we're making it possible for any developer to achieve what previously required a team of ML experts."

The new platform is now available to organisations seeking to improve deployment speed, operational autonomy, scalability, and security for edge AI models.