Ambient.ai Review, Pricing & Features

Ambient.ai turns existing security cameras into an AI threat-detection system. Explore its features, funding, pricing model, and enterprise use cases.

Category
Automation
Pricing
custom
Verified
Not yet
Last updated
July 19, 2026
Founded
2017
Headquarters
Palo Alto, California, United States
AI

What Is Ambient.ai

Ambient.ai is an AI-powered physical security intelligence platform for large enterprises, founded in 2017 by Vikesh Khanna and Shikhar Shrestha and based in Palo Alto, California.

Rather than requiring new cameras or sensors, Ambient.ai connects to a company's existing camera infrastructure and access-control systems, applying computer vision and a proprietary vision-language model (Ambient Pulsar) to detect and explain security-relevant events in real time.

The platform is aimed at enterprise security operations centers that are overwhelmed by manual video monitoring and high false-alarm rates from legacy systems.

Key Features

Foundation provides always-on AI monitoring across camera feeds, automatically flagging activity relevant to security teams rather than requiring humans to watch every screen.

Advanced Forensics reconstructs incidents by connecting people, locations, and context, helping security teams understand what happened and why far faster than manual video review.

Access Intelligence correlates video footage with access control system data (badge swipes, door events) to dramatically reduce false alerts, and Threat Detection applies more than 150 verified threat signatures to catch specific risk patterns like tailgating or unauthorized entry.

Pricing

Ambient.ai does not publish standard pricing; it sells to enterprise customers through a custom, quote-based sales process typically scoped around number of camera feeds, sites, and which product modules are deployed.

Prospective customers must contact Ambient.ai's sales team directly for a tailored quote and implementation plan.

Key Features

Pros & Cons

Pros

  • Works with existing camera and access-control infrastructure, avoiding costly hardware replacement
  • Backed by substantial venture funding, including strategic investment from access-control leader Allegion
  • Reduces false alerts significantly through cross-referencing video and access data
  • Serves large, recognizable enterprise and institutional customers
  • Purpose-built AI model focused specifically on physical security use cases

Cons

  • Pricing is not public and requires a custom enterprise sales process
  • Designed for large organizations, likely not cost-effective for small businesses
  • Effectiveness depends on the quality and coverage of a customer's existing camera network
  • As an AI surveillance tool, may raise privacy and governance considerations for some organizations

Pricing

Frequently Asked Questions

Is Ambient.ai the same company as Amberol?

No. Ambient.ai is an AI physical security company for enterprises; Amberol is an unrelated open-source Linux music player. The names sound similar but the products have nothing in common.

Does Ambient.ai require new cameras?

No. Ambient.ai is designed to integrate with a customer's existing camera and access-control infrastructure rather than requiring new hardware.

Who founded Ambient.ai and when?

Ambient.ai was founded in 2017 by Vikesh Khanna and Shikhar Shrestha and is headquartered in Palo Alto, California.

How much does Ambient.ai cost?

Pricing is not publicly listed. Ambient.ai uses a custom, quote-based enterprise sales process based on deployment scope.

What industries use Ambient.ai?

Customers span corporate campuses, education, manufacturing, data centers, energy and utilities, healthcare, financial services, and cultural institutions like museums.

How much funding has Ambient.ai raised?

Ambient.ai has raised roughly $146 million across multiple rounds, including Series A and B rounds led by Andreessen Horowitz and a $20 million strategic investment from Allegion Ventures.

What is Ambient Pulsar?

Ambient Pulsar is Ambient.ai's proprietary vision-language model, described as an always-on AI reasoning system built specifically for physical security applications.

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