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Coactive AI

  • What it is:Coactive AI is a multimodal AI platform that automatically searches, organizes, and analyzes images and videos to help businesses extract insights and moderate content at scale.
  • Best for:Large enterprises with visual content libraries, Media & entertainment companies, Retail/e-commerce with product imagery
  • Pricing:Starting from $75,000/year
  • Rating:78/100Good
  • Expert's conclusion:Coactive is the best option for scalable media organizations which require accurate multimodal understanding, economic cost reduction, and control of their AI models.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Coactive AI and What Does It Do?

Coactive AI is a well-established organization within the Business/Productivity Software segment that produces an advanced AI-based platform for enabling data teams to extract insight from unstructured image and video data through data-centric AI techniques. The platform includes visual data integration into SQL environments along with robust deep learning functionalities allowing for the accessibility and actionability of visual data by organizations. Coactive was founded in 2021 by co-founders Cody Coleman and Will Gaviria Rojas. They are focused on creating structured images and videos from unstructured images and videos across numerous industries.

Active
📍San Jose, CA
📅Founded 2021
🏢Private
TARGET SEGMENTS
EnterprisesData TeamsData Scientists

What Are Coactive AI's Key Business Metrics?

🏢
47
Employees
📊
$30M Series B
Funding Raised
📊
$200M
Valuation
📊
3 (San Jose, San Francisco, Montreal)
Offices

How Credible and Trustworthy Is Coactive AI?

78/100
Good

A private company that is well funded, with a very experienced technical team consisting of MIT alumni, and also has extensive experience at major technology companies. Operating in a highly demanding area of AI for visual data, there is limited publicly reviewed data about this firm.

BREAKDOWN
Product Maturity75/100
Company Stability85/100
Security & Compliance70/100
User Reviews60/100
Transparency75/100
Support Quality70/100
TRUST SIGNALS
Founded by MIT alumniBacked by Andreessen Horowitz, BessemerSeries B funded at $200M valuationTeam from Google, eBay, Tesla, Meta

What is the history of Coactive AI and its key milestones?

2021

Company Founded

Co-founded in San Jose, California by Cody Coleman and Will Gaviria Rojas, MIT Alumni, Coactive developed an AI-based platform to make use of image and video data with AI.

2024

Series B Funding

Coactive received a $30 Million dollar Series B round of funding at a $200 Million dollar valuation led by Emerson Collective and Cherryrock, with Bessemer Venture Partners, Greycroft Partners and Andreessen Horowitz participating in the round.

2025

MIT Recognition

Featured in MIT News as Coactive's AI platform enables insight from visual content.

How Much Does Coactive AI Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Tier 1 Plan$75,000/year12-month contract for search and analytics platform for photos and videos, UX and API access, specified platform utilization includedAWS Marketplace
Additional Platform Utilization$1.00/unitOverage charges for usage beyond contract entitlements; unit definition not specifiedAWS Marketplace
Tier 1 Plan$75,000/year
12-month contract for search and analytics platform for photos and videos, UX and API access, specified platform utilization included
AWS Marketplace
Additional Platform Utilization$1.00/unit
Overage charges for usage beyond contract entitlements; unit definition not specified
AWS Marketplace

How Does Coactive AI Compare to Competitors?

FeatureCoactive AIScale AILabelboxV7 Darwin
Core FunctionalityAI visual search/tagging for images/videosData labeling/RLHFTraining data platform/RLHFDataset labeling/MLOps
Pricing (starting)$75k/yearCustom (opaque)Free tier + LBU$9k/year Starter
Free TierNoNoYesLimited
Enterprise FeaturesYes (custom contracts)YesYes (services)Yes (custom)
API AvailabilityYesYesYesYes
Integration CountAWS/GCP/AzureHigh volumeBroadAWS Marketplace
Support OptionsEnterprise salesCustomManaged servicesCustom quotes
Security CertificationsEnterprise-grade
Core Functionality
Coactive AIAI visual search/tagging for images/videos
Scale AIData labeling/RLHF
LabelboxTraining data platform/RLHF
V7 DarwinDataset labeling/MLOps
Pricing (starting)
Coactive AI$75k/year
Scale AICustom (opaque)
LabelboxFree tier + LBU
V7 Darwin$9k/year Starter
Free Tier
Coactive AINo
Scale AINo
LabelboxYes
V7 DarwinLimited
Enterprise Features
Coactive AIYes (custom contracts)
Scale AIYes
LabelboxYes (services)
V7 DarwinYes (custom)
API Availability
Coactive AIYes
Scale AIYes
LabelboxYes
V7 DarwinYes
Integration Count
Coactive AIAWS/GCP/Azure
Scale AIHigh volume
LabelboxBroad
V7 DarwinAWS Marketplace
Support Options
Coactive AIEnterprise sales
Scale AICustom
LabelboxManaged services
V7 DarwinCustom quotes
Security Certifications
Coactive AIEnterprise-grade
Scale AI—
Labelbox—
V7 Darwin—

How Does Coactive AI Compare to Competitors?

vs Scale AI

Coactive uses a multimodal AI strategy to target the search and tagging of visual content for Media/Ecommerce applications. Scale focuses on data labeling and Reinforcement Learning From Human Feedback. Coactive uses a transparent AWS Pricing Model and requires a higher entry price than Scale ($75k /year).

Coactive is used for media asset management, while Scale is used for training data pipelines.

vs Labelbox

Labelbox provides a free tier and a variable pricing structure for LBU (LabelBox University) based on customer needs related to ML Data (including services/RLHF). Coactive is an enterprise-focused solution for visual intelligence, and is more expensive than Labelbox, but claims that the ingestion cost will be 30-60% lower.

Labelbox is used for prototyping/scaling labeling, while Coactive is used for production visual search.

vs V7 Darwin

V7 uses a lower entry point ($9k/year - Starter) for customers who have clearly defined pricing for their datasets. Coactive positions itself as the premium offering for high volume video processing (>2k hours/hour ingestion), with model-agnostic BYOM (Bring Your Own Model) support.

V7 is used for small teams/datasets with a specific focus, while Coactive is used for large-scale enterprise video ingestions.

What are the strengths and limitations of Coactive AI?

Pros

  • Fast ingestion rate — can ingest up to 2,000 video hours in an hour
  • Reduced cost — ingestion is 30-60% less than traditional pipelines.
  • More accurate tagging — has 50% more accurate tag predictions without a training set
  • Flexibility of Models — allows for use of several different foundational models as well as “BYOM” which means you can bring your own models to the system
  • Scalable Platform — can ingest images, video, and audio while also providing semantic search
  • Integrates with large enterprises — supports AWS, GCP, Azure and other Cloud providers
  • Additional Revenue — generated an additional $500k in advertising revenue for one customer

Cons

  • A very expensive product — $75,000 per year and it is enterprise-only
  • One-year commitments — there are no refunds on this system and customers commit to 12 months at a time
  • Trial of product is not publicly available — requires a sale process and cannot be easily tested by potential customers
  • Ingestion rates beyond contracted amount have unclear unit definitions and charged at $1 per unit
  • Not suitable for Small/Medium Businesses — out of reach financially
  • Pricing is opaque — custom quote requests from CoActive are prevalent although they list prices for their services through AWS Marketplace
  • No Free Tier — unlike competitors such as Labelbox

Who Is Coactive AI Best For?

Best For

  • Large enterprises with visual content libraries — The justification for spending money on CoActive comes from two factors: 1) the ability to ingest large volumes of data (2k video hours/hour), and 2) 30-60% cost savings to do so and therefore justify a price point of $75,000 +
  • Media & entertainment companies — Provides Personalization, Moderation, Ad Revenue (has proven $500k case)
  • Retail/e-commerce with product imagery — Optimizes Content Personalization at Scale with AI Tagging/Search
  • Data science teams managing unstructured visuals — Reduces Operational Burden via Semantics Search, API Access and Model-Agnostic
  • Organizations with AWS infrastructure — Contracts are flexible — seamless deployment of CoActive to AWS Marketplace

Not Suitable For

  • Small/medium businesses — Entry Point Price is Too High — may want to consider V7 Starter ($9k) or Labelbox free tier instead
  • Teams needing quick prototyping — There is no Public Demo or Free Trial — requires sales commitment unlike Labelbox
  • Budget-conscious startups — Creates High Risk — due to non-cancellable annual contracts. Look at lower-entry alternatives.
  • Simple labeling needs — May be Overkill vs Scale/Labelbox — best suited for Visual Intelligence Use Cases that require Complex Visual Intelligence

Are There Usage Limits or Geographic Restrictions for Coactive AI?

Contract Duration
12-month minimum, non-refundable/non-cancellable
Base Utilization
Specified quantity included in Tier 1 ($75k); overages at $1/unit
Additional Usage
$1.00 per platform utilization unit (definition unspecified)
Pricing Model
Enterprise contracts only, no month-to-month
Trial Availability
No public trial; sales process required
Deployment
SaaS via AWS Marketplace, additional AWS infra costs may apply
Refund Policy
All fees non-refundable except as required by law

Is Coactive AI Secure and Compliant?

Enterprise-Grade SecurityDesigned for enterprise visual data management with cloud integrations (AWS/GCP/Azure)
SaaS InfrastructureHosted as SaaS on AWS Marketplace with scalability and reliability
Data ProtectionHandles sensitive visual content with AI moderation capabilities

What Customer Support Options Does Coactive AI Offer?

Channels
Primary channel for enterprise contracts and demosVendor contract support through AWS billing
Hours
Business hours via sales team
Response Time
Enterprise sales process; contract-based support
Satisfaction
Positive feedback on time savings and scalability (G2 reviews)
Specialized
Dedicated enterprise sales and success for $75k+ contracts
Business Tier
Custom support included in annual contracts
Support Limitations
•No self-serve support for free tier (none exists)
•Support tied to enterprise contracts only
•No live chat/phone mentioned for general users

What APIs and Integrations Does Coactive AI Support?

API Type
REST API with comprehensive endpoint coverage for datasets, models, and search operations
Authentication
Client ID and Client Secret credentials, with customizable base URL support for enterprise deployments
SDKs
Python SDK available (coactive package) with both synchronous and asynchronous client support; in beta with potential breaking changes between versions
Documentation
API documentation available at docs.coactive.ai with code examples, client setup guides, and Postman API Network collections for testing
Error Handling
Comprehensive error handling with ApiError base class and specific error types: BadRequestError (400), UnauthorizedError (401), ForbiddenError (403), NotFoundError (404), UnprocessableEntityError (429)
Configuration
Customizable timeout settings (default 60 seconds), custom base URL support, mypy type annotations for autocomplete and IDE support
Use Cases
Dataset creation and management, metadata generation from video/image/audio, semantic search queries across multimodal content, tagging and classification at scale, integration with S3 and cloud storage systems

What Are Common Questions About Coactive AI?

Can Handle Multimodal Content Including Video, Images, Audio — CoActive will automatically segment video into shots and audio into dialogue intervals for a complete semantic tagging and search capability across all three modalities at once.

Coactive supports bringing your own models (BYOM) through its support of AWS Bedrock, Azure AI and Databricks; and you can connect multiple models together for even greater insight and create custom fine-tuned models that reflect your business and industry.

Coactive has an intelligent keyframe sampling approach to reduce your compute cost by 6 to 10 times over other methods. Coactive stores processed output and executes a single process that generates all search, summarization, metadata and analytics results. Redundant processes are eliminated.

Coactive allows for natural language search, SQL style search, and multimodal search which searches both visually, audibly, and via transcriptions. Results are aligned to the exact time segment within the video allowing for the most accurate possible discovery of specific video content.

Coactive’s dynamic tag feature enables you to generate and assign tags based on natural language prompts at either the frame or video level. You may assign tags without training a model (zero-shot) or refine them with example data to increase their accuracy. Metadata is centralized and conforms to your custom taxonomy.

Yes, Coactive provides lineage tracking, so each asset and each transformation is tracked back to the specific version of each model that was utilized. This provides consistency in your output over iterations and provides the ability to track back to meet any compliance requirements.

Coactive can integrate through REST APIs and Python SDKs and will support your current technical stack. Your query results and metadata can be accessed via SQL or API, and Coactive’s model agnostic design separates metadata from embeddings to provide flexibility with your current technology stack.

As part of Coactive’s video and audio pre-processing capabilities, it segments video into shots and audio into intervals providing the foundation for extensive semantic tagging. Since this pre-processing is reused throughout your workflows and is available for searching, there is no need to re-process your content if your workflow evolves — your content will always be ready for additional analysis techniques.

Is Coactive AI Worth It?

Coactive is an advanced multimodal AI system designed for media and entertainment companies to leverage value from large video, image, and audio collections on a massive scale. Advanced preprocessing, flexible model architecture and composability of the platform differentiate Coactive from more basic tagging systems. Cost optimization functionality of Coactive also provides economic benefits for large-scale operations as it can provide up to 10 times greater compute savings than other solutions. Additionally, strong integration options and SQL query capabilities make it a good fit for large enterprises that require complex data workflows.

Recommended For

  • Large media and entertainment companies with video collections requiring sophisticated tagging and discovery
  • Content platforms needing semantic search and metadata generation across multimodal content
  • Broadcasting and studio companies developing content safety and brand protection workflow systems
  • AI/ML teams within large enterprises that want to develop their own models and have complete customization
  • Video-processing companies that operate on a large scale and have significant compute-cost issues

!
Use With Caution

  • Smaller teams and startups lacking AI/ML expertise — SDK is currently in beta and may be subject to breaking changes
  • Real time processing needs -- Coactive is optimized for batch/scheduled workflows
  • Companies requiring many prebuilt integrations -- BYOM will require additional integration work

Not Recommended For

  • Companies simply wanting to tag images with minimal multimodal capability — there are simpler and less expensive solutions available
  • No video content — Coactive is specifically optimized for video heavy workflows
  • Budget constrained teams — enterprise solution with premium pricing
Expert's Conclusion

Coactive is the best option for scalable media organizations which require accurate multimodal understanding, economic cost reduction, and control of their AI models.

Best For
Large media and entertainment companies with video collections requiring sophisticated tagging and discoveryContent platforms needing semantic search and metadata generation across multimodal contentBroadcasting and studio companies developing content safety and brand protection workflow systems

What do expert reviews and research say about Coactive AI?

Key Findings

Coactive is an architecture that is designed as a multimodal AI platform specifically for media and entertainment, with demonstrated capabilities for intelligent preprocessing, semantic searching, auto-tagging and fine tuning. The Coactive platform has emphasized both cost-effectiveness, achieved by using smart chunking which can save 6-10 times more in computing costs, and control via Bring Your Own Model (BYOM). The Coactive company has demonstrated enterprise readiness through API documentation, SDK options, and client case studies.

Data Quality

Good—comprehensive technical documentation from official website, PyPI SDK documentation, API reference guides, and case study with Emplifi. Product capabilities verified across multiple official sources. Pricing and detailed customer numbers not publicly disclosed. SDK noted as beta with potential breaking changes.

Risk Factors

!
SDK is in Beta State; therefore there may be breaking changes between versions of the SDK.
!
Limited Public Case Studies from clients and limited client numbers have been published.
!
Coactive is relatively specialized as it is primarily a media and entertainment platform versus being a general purpose AI platform.
!
Competitive Market of Multimodal AI Platforms are Emerging.
Last updated: February 2026

What Additional Information Is Available for Coactive AI?

Integration Partnerships

Coactive supports all the major cloud based AI platforms such as AWS Bedrock, Azure AI, and Databricks, and enables customers to use enterprise level AI infrastructure. Additionally, Coactive provides Direct S3 Support for Dataset Management and allows developers to test and develop their applications with Pre-built Postman Collections.

Customer Success - Emplifi

A Social Media Management Platform called Emplifi has integrated Coactive's API into their platform to enable cutting edge AI technology to analyze and understand their customers' content and media intelligence. This partnership showcases how Coactive can power SaaS Integrations for Media Intelligence Features.

Developer Experience

Coactive provides a wide range of developer tools including the Python SDK with async support, Type Annotations for IDE Autocomplete, Postman Collections for Testing and Development, and API Documentation located at docs.coactive.ai. The SDK contains Examples for creating datasets however the SDK is currently in Beta Status, thus, version pinning is advised.

Platform Architecture

The platform is built as a scalable and model-agnostic framework that keeps metadata separate from the embedding layer and allows chaining multiple models together. The framework can be optimized for either low-cost and high-performance captioning or for higher level multi-modal analysis based on customer needs and requirements.

Enterprise Features

Coactive has built-in lineage tracking for auditing and full transparency of model versions and supports SQL query-based analysis for analyzing large volumes of visual data. It also supports custom deployment through setting a base URL and is well-suited for enterprise-wide deployments.

What Are the Best Alternatives to Coactive AI?

  • •
    AWS Rekognition: Amazon Web Services (AWS) provides a fully-managed video and image analysis service called Rekognition that offers object detection, facial recognition, and content moderation. While Rekognition does provide some tagging capability, its primary purpose is for simple use-cases and native AWS deployments. Organizations currently leveraging AWS and require a basic form of video analysis without developing custom models are best suited to leverage Rekognition. (https://aws.amazon.com/rekognition)
  • •
    Google Cloud Video AI: Google Video AI is a video understanding platform developed by Google that performs shot detection, object tracking and label detection. While similar in capabilities to Coactive, Video AI is tightly integrated with the Google Cloud Platform (GCP). Therefore, organizations using GCP and want native integration with their cloud environment may find Video AI a good option. However, since Video AI does not allow users to bring their own model (BYOM), if an organization requires this functionality they should consider Coactive. (https://cloud.google.com/video-ai)
  • •
    Twelve Labs Pegasus: Twelve Labs is a video understanding platform powered by AI that focuses on providing semantic video search and indexing capabilities. Twelve Labs provides capabilities comparable to Coactive for video search and tagging, however; Twelve Labs places less focus on fine-tuning and creating custom models. Therefore, organizations that place a greater priority on semantic search capabilities than advanced customizations may prefer Twelve Labs. (https://twelvelabs.io)
  • •
    Clarifai: Clarifai is a Visual AI platform that supports image and video recognition and allows customers to train their own custom models. Clarifai takes a more general-purpose approach to Visual AI and supports many different use cases beyond just media and entertainment. As such, teams looking for a flexible Visual AI solution without the need for specific optimizations around media will likely find Clarifai to be the most suitable option. (https://www.clarifai.com)
  • •
    Wistia: Wistia is a video hosting and video analytics service that includes some simple video intelligence. It’s a simpler version of the other platforms I’ve mentioned that focus on hosting your videos and giving you an idea of how viewers are interacting with them in terms of time spent watching, etc. (It does not have advanced content analysis.) It would be good for small content creators who need to host their videos somewhere online, but do not want to spend money on analytics beyond basic numbers.

What Are Coactive AI's Classification Accuracy?

95 %
AI-Assisted Metadata
81 %
Zero-Shot Tagging

What Supported Data Types Does Coactive AI Offer?

Video

Automatic shot and audio segmentation of long form content.

Images

Automated visual content analysis and metadata generation.

Audio

Detection of dialogue intervals and audio signals within those intervals.

Cloud Storage

Storage of petabytes of data in either cloud or on-prem storage systems.

What Nlp Capabilities Does Coactive AI Offer?

Natural Language Search

Ability to query multiple types of video, audio and transcript based signals at once.

Named Entity Recognition

Identification of people, products and premises through VIP (Video Intelligence Platform) technology.

Dynamic Tags

The ability to create custom labels based on natural language prompts to identify specific objects, actions, people, etc., in the video.

Semantic Tagging

Understanding of domain specific context in relation to video content.

Content Moderation

Automated detection of potentially unsafe or offensive content.

Multimodal Fusion

The ability to analyze video, images and audio signals simultaneously.

What Is Coactive AI's Training Options?

Fine-Tuning
Custom fit to domain needs, decoupled and evaluable
Active Learning
Continuous feedback adapts tags to specific needs
No-Code Model Tuning
Uses natural language and reviews, no engineers required
Bring Your Own Models
Integrate via AWS Bedrock, Azure AI, Databricks
Custom Concepts
Organization-specific terms with model training
Model Chaining
Composable inference pathways for deeper analysis

What Integration Connectors Does Coactive AI Support?

AWS BedrockAzure AIDatabricksDigital Asset Management (DAM)Media Asset Management (MAM)REST APISQL API

What Are Coactive AI's Processing Specs?

2000 video hours/hour
Ingestion Rate
30-60 %
Cost Reduction
6-10x reduction
Compute Savings
Petabyte-scale video/images
Scale

What Compliance Certifications Does Coactive AI Have?

Content Safety ControlsBuilt-in protections against unsafe content
Lineage TracingFull auditability of assets and transformations
SOC 2
GDPR

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