SeeChange

Name: SeeChange
Brand: SeeChange

Creating powerful edge to cloud, Vision AI solutions for retail

Est 2018|Raised $13.3M|7 Ref Customers

LinkedIn 3K|Website|FTEs 61|HQ Manchester, England, GB

MarketsPhysical Security Systems

01Competitive Landscape

Narrative analysis

- SeeChange vs Everseen: Everseen is described in public materials as focused on self-checkout shrink reduction with research based on large transaction volumes. SeeChange presents a broader set of in-store use cases (hazards, aisle tracking, exit tracking) which may be relevant when retailers prefer a single platform for multiple vision applications. - SeeChange vs Auror: Auror focuses on crime intelligence workflows rather than primary computer vision detection; many retailers deploy both detection systems and crime-intel platforms in parallel to address different LP operations. - SeeChange vs Focal Systems: Focal Systems emphasizes shelf availability and store operations optimization, which can overlap operationally if a retailer consolidates camera platforms for multiple use cases.

Market share and adoption trends

No authoritative public market-share data for retail loss-prevention vision AI platforms was found. The vendor notes inclusion in an industry analysts' list of innovators in computer vision applications; such inclusions are not endorsements and typically come with analyst-specific scopes and disclaimers.

	SeeChange	Everseen	Auror
Starting Price	Not publicly listed (sales-led)	Not publicly listed (enterprise)	Not publicly listed; vendor describes modular SaaS pricing
Recommended for	Retailers seeking camera-based, multi-zone loss and safety detection (checkout + aisle + hazards)	Large retailers prioritizing self-checkout shrink reduction at high transaction volumes	Retailers prioritizing organized retail crime (ORC) intelligence and case management
Key Strength	Platform approach intended to reuse cameras and provide configurable rules and partner integrations	Checkout-focused solutions with published research based on large transaction samples	Case-management workflows, incident reporting, and law-enforcement collaboration network
Key Weakness	Limited public independent product reviews; pricing opacity; limited publicly available audit artifacts	Focused primarily on checkout use cases rather than broader aisle/hazard detection	Not focused on computer vision for detection; complementary rather than directly substitutable

01Competitive Landscape

Narrative analysis

SeeChange vs Everseen: Everseen is described in public materials as focused on self-checkout shrink reduction with research based on large transaction volumes. SeeChange presents a broader set of in-store use cases (hazards, aisle tracking, exit tracking) which may be relevant when retailers prefer a single platform for multiple vision applications.
SeeChange vs Auror: Auror focuses on crime intelligence workflows rather than primary computer vision detection; many retailers deploy both detection systems and crime-intel platforms in parallel to address different LP operations.
SeeChange vs Focal Systems: Focal Systems emphasizes shelf availability and store operations optimization, which can overlap operationally if a retailer consolidates camera platforms for multiple use cases.

Market share and adoption trends

	SeeChange	Everseen	Auror
Starting Price	Not publicly listed (sales-led)	Not publicly listed (enterprise)	Not publicly listed; vendor describes modular SaaS pricing
Recommended for	Retailers seeking camera-based, multi-zone loss and safety detection (checkout + aisle + hazards)	Large retailers prioritizing self-checkout shrink reduction at high transaction volumes	Retailers prioritizing organized retail crime (ORC) intelligence and case management
Key Strength	Platform approach intended to reuse cameras and provide configurable rules and partner integrations	Checkout-focused solutions with published research based on large transaction samples	Case-management workflows, incident reporting, and law-enforcement collaboration network
Key Weakness	Limited public independent product reviews; pricing opacity; limited publicly available audit artifacts	Focused primarily on checkout use cases rather than broader aisle/hazard detection	Not focused on computer vision for detection; complementary rather than directly substitutable