Invisible AI

Name: Invisible AI
Brand: Invisible AI

A manufacturing vision platform to empower your workforce. Put people first with Invisible AI.

Est 2018|3 Ref Customers

LinkedIn 7K|Web traffic 20K|FTEs 80|HQ South San Francisco, California, US

MarketsQuality Assurance

01Competitive Landscape

Narrative competitive analysis

Where Invisible AI appears to provide strengths: - Manual operations visibility: the product is focused on measuring manual assembly work via motion analytics. - Edge/on-prem orientation: for organizations concerned about cloud-based video storage, on-device processing may reduce bandwidth and cloud storage considerations. - Automotive adoption signal: public announcements reference deployments with an automotive OEM. Where competitors may offer advantages: - Safety/EHS specialists (Intenseye / Protex AI / Voxel AI) may have broader libraries of safety-specific detections (PPE detection, restricted-zone monitoring, near-miss detection) and more visible EHS buyer engagement. - Operations platforms (Tulip) provide tools for workflow digitization, standard work enforcement, and integrations without relying on cameras, which can be preferable where camera deployment is not acceptable. Customer decision drivers (typical in this category): - Choose Invisible AI when downtime has high financial impact, manual work variability is a core constraint, and plant leadership will support camera-based analytics under a clear privacy and governance framework. - Choose a competitor when the primary priority is EHS event detection only, when camera deployment is culturally or legally constrained, or when a non-video connected-worker approach is preferred.

	Invisible AI	Protex AI	Tulip
Starting Price	Not public (contact sales)	AWS Marketplace shows directional per-site plus per-camera pricing	Public starting tier billed annually per interface with a minimum quantity; entry pricing is in the low-hundreds per interface range
Typical Use Case	Factories seeking human-motion visibility, automated time studies, root-cause/traceability, and on-prem video analytics	Safety-focused vision deployments (incident and risk detection) with clearer directional price anchoring	Connected worker / composable operations apps (quality checks, workflows, integrations)
Key Strength	Edge/on-prem architecture and a focus on human work analytics; public signals of automotive deployments	Clearer packaging signals via marketplace channels; safety-first positioning	Transparent entry pricing; broad workflow digitization beyond video
Key Weakness	Pricing opacity; adoption risk related to worker-monitoring optics; limited public third-party review footprint	Total cost of ownership can be high with per-site + per-camera fees; implementation overhead typical	Not a direct motion-analytics (camera-based) replacement; may require more app building and IT integration

01Competitive Landscape

Narrative competitive analysis

Where Invisible AI appears to provide strengths:

Manual operations visibility: the product is focused on measuring manual assembly work via motion analytics.
Edge/on-prem orientation: for organizations concerned about cloud-based video storage, on-device processing may reduce bandwidth and cloud storage considerations.
Automotive adoption signal: public announcements reference deployments with an automotive OEM.

Where competitors may offer advantages:

Safety/EHS specialists (Intenseye / Protex AI / Voxel AI) may have broader libraries of safety-specific detections (PPE detection, restricted-zone monitoring, near-miss detection) and more visible EHS buyer engagement.
Operations platforms (Tulip) provide tools for workflow digitization, standard work enforcement, and integrations without relying on cameras, which can be preferable where camera deployment is not acceptable.

Customer decision drivers (typical in this category):

Choose Invisible AI when downtime has high financial impact, manual work variability is a core constraint, and plant leadership will support camera-based analytics under a clear privacy and governance framework.
Choose a competitor when the primary priority is EHS event detection only, when camera deployment is culturally or legally constrained, or when a non-video connected-worker approach is preferred.

	Invisible AI	Protex AI	Tulip
Starting Price	Not public (contact sales)	AWS Marketplace shows directional per-site plus per-camera pricing	Public starting tier billed annually per interface with a minimum quantity; entry pricing is in the low-hundreds per interface range
Typical Use Case	Factories seeking human-motion visibility, automated time studies, root-cause/traceability, and on-prem video analytics	Safety-focused vision deployments (incident and risk detection) with clearer directional price anchoring	Connected worker / composable operations apps (quality checks, workflows, integrations)
Key Strength	Edge/on-prem architecture and a focus on human work analytics; public signals of automotive deployments	Clearer packaging signals via marketplace channels; safety-first positioning	Transparent entry pricing; broad workflow digitization beyond video
Key Weakness	Pricing opacity; adoption risk related to worker-monitoring optics; limited public third-party review footprint	Total cost of ownership can be high with per-site + per-camera fees; implementation overhead typical	Not a direct motion-analytics (camera-based) replacement; may require more app building and IT integration