Enterprise multimodal AI platform for processing unstructured visual content at scale.
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<h3>Product Overview</h3><p>Coactive AI operates a premium enterprise Multimodal AI Platform (MAP) that processes unstructured visual content across images, videos, and audio at scale. The company serves Fortune 500 retailers, media and entertainment companies, and community platforms managing large-scale visual content libraries. Their platform automates content tagging, enables semantic search across visual assets, and provides content moderation capabilities with quantified ROI: Fandom automated 88% of manual labeling in four weeks, achieving 50% cost savings and 74% reduction in manual review hours.<br />
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The company does not maintain a public pricing page and operates exclusively through high-touch enterprise sales with custom contracts starting at $75,000 annually.</p>
<h3>Key Features & Capabilities</h3><p>Coactive's MAP combines multimodal AI processing, discovery and search, and workflow automation with enterprise-grade integration and governance controls designed for high-volume media libraries.</p><ul><li>Multimodal processing: Unified image, video, and audio analysis in a single platform, including intelligent video segmentation that auto-segments video into shots and audio intervals.</li><li>Semantic search & discovery: Natural language search across visual modalities without requiring pre-existing metadata.</li><li>Metadata tagging & fine-tuning: AI-powered automated tagging for personalization and ad targeting, including zero-shot tagging (reported at 81% accuracy post-Autumn '25 release) and included fine-tuning at no extra cost.</li><li>Enterprise integration & access control: BYOM architecture via AWS Bedrock, Azure AI, and Databricks, plus role-based access control with a 5-tier RBAC model (System Admin, Member, Dataset Admin, Dataset Editor, Dataset Viewer).</li><li>API and throughput limits: API-based workflows (documented as 6 REST endpoints) and performance capabilities up to 2,000 video hours/hour, with support for 13 image formats and 7 video formats (max 5-hour video duration).</li></ul>
<h3>Pricing Model Analysis</h3><p>Coactive AI uses a subscription-with-overage enterprise model: a fixed annual subscription (anchored by a $75,000/year entry point) paired with usage-based overages billed at $1.00 per unit above the base allocation. Public sources confirm the overage rate but do not disclose what constitutes a billable "unit," which is the key constraint on accurate total cost modeling.</p><div class="tableResponsive"><table cellpadding="6" cellspacing="0"><tr><th>Metric Type</th><th>What Measured</th><th>Why It Matters</th></tr><tr><td>Value Metric</td><td>Enterprise contract value tied to operational efficiency gains</td><td>Enables value-based pricing; Fandom achieved 88% automation of manual labeling</td></tr><tr><td>Usage Metric</td><td>Per-unit consumption above base allocation</td><td>Scales with customer growth and platform usage intensity</td></tr><tr><td>Billable Metric</td><td>Undefined "units" at $1.00 each</td><td>Unit definition affects total cost modeling and forecasting</td></tr></table></div>
<h3>Customer Sentiment Highlights</h3><ul><li>“Coactive's platform allowed full customization to match our unique guidelines. And, in just four weeks, 88% of our manual labeling was automated. Coactive allows Fandom to improve the user safety of our wiki communities while reducing cost. - Florent Blachot, VP of Data Science & Engineering, Fandom”<b> <span class="pricingHiphenSymb"> - </span>Case Study</b></li><li>“Partnering with Coactive has transformed moderation from a bottleneck into a competitive advantage. We can now manage millions of uploads with confidence, protect our fans, and deliver the brand safety advertisers expect. - Florent Blachot, VP of Data Science & Engineering, Fandom”<b> <span class="pricingHiphenSymb"> - </span>Fandom Case Study</b></li><li>“Our brands have been able to clear their content backlogs, making their workflows much smoother. We aim to make sure they are spending time in our platform efficiently, and these results show we're achieving that. It's like night and day. - Heidi Eggert, Senior Product Manager, Emplifi”<b> <span class="pricingHiphenSymb"> - </span>Emplifi Case Study</b></li><li>“It was important that our visual search-powered product discovery solution provided two key benefits: accuracy and speed. For customers with large product catalogs, efficiency while product tagging is crucial. - Heidi Eggert, Senior Product Manager, Emplifi”<b> <span class="pricingHiphenSymb"> - </span>Emplifi Case Study</b></li></ul>
Metronome’s Take
<p>Coactive is priced as a dedicated enterprise platform rather than a self-serve tool, meaning you engage their team directly to build a contract sized to your content library and processing needs. Rather than paying per image or per query, your organization commits to a contract that covers a defined volume of ingestion and analysis, with additional usage billed on top if you exceed it. One structural advantage built into the platform is that once your content is processed, the underlying embeddings are reused across multiple downstream use cases, meaning you are not charged to reprocess the same content when you build a new application or analysis on top of it.</p>
<p><strong>Recommendation:</strong> Coactive's contract-based model is well suited for organizations where the cost of managing and monetizing large visual content libraries is a strategic priority rather than a tooling line item. The reusable embedding architecture means the platform becomes more cost-efficient over time as more applications are layered on top of a single ingestion investment. Companies best positioned for this model are mid-to-large enterprises in media, entertainment, e-commerce, and advertising that operate substantial digital asset libraries and need to unlock actionable intelligence from visual content at scale, particularly those already embedded in the AWS ecosystem where cloud procurement paths simplify the purchasing process.</p>
<h4>Key Insights</h4><ul><li>
<strong>Reusable embeddings eliminate reprocessing costs.:</strong> Unlike other platforms and cloud providers, Coactive allows fine-tuning repeatedly using stored embeddings with no per-run pricing or forced reprocessing. Once content is ingested and embedded, that investment persists across all downstream applications built on it. <p><strong>Benefit:</strong> Enterprises with large visual content libraries can build multiple use cases, such as content recommendations, brand safety monitoring, and ad targeting, on a single layer of processed content without incurring duplicate ingestion or compute costs each time.</p></li><li>
<strong>Model-agnostic architecture with no foundation model lock-in.:</strong> Coactive's architecture integrates preferred closed or fine-tuned models through frameworks like AWS Bedrock, Azure AI, and Databricks, giving organizations full control over what runs where. This means the platform contract is not tied to a single underlying model provider. <p><strong>Benefit:</strong> As better or more cost-effective models become available, organizations can upgrade or swap components without renegotiating their platform relationship or rebuilding their ingestion pipelines, protecting the long-term value of their infrastructure investment.</p></li><li>
<strong>Contracted volume with AWS Marketplace availability.:</strong> Pricing is based on contract duration and terms, with overages applied on top, and the platform is available through AWS Marketplace where cloud credits and existing procurement relationships can apply. <p><strong>Benefit:</strong> Enterprise buyers with existing AWS committed spend can apply pre-committed cloud budgets toward Coactive, consolidating vendor management and potentially reducing net cost through existing cloud agreements rather than opening a new budget line.</p></li></ul>
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