The companies that’ll stand atop their industries in the future will be the ones that rapidly extract value from AI. But the question becomes how? The future of work belongs to organizations that can harness the power of AI to make data more accessible, actionable, and connected. And that transformation is already underway.
For example, Veritone recently announced new innovations designed for advertisers, agencies and media professionals. These types of organizations struggle with the technical aspects of setting up campaign tracking and the time-consuming task of understanding and analyzing large amounts of performance data into clear, actionable insights. With two new AI agents, Connection for Veritone Attribute and Data Summary for Discovery, users can simplify workflows and extract insights quickly from their campaigns.
This is just one example of agentic AI in action. But why haven’t more organizations adopted and implemented such capabilities?
The future of AI belongs to those who tame the chaos of unstructured data
Unstructured data in video, audio, PDFs, emails, and other digital media makes up over 80-90% of the world’s data. Unfortunately, most organizations are unable to access this data which makes the adoption of AI possible. They are, in fact, data-rich but insight-poor.
Most legacy data management systems were built with structured formats like tables and spreadsheets in mind. But today’s organizations face a deluge of unstructured information. These tools simply weren’t designed to manage the scale, diversity, and speed at which this kind of data is generated.
The most important question you can ask yourself is how you and your organization are managing your structured and unstructured data. This is the starting point, for it’s the foundation on which AI can be fully adopted. But how does one make their data usable for AI?
Bridging the gap to AI adoption
Unlocking the potential of unstructured data requires a shift in mindset: every piece of content is data. Modern AI systems break down that data into tokens, the smallest units of meaning, whether a full word, part of a word, punctuation mark, or even a space. By analyzing the relationships between these tokens, AI can interpret context, derive meaning, and generate intelligent responses.
But this isn’t just about smarter tagging or classification. It represents a new way of thinking about the lifecycle of enterprise data, from its raw, unstructured state to a form that can be enriched, summarized, and connected by AI agents. Preparing data in this way is only the foundation. To make it actionable across industries and workflows, enterprises must enable their AI to extend beyond training limitations, connecting insights across systems, silos, and applications.
Veritone Data Refinery (VDR) delivers the data preparation required by AI to transform Enterprise workflows
Recognizing the crippling gap across industries in data preparation so that an organization can adopt AI, Veritone created Veritone Data Refinery (VDR). It provides a powerful way to transform messy, unstructured data into organized, structured formats, ready to power advanced AI systems — from large language models (LLMs) to complex multimodal models (MMLs).
Earlier this year, VDR, powered by aiWARE™, surpassed a remarkable milestone, processing more than five trillion tokens across millions of hours of video and audio. This achievement underscores what’s possible when enterprise AI is engineered for performance, extensibility, and trust.
Most enterprise content still sits untapped in formats like broadcast archives, sports footage, marketing assets, and security recordings. VDR changes that by converting raw, unstructured data into AI-ready assets. Once refined, this data becomes discoverable, monetizable, and even fuel for secure, proprietary AI models, all without the need for retraining entire systems.
Veritone AI Agent Connection for Attribute delivers automated site setup and validation to accelerate attribution workflows
The Connection agent within Veritone Attribute takes the friction out of onboarding and ensures advertisers can move quickly from setup to signal. Instead of requiring long, manual audits or technical back-and-forth, the agent automatically scans a site to understand its current environment.
Connection can detect whether Google Tag Manager or analytics pixels are already in place, highlight conflicts or redundancies, and then recommends the best course of action. What makes this especially powerful is its ability to adapt the onboarding workflow to the advertiser’s actual platform, whether they’re running WordPress, Shopify, or a custom CMS, so the instructions feel tailored, not generic.
For teams that need to loop in developers, Connection generates clean, developer-friendly documentation alongside marketer-level guidance, ensuring alignment across technical and non-technical roles. And the value doesn’t stop after launch.
By running periodic health checks, Connection flags missing or broken tags and alerts teams to drift in data quality before it undermines campaign performance. The result is faster time to signal, earlier optimization opportunities, and consistent, high-integrity data across all accounts. In short, Connection helps advertisers spend less time wrestling with setup and more time benefiting from actionable attribution.
Veritone AI Agent Data Summary for Discovery delivers unified reporting and actionable insights to transform decision-making
On the Discovery side, the Data Summary agent turns raw, often fragmented information into cohesive, digestible narratives. Instead of spending hours stitching together campaign metrics, audience insights, and creative performance data across multiple sources, users can rely on the agent to blend everything into one clear, unified report.
These summaries aren’t just data dumps—they’re layered to meet the needs of different stakeholders. Executives might see a top-line view of performance trends, while campaign managers get more granular breakdowns by channel, audience, or even time of day.
What makes the summaries even more valuable is their ability to go beyond describing what happened to offering hypotheses about why results occurred and suggesting possible next steps. If a shift in budget allocation improves conversions among younger demographics, for example, the agent highlights that trend and frames it as a testable insight. Because the output is editable and customizable, teams can easily adapt reports to match client branding or internal templates, and they always retain the option to refine AI-generated insights with their own context.
For marketers and analysts alike, the biggest advantage is speed and scalability. What once required hours of manual reporting is now available almost instantly, freeing up time to focus on strategy rather than formatting. And because the summaries are consistent, clear, and actionable, they help build trust with clients and executives who need confident, comprehensible reporting to make informed decisions. In essence, Data Summary transforms raw discovery into insight that drives action.
Veritone aiWARE™ acts as the foundation to flexible, model agnostic AI capabilities
At the core of our products, from Veritone Data Refinery to our AI Agent offerings, is aiWARE™. The platform is an orchestration layer over 850 specialized AI models, spanning domains from vision and speech to data, biometrics, text, and generative capabilities. These models ingest, analyze, enrich, and correlate multimodal content in concert, enabling enterprises to treat once-static or siloed data as living, queryable intelligence.
With aiWARE™ underpinning VDR, every transformation or insight is driven by a scalable, flexible, and model-agnostic infrastructure. You’re not tied to a single algorithm or vendor; instead, aiWARE allows you to swap, parallelize, or ensemble models to meet evolving requirements or to test new approaches.
aiWARE enables embedding natural language understanding, entity extraction, and contextual linking across content types; it can turn a passive video or audio archive into a semantically indexed, richly tagged repository. That means search is no longer keyword-bound. You can probe by concept, theme, sentiment, related entities, or cross-media context, and discover assets you never knew existed.
With aiWARE’s object detection, face recognition, speaker diarization, and sensitive content identification engines, the system can autonomously flag or redact PII, route files for legal review, or enforce compliance policies. This frees up legal, content, and operations teams from tedious manual review and reduces human error in high-stakes domains.
Archives of audio, video, transcripts, images, or documents often lie fallow because they lack structure or discoverability. By applying aiWARE’s models to enrich, index, and relate those assets, organizations can repurpose them as licensed content, searchable research datasets, or intelligence products. What was once a liability becomes a monetizable resource.
Beyond pure model performance, aiWARE embeds controls around access, auditing, model versioning, and drift management. This ensures that as usage expands across departments, geographies, or regulatory environments, governance mechanisms keep data access, lineage, and AI decisions auditable and secure.
In short, with aiWARE as VDR’s engine, your data becomes a living, queryable, and governed foundation for AI-powered workflows and insights.
What was once an edge is now table stakes. The leaders of tomorrow will be the enterprises that embed AI-powered data asset management into the heart of their operations, creating intelligent systems that continuously generate insights, automate decisions, and drive value without interruption.
Learn More About Veritone Data Refinery
Sources:
https://researchworld.com/articles/possibilities-and-limitations-of-unstructured-data
https://www.forbes.com/sites/craigsmith/2024/11/20/veritone-introduces-data-refinery-tackling-ais-data-drought/
