START: Andrey Gizdov, CEO & Co-Founder, OpenVector: "Vision Language Action Systems for the Physical World"

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There are over a billion cameras in the world. They can all see. Almost none of them can tell you what they saw.

Andrey Gizdov has been in computer vision since 2016, when CNNs were all the rage, researching real-time vision models.

He met his co-founder Vishal Urlam at a hackathon. His co-founder had deployed cameras and IoT devices across India's power grid to monitor it.

Then they went to conferences on cameras and intelligence and found the state of affairs grim.

From that point, they knew this was a company that was going to exist.

OpenVector connects what cameras see to what businesses do.

Connect an existing camera and describe a workflow in plain English:

Track a misplaced item.

Check that an SOP was followed.

Detect an unscanned item.

Turn an empty shelf into a restocking task.

When something needs attention, OpenVector can take the next step inside the software a business already uses - creating records, sending requests, updating tasks, or notifying someone to act.

Vision → Language → Action.

Doing that without replacing the existing camera infrastructure is the hard part.

Historically, bandwidth and compute pushed vision systems onto on-prem hardware. And ripping out a customer's existing setup doesn't scale.

Andrey says OpenVector has significantly reduced those requirements with almost no loss in accuracy. Today, the company describes its underlying technology as the world's fastest and lowest-bandwidth VLM engine.

During YC, they sold to major companies, including some of the biggest gas-station operators in the country.

The larger bet is that AI is moving out of the chat window and into the physical world.

OpenVector is building the layer between what a camera sees and what a business does next.


🎙️Andrey Gizdov, CEO & Co-Founder, OpenVector on Fondo START  

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01:39 Harvard and the path into computer vision

02:42 Vision, language, action systems

03:08 Typed commands into camera workflows

03:17 Warehouse and subway use cases

05:15 Why build it now

05:35 Meeting his co-founder

06:02 The camera conference

06:19 Getting into YC, second try

06:38 How they got the domain

07:45 Biggest YC lesson: sales

08:05 Client ROI and talking price

09:23 Why nobody solved this sooner

10:25 Cutting bandwidth and compute

11:22 Foundation models for vision

11:42 AI moving to the physical world

Check out openvector.com