Moderate - Trust & Safety
Visual Moderation
Text Moderation
Audio Moderation
CSAM Detection
Demographic Attributes
Detect Objects & Scenes
OCR
Contextual Scene Classification
Detect AI Content
AI-Generated Content Classification
Detect People & Identity
Likeness Detection
Logo & Logo Location
Celebrity Recognition
Generate
Image Generation
Video Generation
Hive Vision Language Model
Translate
Speech-to-Text
Translation
Search
Custom Search
Reverse Image Search
Media Search
Platform
Custom Training - AutoML
Moderation Review Tool
Technology & Digital Platforms
For Online Communities
For Streaming Platforms
For Marketplaces
For Generative AI Apps
For Gaming Companies
For Dating Apps
For Rideshare and Delivery Services
For Music Companies
Media & Sports
For Brands
For Publishers
For Agencies
For Teams and Leagues
Risk & Identity Management
For U.S. Government Agencies
For Insurance Companies
For Financial Services
Use Cases
Content Moderation
Sponsorship Intelligence
Ad Intelligence
Context-Based Ad Targeting
Careers
About Us
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Hive Vision Language Model (VLM) brings flexible, prompt-based visual understanding to production vision tasks. With Hive VLM, teams can use natural language to define their policy and classify images, video, and text through a single endpoint. But production workflows often need more than flexible prompting — they also need control. That is why we are […]
Hive tackled key challenges related to Spark, and why our product is better for it. Read more to learn how we go about coding problem solving.
Who Watched the Oscars? A Close Up on This Premium Audience
We’ve created a data platform including Apache Spark applications that use Mesos as a resource manager. Using Spark & Mesos together is a relatively new idea with incomplete documentation.
“Who Won the Super Bowl LIII Ad Game?” – An interview with Dan Calpin
AI Makes the Call: These Brands Scored in Super Bowl Exposure
We achieved major recall and performance boosts against state-of-the-art methods for content-based image retrieval and approximate nearest neighbors tasks.
