GYRUS AI

Gyrus AI is a Pioneer in developing ready-to-deploy AI/ML models and frameworks for Automated video Anonymization, processing and analytics. Our solutions include Media Asset Management Search, Program Recommendation, Video Anonymization, Virtual Ads, and AI Dubbed Lip Sync.

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Key Media and Entertainment Trends from NAB Show 2026.

Discover NAB Show 2026 trends with Gyrus AI. See how Semantic Media Search and Virtual Product Placement transform core media workflows.

How are broadcasters and streaming platforms preparing for the next wave of AI-powered media workflows?

Insights from NAB Show 2026 reveal a clear shift toward semantic search, contextual monetization, and production-ready AI infrastructure.

See what industry leaders were discussing at the event

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Why Video Intelligence Is Transforming Media Infrastructure

Learn how Gyrus AI transforms media workflows with video intelligence, powering media asset management, semantic search, and virtual ad plac

Media companies are sitting on massive video archives—but most of that content remains practically unusable.

Why?

Because traditional search relies on manual tags, incomplete metadata, and endless scrubbing through footage.

As video libraries grow across OTT, streaming, sports, and digital media, the real challenge is no longer storage.

It’s discoverability.

We’ve published a new blog on how AI-powered video intelligence is helping media companies transform archives into searchable, monetizable assets.

See It Live at NAB 2026.

This week at NAB Show 2026 in Las Vegas, Gyrus AI will be demonstrating how video intelligence can transform media workflows.

We’ll be showcasing:

Semantic Media Search: AI-powered video discovery

Virtual Product Placement: Scalable contextual brand integration

If you’re attending NAB and want to explore how these technologies can work with your content pipeline, we’d love to connect.

Visit us at Booth W2300K – AI Innovation Pavilion

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Visit Gyrus AI at NAB Show 2026, Las Vegas (Booth W2300K). Explore AI-powered semantic video search, in-scene ads & media management solutio

NAB Show Isn’t Just a Trade Show. It’s Where the Media Industry Comes to Find Solutions to Its Real Problems.

Every April right when spring settles over Las Vegas, the people who actually build the media industry – editors, broadcast engineers, streaming architects, ad tech leads show up at the NAB Show. Their goal isn’t vague. They’re there to spot real problems in how media gets made. The show helps them to figure out what’s actually broken and who’s fixing it.

The latest 2026 edition, running from April 18–22 at the Las Vegas Convention Center has an unmistakable theme running through it: AI isn’t experimental anymore. It’s operational. Sessions for this year feature real deployments from Microsoft, Google Cloud, and BBC Studios – not just demos, but real-world impact.

A second AI Innovation Pavilion appears at NAB Show 2026 – a sign of how quickly the conversation has shifted. Instead of asking what AI means, people are now asking where to start using it. More importantly, the focus is moving from experimental AI to scalable, production-grade deployments that deliver measurable ROI. The new space on the floor reflects that change.

We’re also here for exactly that conversation. Gyrus AI takes space at Booth W2300K inside the AI Innovation Pavilion, showing off a pair of tools built sharp for real problems today’s media teams face daily. One speeds up how quickly clips get found, while the other slips ads into view so smoothly they don’t yank attention away.

Semantic Media Search – Because “Search by Tag” Was Always a Lie:

Here’s the real situation in most media organizations today:❌ The Old Way✅ With Semantic Media SearchEditor needs a clip of “a crowd cheering at sunset”Types: “crowd cheering at sunset, outdoor stadium”Types in keywords – gets 4,000 unrelated resultsAI understands the meaning, not just the wordsSearches across 6 different folder structuresReturns contextually matched results in secondsEventually calls a colleague who “might remember where it is”Timestamps exact moments within each clip2–3 hours later, maybe finds itDone in under 5 minutes

The problem isn’t just storage. It’s retrieval. And retrieval has always been broken because traditional media asset management search systems were built around keywords and manual metadata, both of which require human effort to be accurate, and humans aren’t consistent.

Manual tagging becomes impractical and expensive at large scales. Humans make mistakes and miss relevant details.

What Makes It Actually Different?

This isn’t keyword search with better synonyms. It’s a different architecture altogether:

Text Queries  |  Image Queries  |  Audio Understanding  |  No Manual Tagging  |  No Pre-existing Metadata  |  Knowledge Graph Powered  |  Domain-Trained AICapabilityTraditional MAM SearchGyrus AI Semantic Media SearchSearch by natural languageRequires exact keywordsUnderstands meaning & contextSearch by imageNot supportedUpload an image, find similar scenesAudio content searchNot supportedSearches spoken words, music, toneRequires pre-taggingYes – ongoing manual effortNo – works on raw footageRelationship mappingFlat, keyword-basedKnowledge graph connects related contentIndustry-specific accuracyGeneric modelsDomain-trained for your vertical

Who This Is Built For:

News broadcasters with decade-long archives that are technically searchable but practically useless.

Post-production editors who waste billable hours hunting for clips they’ve seen before.

Sports networks managing thousands of match hours that need frame-level retrieval.

Streaming platforms trying to surface and reuse catalogue content efficiently.

MAM platform vendors who want to layer AI intelligence onto existing infrastructure via API.

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Why Media Asset Management Systems Still Struggle with Search

Strong Media Asset Management doesn’t guarantee strong search. Discover how MAM-agnostic semantic video search uses contextual indexing and

What holds media companies back now isn’t lack of content. It’s a lack of clarity. When videos pile up across scattered folders, locating one specific clip takes time – no matter how advanced the Media Asset Management system seems. Right where you’d expect efficiency, things slow down.

Storage, organization, and permissions – that’s what most Media Asset Management platforms handle smoothly. Yet their video search tools lag behind. Finding files often means relying on tags, titles and manually entered metadata. If details are skipped or messy, good luck spotting the file later.

Here’s the thing about Semantic Video Search – it has to connect across every MAM, not live trapped in a single system.

Why Semantic Video Search Should Be MAM-Agnostic:

Picture this – most organizations aren’t using one single, clean MAM environment. Over time, they accumulate:

Multiple archives.

Different storage systems.

Legacy and modern MAMs.

Cloud and on-premise setups.

Fresh starts aren’t practical when they want’s to improve search quality.

A MAM-agnostic Semantic Video Search API works across this complexity. It does not demand a new Media Asset Management system or a complete migration. By linking into current tools, it brings smarter search. Smarts get layered over old frameworks instead of tossing them out.

Here’s when getting systems to work together really matters.

One Semantic Layer Across Multiple Media Archives: 

Most folks skip this detail entirely. It slips under the radar without much thought at all.

Storage location of the file.

Who takes care of running it.

What labels were attached back then.

Searching happens based on what people actually want.

For big groups, it matters a lot when editors, reporters, promoters, or analysts handle shared material differently.

Keywords to Video Search with Meaning (Contextual Video Search)

Keywords are fragile. Context is durable. Contextual Video Search understands:

What appears in the video

Who is speaking, and what is being said

What is happening in that specific moment

When indexing is kept separate, videos can be indexed once and used across any MAM or media platform. The indexed data works independently, no matter where the video is stored or accessed.

This makes video search flexible, easy to integrate, and free from platform dependency.

Where Gyrus Semantic Video Search Fits In?

Gyrus Semantic Video Search is built as an independent semantic layer that works alongside existing Media Asset Management systems.

What happens inside Gyrus system stays flexible. It connects through APIs, grasps what content means, then delivers useful answers. Old setups keep running as they are, untouched.

How storage works? Not its concern. Because it works alongside existing systems, companies can upgrade search capabilities without a full overhaul.

Why This Affects Teams Beyond Technology?

Finding things faster doesn’t only upgrade tools – work habits shift because of it.

When semantic search works regardless of MAM:

Finding content takes less time when you’re an editor.

Finding old stories again? Reporters make better use of stored material these days.

Content teams avoid duplicate work.

Decision-makers gain visibility into hidden assets.

Semantic Media Search becomes the connective tissue that brings meaning across the entire media landscape.

Final Thought:

Loose boundaries let semantic video search perform at its peak. Without tying itself to one Media Asset Management system, flexibility grows – so does room to expand, adapt, stay relevant.

Finding hidden meaning in old files becomes possible when one Semantic Media Search API taps into every storage spot. Because semantic search is API-driven, it can plug into any MAM platform – without changing existing ingest, storage, or workflows. Even in organizations using multiple MAM systems, the same search and indexing layer works seamlessly across all of them.

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How Semantic Media Search Helped a Retail Company Create Marketing Assets Faster.

Gyrus Semantic Media Search Improved Retail Content Production

Learn how Gyrus AI semantic media search helped a retail content team find assets faster, reduce rework, and accelerate marketing production

Today’s modern retail and e-commerce companies produce huge amounts of visual content – product photos, promotional videos, user-generated clips, audio voiceovers, influencer reels, etc. 

When teams look for files using visual similarity, spoken content, or contextual semantics, old-style search tools fall short because they rely on manual tags or simple keyword indexing, which fail to understand the meaning of this content. Instead of just scanning filenames or descriptions, semantic and multimodal search systems turn text, images, video, and audio into a shared semantic space that enables retrieval based on meaning rather than exact metadata matches.

The Wish List:

So the company set clear goals meant to make a real difference both technically and commercially.

Contextual search without manual tagging.

Ability to search media using text, image, or audio inputs.

Faster indexing of large volumes of video and image data.

A cost-efficient alternative to metadata-heavy or LLM-centric solutions.

Seamless integration with the existing MAM/DAM platform.

Measurable ROI, driving faster discovery, lower content creation costs.

The Solution:

One step ahead, the team brought Gyrus AI Semantic Media Search and integrated it into their media/digital asset management setup. Mostly behind the scenes, it works by understanding content deeply before delivering results.

Contextual search, no tagging needed – Editors could now just type simple queries like “product unboxing close-up” or “model wearing blue jacket” and instantly find the scene they were looking for.

80% faster processing speed – An hour of video gets indexed in ~ 5 minutes by an RTX 3090/4060.

Up to 10× more cost-effective – Our solution was able to deliver the most cost savings when compared to metadata-heavy or LLM-based solutions.

Compact multimodal model – It is optimized to process video, audio, and images while staying lightweight and efficient.

Flexible deployment – Able to run on-prem aligning with enterprise requirements.

The Results:

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Virtual Product Placement: The New Standard for In-Content Advertising.

Learn how virtual product placement turns every video frame into scalable, non-intrusive ad inventory using AI.

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How Gyrus AI Search made a regular MAM smart and won over broadcaster?

Gyrus AI Semantic Media Search made a Media Asset Management (MAM) platform smarter, helping a broadcaster boost speed and cut costs.

Media Asset Management (MAM) and Digital Asset Management (DAM) platforms are considered to be the backbone for broadcasters doing numerous operations like storing and organizing massive libraries of video contents – news, shows, sports, archives, etc and making them accessible for reuse.

But broadcasters these days are not satisfied with just storage anymore. They are demanding speed, intelligence, and cost efficiency. They have to find events of interest in video files based on context and not just titles or manual tags. This is the point where traditional metadata search falls short and contextual AI search proves its value.

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10 Must-Know Deployment Tips for Media Search Solutions.

Learn 10 essential deployment tips for Intelligent media search covering models, ingestion, indexing, security & scalability for media organ

An Intelligent Media Search solution can actually change the way how your team interacts with video, audio, and image content. However, deployment planning is where the real success happens – from choosing the appropriate infrastructure model to compliance and operational aspects on a performance and integration level.

Given these factors, you are more confident of rolling out very fast while insulating the search against the ever-expanding amount of media data.

Still have questions or just want to see how Intelligent Media Search works for your media library?

We can walk you through everything – from uploading your content to finding the exact scene you need in seconds. Book your free demo today at www.gyrus.ai

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RAG Worked. But for Search, GraphRAG Works Better. - Gyrus AI | Blog | Insights on AI & Intelligent Media Search, In-scene Ad Placement, Aut

Discover how GraphRAG transforms AI media search by enabling intelligent, context-aware retrieval across timelines, speakers, and scenes. Ex

Imagine RAG like searching a library by keywords, generating keyword hits that are then passed to a language model for some dot-connecting. Works well when answers to simple queries are needed, but what happens when linked facts from different places are needed? 

GraphRAG structures knowledge into entities and relations, allowing answers to be formed in a more considered and connected fashion. It is like moving away from disorganized index cards to a smart map of relations. This is an excellent option for media search, for whom “who said what when, in what context” matters enormously.

How RAG Works (Briefly):

In RAG, chunks of documents are converted into vectors (numerical form). These vectors are then searched against your query by matching the best correspondences. The retrieved chunks are passed into the LLM, together with the user’s question, thus giving an answer based on the given content. 

It is excellent for Q&A, but it loses the context when the relationship extends across chunks or when reasoning must follow a chain.

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How Gyrus Cut Media Processing Costs 10x for News Broadcaster

Gyrus AI cuts 90% of media processing costs with on-premise AI video search, automated MAM, metadata-free indexing, fast broadcast workflows

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Video Processing Made Smart and Easy with Intelligent Media Search

Watch how Gyrus AI’s video search engine identifies faces with stunning accuracy - even across age differences using nothing more than a photo. It understands specific persons, actors, or even objects in visual content and deliver precise video results. 📷 In this demo: We searched using a photo of David Schwimmer (Ross Geller, Friends) → Instantly returned clips where he appears in the show. Then used a photo of Jennifer Aniston (Rachel Green, Friends) → Accurate retrieval of every matching scene. No tags. No metadata. Just pure visual intelligence that understands face features and scene context. 🔍 Perfect for broadcasters, streamers, and content curators who manage large video libraries. Book a custom demo or connect with us at https://gyrus.ai/Solutions/media-asset-management-search.html

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Streamline Semantic AI Intelligent media search and Discovery with Gyrus AI in Media Asset Management and Digital. Easily find,tag,and organ

Video Processing Made Smart and Easy with Intelligent Media Search

Discover Moments that Matter with Ease.

Search Videos by Context and ContentSeamlessly Integrates With Your MAM/DAM or Cloud Platform

Request a Demo

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Why Embeddings Matter in AI Media Discovery | Gyrus AI Blog

Embeddings in AI media discovery transform digital asset management by understanding semantics video search, enhancing video content indexin

The need for efficient search and retrieval of relevant video content has become increasingly important in the fast-paced digital media landscape. In the older scenario, manual tagging and generating metadata were considered the hallmark of any retrieval method. However, this fails to capture the nuanced semantics of a video and its meaning. Embeddings have made a revolutionary technology that allows machines to understand and index video content indexing based on its intrinsic meaning. 

Understanding Embeddings in the Context of Video.

Embeddings are continuous vector representations that encapsulate the semantic concept of data, be it text, images, audio, or video. In the video context, embeddings are created by feeding visual frames, audio signals, and textual elements (such as subtitles) to deep learning models in some fashion. Such a process changes complex, high-dimensional data into an ordered format that can be readily analyzed and compared by machines.

Conclusion:

In the scope of applying data science techniques to video content, Embeddings offer a series of solutions ranging from simple keyword search to powerful semantically oriented retrieval systems. By embedding advanced concepts, multimedia videos can be indexed and queried semantically for far more meaningful and efficient access.

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Gyrus AI Solutions- Intelligent Media Search

Find the Right Moment in Seconds

Gyrus AI is an advanced AI video search engine designed for next-generation Media Asset Management (MAM). Powered by cutting-edge machine learning and semantic video search capabilities, it transforms the way you discover, organize, and retrieve content.

From video, audio, to images, Gyrus enables contextual media search that goes far beyond traditional metadata—so you spend less time searching and more time creating, analyzing, or delivering results.

Why Gyrus?

🔍 Intelligent Media Search Search by scenes, speakers, objects, emotions, or themes—not just keywords. 🧠 AI-Driven Tagging & Video Content Indexing Automatically tag, categorize, and enrich your media with deep context. ⚡ Lightning-Fast Retrieval Instant access to large video archives and datasets. 🔗 Seamless Integration Works with your current MAM, DAM, or cloud platform. 🔒 Scalable & Secure Enterprise-grade solution built to scale with your needs.

Use Cases

🎬 Broadcast & Media Companies An AI tool for media companies to locate clips for editing, archiving, or reuse. 📈 Marketing & Creative Teams Quick access to brand-compliant visuals via AI media discovery. 🎓 Education & Research Surface key segments from lengthy lectures or interviews using semantic search. ✅ Corporate Training & Compliance Easily audit, review, and manage recorded content.

Boost Your Media Discovery Strategy

With Gyrus, you’re not just managing media—you’re unlocking it.

Contextual video search

Knowledge graph media search

Content discovery AI tools

Built for rich video content indexing

See Gyrus in Action

Discover how our AI-powered media search platform can transform your workflow.

👉 Book a Demo

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Streamline AI media search with Gyrus AI in Media Asset Management(MAM). Easily find,tag,and organize semantic AI Discovery Digital Asset, m

Gyrus AI Solutions – Intelligent Media Search Find the right moment in seconds. Gyrus uses AI to scan, tag, and retrieve media with precision—video, audio, or images—so you never waste time searching again.

Discover Moments that Matter with Ease.

Search Videos by Context and Content Seamlessly Integrates With Your MAM/DAM or Cloud Platform

Want to see how Gyrus Intelligent Media Search can save you time? Let us show you

Book a Demo

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Why On-Premise Media Search Is Making a Comeback? - Gyrus AI | Blog | Insights on AI & Intelligent Media Search, In-scene Ad Placement, Auto

Discover why media houses choose on-premise AI Media Search and Asset Management for secure, cost effective semantic video search indexing.

Why Media Houses Prefer On-Premise Solutions?

Intelligent Media Search organizations deal with a large amount of highly sensitive content, including unreleased footage, undisclosed interviews, and proprietary research materials. Keeping such data within the organization and processing it on-premises reduces the risk of exposure to breaches or unauthorized access outside the organization. Moreover, these very well comply with applicable regulations and put all those who worry about data sovereignty at ease.

Media houses are also cautious about using prompts or APIs connected to public large language models (LLMs), as these could potentially expose confidential data. While cloud solutions are evolving, getting media houses to fully embrace public cloud networks will take time due to their strong comfort with existing on-premise systems.

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NAB Show 2025 | Las Vegas

Discover Intelligent Media Search & seamless in-scene ad placement.

Intelligent Media Search

AI-generated descriptions for video and audio.

Automated scene and dialogue tagging with timestamps.

Fast and precise search across large video libraries.

Integration with knowledge graphs for smarter searches

Meeting at NAB 2025

30 min

W4143AE, West Hall, PropelME, NAB Show, Las Vegas Convention Center

Check out how we simplify video content Search with our Intelligent Media Search solution and In-scene Ad Placement solution to seamlessly blend the ads into the scene - automatically placed at the right spot, at the right time, for maximum engagement. Experience innovative ML/AI solutions for Video Processing, Media Management and Advertising.