Edgify Raises $9M Series A+ to Bring Edge AI Loss Prevention Beyond Grocery Retail

In August 2026, London-based edge AI infrastructure company Edgify raised $9 million in Series A+ funding to accelerate the rollout of its decentralized AI platform for physical retail and expand into new industrial sectors. The round was backed by Rank Ventures and Mangrove Capital Partners, bringing the company's total funding to $25 million (approximately €21.6 million).

Funding Details at a Glance

Detail	Amount / Entity
Series A+ round	$9 million (approx. €7.7M / £6.7M)
Total funding to date	$25 million (approx. €21.6M)
Lead investors	Rank Ventures, Mangrove Capital Partners

Expansion Targets Beyond Grocery

Edgify has already found strong traction in grocery retail, where its computer vision models help retailers identify theft and improve operational efficiency. With the new capital, the company is initially targeting three additional sectors:

• Transportation
• Logistics
• Manufacturing

Broader physical retail categories — including quick-service restaurants (QSR), distribution centers, and apparel — are also planned for expansion.

How Edgify's Edge AI Platform Works

Edgify's platform is a hardware-agnostic, decentralized edge AI infrastructure that runs computer vision and machine learning models directly on in-store devices — such as self-checkout kiosks, cameras, scales, and point-of-sale systems — rather than sending data to the cloud.

Key Technical Mechanics

• On-device training & inference: Models are deployed and trained locally on edge hardware inside each store, so all video and transaction data stays on-site.
• Self-learning models: The system continuously learns from new in-store scenarios without requiring manual re-training or cloud connectivity.
• Federated orchestration: The platform connects and orchestrates AI models across all edge devices in a store, and can share learnings across store locations without moving raw data.

Real-World Use Cases

Loss prevention: The platform detects scan avoidance, "skip-scanning" at self-checkout, item misidentification, and other theft behaviors in real time by analyzing video and transaction data locally. It flags suspicious activity instantly, without the latency or privacy concerns of cloud-dependent systems. According to the company, over 8,000 devices are already live across 12 countries.

Real-time staff assistance: Employees receive on-device alerts about potential theft or checkout errors as they happen, enabling immediate intervention. The same infrastructure can power customer assistance features, such as item lookup or checkout guidance, all processed at the edge.

Why This Matters for Retail and Industrial AI

Edgify's approach addresses a growing tension in physical retail: the pressure to reduce shrink and improve operational efficiency versus the cost, latency, and privacy concerns of cloud-reliant AI systems. By keeping intelligence on the edge, the company argues that AI can operate at the speed of commerce while respecting data sovereignty — a value proposition that appears to resonate with investors as the company prepares to take its platform from grocery aisles to factory floors and distribution centers.