DNAfabric
The AI + Metadata + Data Unification Platform
In an era of fast moving and multi-choice AI, we help you maximize your audio, visual assets (legacy and future) with an open and customizable data management and AI enablement platform.
What is DNAfabric AI
DNAfabric AI is a unique approach to AI pipelines. Think of it as a set of building blocks, designed to help any organization create multiple AI workflows in the audio, visual space.
(01) Ready-to-Use AI Building Blocks
From transcoders to databases, every component is included and tuned specifically for audio and video AI workflows.
(02) Reduce Costs, Max Efficiency
Combine multiple AI models and LLMs to maximize efficiency, accuracy, and cost control—without lock-in.
(03) Exascale-Ready AI Metadata Storage
AI metadata grows fast. Built to store, index, and manage it at massive scale without overwhelming infrastructure.
(04) Hundreds of AI Use Cases Across the Organization
Deploy AI across departments, roles, and teams—from editorial and QC to marketing and archives.
AI Pipelines The fully composable and customizable AI pipeline for audio visual organizations.
Mix n Match • Compose • Save costs • Drive efficiency • Increase revenues
Get More Than
30+ integrations with
popular tools
4.8 (Rating)
Combined multiple on-prem and
cloud AI end points and LLMs
Enabled parallel submission to multiple AI vendors – resulting in maximum efficiency for content enrichment
Minimize your cost – by creating intelligent proxies and combining the most cost effective models across providers
Maximize your AI enrichment investments and workflows by integrating multiple LLMs to further tune and enhance your AI results.
AI Pipeline Highlights The proven way to get audio, visual AI pipelines working for your business.
Do not limit your data to one AI provider
- Mix and match AI vendors and modalities—including AWS, Azure, Google Cloud, and Twelve Labs—to build pipelines that fit your content, workflows, and budget.
- Choose a single provider or combine many to maximize accuracy while controlling costs.
Be smart, manage AI costs up font
- With the ability to select from multiple vendors – you are in charge
- Switch, mix, match as needed
Own and control your AI metadata (and legacy metadata)
- Extract, store, and manage all AI-generated metadata in an open, vendor-neutral format.
- Eliminate lock-in while building a scalable foundation that grows with your AI strategy.
- Add legacy metadata to the same architecture.
Use LLMs to drive intelligence decisions and do more
- Leverage human-guided LLM enrichment to extract deeper meaning from audio and video timelines.
- Apply reasoning, summarization, and interpretation on top of existing AI metadata—powering multiple downstream pipelines and enabling smarter workflows across every department.
We can help you create the lowest cost audio visual AI pipelines!
As media libraries grow, full-video AI analysis quickly becomes financially unsustainable. This paper introduces a cost-optimized enrichment model that leverages scene detection, sub-scene classification, and selective frame extraction to maintain insight quality while sharply reducing AI processing costs.
AI Use Cases Empower every user, Across every department
From ingest to archive, utilize AI enrichment and LLMs to accelerate and drive value into every pipeline.
Validate AI before you commit
- Compare AI vendors and modalities on real audio-visual content with normalized results.
- Make informed, evidence-based decisions without vendor lock-in or blind experimentation.
Start editing with intent, not raw footage
- Automatically surface scenes, highlights, dialogue, and editorial selects.
- Reduce prep time so editors focus on storytelling, not scrubbing timelines.
Catch risk before it reaches air
- Detect policy violations with frame-accurate, auditable metadata.
- Ensure consistent enforcement across platforms while reducing legal exposure.
Find the moments that move audiences
- Identify emotional peaks and promo-ready clips across your library.
- Launch campaigns faster with smarter reuse of existing content.
Turn archives into active assets
- Enrich and unlock decades of content with intelligent metadata.
- Transform long-term storage into a searchable, monetizable content resource.
See the story beyond the cut
- Gain episode- and season-level insight into tone, characters, and themes.
- Make faster creative decisions with data-backed visibility across content.
Find the right footage in seconds
- Search across video, audio, and transcripts with time-accurate precision.
- Strengthen reporting with instant access to historical context and related stories.
Know where rights risk lives
- Track faces, brands, and usage across libraries with clear audit trails.
- Support faster approvals and safer distribution with defensible metadata.
Localize with context, not guesswork
- Deliver scene-aware transcripts, speakers, and priorities for global teams.
- Reduce errors and costs while preserving cultural and narrative intent.
Data Pipelines Beyond AI: Comprehensive Data Management
Search, Analytics, Backup, Archive, Migration and Sync
Ready-to-Use AI Building Blocks
From transcoders to databases, every component is included and tuned specifically for audio and video AI workflows.
(02) Reduce Costs, Max Efficiency
Combine multiple AI models and LLMs to maximize efficiency, accuracy, and cost control—without lock-in.
(03) Exascale-Ready AI Metadata Storage
AI metadata grows fast. Built to store, index, and manage it at massive scale without overwhelming infrastructure.
(04) Hundreds of AI Use Cases Across the Organization
Deploy AI across departments, roles, and teams—from editorial and QC to marketing and archives.
Reduce Costs, Max Efficiency
Combine multiple AI models and LLMs to maximize efficiency, accuracy, and cost control—without lock-in.
(03) Exascale-Ready AI Metadata Storage
AI metadata grows fast. Built to store, index, and manage it at massive scale without overwhelming infrastructure.
(04) Hundreds of AI Use Cases Across the Organization
Deploy AI across departments, roles, and teams—from editorial and QC to marketing and archives.
Exascale-Ready AI Metadata Storage
AI metadata grows fast. Built to store, index, and manage it at massive scale without overwhelming infrastructure.
(04) Hundreds of AI Use Cases Across the Organization
Deploy AI across departments, roles, and teams—from editorial and QC to marketing and archives.
Hundreds of AI Use Cases Across the Organization
Deploy AI across departments, roles, and teams—from editorial and QC to marketing and archives.
The fully composable and customizable AI pipeline for audio visual organizations.
Get More Than 30+ integrations with popular tools
4.8 (Rating)
Combined multiple on-prem and
cloud AI end points and LLMs
Enabled parallel submission to multiple AI vendors – resulting in maximum efficiency for content enrichment
Minimize your cost – by creating intelligent proxies and combining the most cost effective models across providers
Maximize your AI enrichment investments and workflows by integrating multiple LLMs to further tune and enhance your AI results.
The proven way to get audio, visual AI pipelines working for your business.
Do not limit your data to one AI provider
- Mix and match AI vendors and modalities—including AWS, Azure, Google Cloud, and Twelve Labs—to build pipelines that fit your content, workflows, and budget.
- Choose a single provider or combine many to maximize accuracy while controlling costs.
Be smart, manage AI costs up font
- With the ability to select from multiple vendors – you are in charge
- Switch, mix, match as needed
Own and control your AI metadata (and legacy metadata)
- Extract, store, and manage all AI-generated metadata in an open, vendor-neutral format.
- Eliminate lock-in while building a scalable foundation that grows with your AI strategy.
- Add legacy metadata to the same architecture.
Use LLMs to drive intelligence decisions and do more
- Leverage human-guided LLM enrichment to extract deeper meaning from audio and video timelines.
- Apply reasoning, summarization, and interpretation on top of existing AI metadata—powering multiple downstream pipelines and enabling smarter workflows across every department.
We can help you create the lowest cost audio visual AI pipelines!
As media libraries grow, full-video AI analysis quickly becomes financially unsustainable. This paper introduces a cost-optimized enrichment model that leverages scene detection, sub-scene classification, and selective frame extraction to maintain insight quality while sharply reducing AI processing costs.
Empower every user, Across every department
From ingest to archive, utilize AI enrichment and LLMs to accelerate and drive value into every pipeline.
Validate AI before you commit
- Compare AI vendors and modalities on real audio-visual content with normalized results.
- Make informed, evidence-based decisions without vendor lock-in or blind experimentation.
Start editing with intent, not raw footage
- Automatically surface scenes, highlights, dialogue, and editorial selects.
- Reduce prep time so editors focus on storytelling, not scrubbing timelines.
Catch risk before it reaches air
- Detect policy violations with frame-accurate, auditable metadata.
- Ensure consistent enforcement across platforms while reducing legal exposure.
Find the moments that move audiences
- Identify emotional peaks and promo-ready clips across your library.
- Launch campaigns faster with smarter reuse of existing content.
Turn archives into active assets
- Enrich and unlock decades of content with intelligent metadata.
- Transform long-term storage into a searchable, monetizable content resource.
See the story beyond the cut
- Gain episode- and season-level insight into tone, characters, and themes.
- Make faster creative decisions with data-backed visibility across content.
Find the right footage in seconds
- Search across video, audio, and transcripts with time-accurate precision.
- Strengthen reporting with instant access to historical context and related stories.
Know where rights risk lives
- Track faces, brands, and usage across libraries with clear audit trails.
- Support faster approvals and safer distribution with defensible metadata.
Localize with context, not guesswork
- Deliver scene-aware transcripts, speakers, and priorities for global teams.
- Reduce errors and costs while preserving cultural and narrative intent.