NEW YORK, April 23, 2026 — Shade has raised $14 million in a new funding round led by Khosla Ventures. The round also included participation from Construct Capital and Bling Capital. The investment brings the company’s total funding to around $20 million, following earlier backing from investors such as General Catalyst, SignalFire, and Contrary.

The capital will support further development of Shade’s platform, which focuses on search and retrieval systems for video content. The round closed in March.

System Built to Search Video Using Plain Language

Shade is building a system that allows users to search video libraries using everyday language. Instead of relying on manual tagging or metadata fields, users can type natural language queries to find specific moments in video files.

The system processes video content and breaks it down into searchable elements. These include spoken dialogue, visual cues, and contextual signals. This information is then indexed so it can be queried later.

Shade’s goal is to make large collections of videos easier to access without requiring detailed manual tagging or structuring. This is particularly relevant for companies that store large amounts of footage across different projects.

Demand Grows as Video Volumes Expand

The rise in AI-generated content and digital video production has increased the size of video libraries across many organisations. This includes media companies, marketing departments, and enterprises that store training or internal communication content.

As these libraries grow, it becomes harder to locate specific clips using traditional systems. Keyword tagging alone often fails to capture context, especially in long or unstructured video files.

Search systems that interpret audio and visual content directly are being developed to address this gap. These systems aim to make video retrieval faster and more precise by analysing content at a deeper level.

Investor Interest Tied to AI Infrastructure Tools

The participation of firms such as Khosla Ventures and General Catalyst reflects continued investment in AI infrastructure tools rather than only consumer-facing applications.

Video search sits within a broader category of software focused on managing unstructured data. This includes text, images, and audio, with video representing one of the most data-intensive formats.

Investors are backing companies that build systems to process and index this type of data at scale. These systems sit between raw storage and user-facing applications, enabling faster access to information stored in large datasets.

Funding to Support Scaling and Model Development

Shade plans to use the funding to expand its engineering capacity and improve its underlying models. Processing video at scale requires significant computing resources, particularly for extracting and analysing audio and visual data.

The company is also working on improving search accuracy. This involves refining how the system interprets user queries and matches them with relevant segments in video files.

Another focus is scaling infrastructure so the system can handle larger volumes of video as more organisations adopt the product.

Shade Builds Video Search Infrastructure

Shade operates in a segment of AI focused on infrastructure for unstructured data. As organisations generate more video content, demand is increasing for systems that can organise and retrieve that material efficiently.

Video is more complex than text or images because it contains multiple layers of information, including speech, motion, and visual context. Systems that can process these layers and make them searchable are becoming more relevant in enterprise software stacks.

With $20 million in total funding, Shade is now working to expand its platform as video production and storage continue to grow across industries.