Oriane

What is Oriane?

Oriane is an AI-powered video intelligence platform for brands. It helps you search across millions of videos to find relevant brand, product, creator, and context moments, then use the results to plan content, identify creators, and track performance.

Unlike tools that rely only on text or creator profiles, Oriane analyzes what appears in videos (including on-screen elements and spoken content) so you can query video content directly—using text search, visual description, or uploaded images.

Key Features

• Video search that analyzes content, not just text: Oriane evaluates what’s on screen and what’s being said, along with captions, products, logos, and surrounding context.
• Multiple ways to search: Search with text, describe a visual, or upload an image to find matching video moments.
• Cross-platform matching for video moments: Searches identify relevant moments across TikTok, Instagram, and YouTube.
• Downloadable, analysis-ready datasets: Export rich CSV data from any search, including views, engagement, creator details, transcripts, and visual tags.
• One workflow across planning and measurement: Use insights from the same dataset to support content strategy, creator partnership decisions, brand-safety checks, and ROI tracking.

How to Use Oriane

1. Start a search: Describe what you want to find (for example, an unboxing product moment, a competitor’s logo, or a trending visual style).
2. Review matching moments: Oriane returns results based on analyzed video content, including transcripts and visual tags.
3. Export results: Download the data as CSV for further analysis in tools such as Claude or your own pipeline.
4. Apply insights: Use the dataset to build content plans, map creator partnerships, run brand safety checks, and track campaign ROI.

Oriane also supports starting with an uploaded image or a visual description if you don’t have a text query.

Use Cases

• Detect trends and content opportunities: Search for an industry, product, or visual aesthetic to see what matching moments are performing, then translate that into a content plan.
• Competitor research: Look up competitor brand or product references (e.g., logos or featured items) to find where and how competitors appear in video content.
• Find and vet creators based on video evidence: Identify creators based on what they show and say in their videos rather than relying only on bio information or follower counts.
• Brand safety checks: Use the searchable, transcript- and tag-aware dataset to review contexts around brand or product mentions.
• Measure and optimize creator partnerships: Track engagement outcomes using the exported dataset and apply the same results to ROI tracking and campaign adjustments.

FAQ

• What types of inputs can I use to search? Oriane supports searching with text, describing a visual, or uploading an image.

• Which video platforms does Oriane search? The site states Oriane searches across TikTok, Instagram, and YouTube.

• What data can I export from a search? Oriane offers rich CSV exports including views, engagement, creator details, transcripts, and visual tags.

• How is Oriane different from traditional social listening? The platform is described as “video-first,” analyzing the content of videos (on-screen elements and spoken/caption information) rather than reading only text or creator profiles.

• Can I use the exported data for analysis tools? The site notes you can feed the CSV output into Claude or your own analysis pipeline.

Alternatives

• Text-based social listening tools: These focus on captions, posts, or profile metadata rather than analyzing the actual video content, which can limit direct discovery of product or brand moments inside videos.
• Influencer discovery platforms: Often centered on creator profiles and follower metrics, they may not support searching by what a creator demonstrates or says in specific video contexts.
• General media search and analytics: Approaches that index only metadata or manually categorized content can require more manual work to achieve transcript and visual-tag-based search.
• Analytics workflows built on manual transcription + tagging: Teams can replicate parts of the workflow using transcription and tagging pipelines, but it typically requires more setup compared with a dedicated video intelligence search engine.