Mixpeek
Multimodal video search API: find any scene by description
A strong pick for video-heavy multimodal search with minimal glue code. Its managed indexing and cross-modal joins beat plain vector DBs for scene-level work, but it's overkill for pure text or simple vector search. Start with the free tier to test on your own buckets.
- Advertising agencies needing talent search and brand safety across video libraries
- Entertainment companies requiring scene search and archive access
- E-commerce teams for visual search and product discovery page enrichment
- Educational institutions for lecture search and transcript Q&A
- Pure text or tabular data search – simpler vector DBs are more cost-effective
- Teams needing full control over feature extraction pipelines
- Organizations without object storage infrastructure (S3/GCS/R2 required)
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Skip Mixpeek if you only need simple vector search on text or tabular data, or if you don't have existing object storage (S3/GCS/R2) set up.
The Multimodal Extractor costs $0.05 per minute of video, which can add up quickly for large libraries.
Mixpeek's pricing fits mid-size teams with existing video archives; the Pro tier ($99/mo) is cheaper than comparable managed services like Twelve Labs for moderate usage, but the $0.05/min video extraction fee is higher than some alternatives. For startups with small archives, the free tier is generous.
In short
Mixpeek — Multimodal video search API: find any scene by description. Best for Advertising agencies needing talent search and brand safety across video libraries, Entertainment companies requiring scene search and archive access, E-commerce teams for visual search and product discovery page enrichment. Free to start; paid plans from $25/mo.
What's new in Mixpeek
Checked 13 days agoAcross the latest 5 updates: 4 feature updates and 1 changelog entry.
Docs Feature: Searchable home for every technical guide
The 70+ vendor-neutral guides now have a searchable, category-filtered home at /guides.
Engine Performance: Steadier extraction and storage sync under heavy load
Two fairness fixes: GPU job admission is now capacity-aware, and storage-sync dispatches are prioritized.
Studio Feature: Cluster visualization overhaul — Atlas-level exploration
Cluster view upgrade with color-by-field, similarity-threshold slider, result pager, and image preview.
Multimodal Extractor v2 with Gemini Embedding 2
New multimodal extractor generates 3072D embeddings using Gemini Embedding 2 for richer cross-modal search.
Plugin Marketplace
Publish, discover, and install custom extractors across organizations with typed SDK and CLI tools.
Viability Score
How likely is Mixpeek to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Multimodal search across video, images, audio, documents
- Auto-extract scenes, faces, OCR, transcripts, embeddings
- Multi-stage retrieval: filter, join, rerank in <100ms
- Managed Vector Store (MVS) with dense, sparse, BM25 search
- Multimodal Extractor v2 with Gemini Embedding 2 (3072D embeddings)
- Face & person search across video libraries
- IP & copyright detection for logos, songs, faces
- Brand & ad safety pre-publish screening
- Speaker diarization aligned to transcript timeline
- Layout extraction from PDFs (header, body, charts, signature)
- Plugin Marketplace for custom extractors
- Cluster visualization with color-by-field, similarity slider
- Cross-modal joins at same object and timestamp
- Source adapters: Iconik, Webhook, Email, Supabase
- Deploy-resilient batch jobs with auto-resubmit
About Mixpeek
Mixpeek is a multimodal retrieval platform that indexes video, images, audio, and documents from object storage (S3, GCS, R2) and makes them searchable via natural language. Built for developers and data teams, it auto-extracts scenes, faces, OCR, transcripts, and embeddings at upload time. You can compose multi-stage search pipelines in under 100ms — filter, join, rerank across modalities — and use a managed vector store (MVS) supporting dense, sparse, and BM25 search. Recent updates include Multimodal Extractor v2 with Gemini Embedding 2 (3072D embeddings), a Plugin Marketplace for custom extractors, and cluster visualization improvements. Cross-modal joins tie features like faces, speakers, and OCR to the same object and timestamp, enabling queries like "find when our CEO said guidance while the slide read Q4 outlook." Unlike Pinecone or Weaviate, Mixpeek offers a perception layer with typed extractors (faces, layouts, speakers) out of the box, making it particularly strong for video-heavy use cases like talent search, brand safety, and scene retrieval.
Behind the Verdict
We'd reach for Mixpeek when our video library needs scene-level search without building custom extraction pipelines. The recent Multimodal Extractor v2 with Gemini Embedding 2 delivers richer embeddings for cross-modal queries, while the Plugin Marketplace allows sharing custom extractors across teams. The cluster visualization overhaul (color-by-field, similarity slider) makes exploring large archives more intuitive. In practice, the MVS path ($25/mo minimum) lets you bring your own vectors for deep integration. Where it bites: if you only need text or tabular search, a simpler vector DB like Pinecone is more cost-effective and has a lower learning curve. Also, you must have object storage (S3/GCS/R2) — no direct file upload support beyond what's in your buckets. The closest alternative is Twelve Labs, but Mixpeek's cross-modal joins and typed extractors give it an edge for complex queries spanning faces, text, and audio. For pure video understanding, Twelve Labs might be simpler; for joined multimodal search, Mixpeek wins.
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Real-world workflow fit
Concrete scenarios for the personas Mixpeek actually fits — and what changes day-one when you adopt it.
You need to find all scenes in a 10K-hour video library where a specific celebrity appears.
Outcome: Upload bucket to S3, connect via Mixpeek, run face search — results in milliseconds with timestamps, ready for editorial reuse.
You want to build a visual recommendation system that suggests products based on scene similarity.
Outcome: Index product images, configure retriever with visual embeddings, deploy recommendation endpoint in a day.
You need to screen user-uploaded videos for copyrighted logos before publication.
Outcome: Set up a retriever with IP detection extractor, auto-flag violations in real-time, reduce manual review by 80%.
Use Cases
- Search for a specific face across thousands of hours of video in milliseconds.
- Detect copyrighted logos or songs in user-generated content before publication.
- Build a visual recommendation system that ranks scenes by similarity using reinforcement learning.
- Automatically transcribe and index lecture videos for natural language Q&A.
- Screen ad creatives against brand safety blacklists at bid-time speeds.
- Find the exact frame in a video where a person says a specific phrase.
- Auto-label datasets using taxonomy-driven classification and feedback loops.
Models Under the Hood
as of 2026-07-05
Limitations
- The free tier is limited to 1 GB storage and 1K credits/month, insufficient for moderate-scale projects.
- Pricing scales with storage and extractor usage — the Multimodal Extractor costs $0.05/min of video, which can become expensive for large libraries.
- Real-time streaming ingestion is not advertised.
as of 2026-07-02
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Mixpeek tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Developers exploring Mixpeek with small test buckets (under 1K credits/month).
What this tier adds
Free entry point with 1K credits/month, 3 collections, and basic extractors.
Build
$25/mo minimum
Scale
$250/mo minimum
Enterprise
Custom
Ideal for
Large organizations requiring single-tenant deployment, SSO, and custom integrations.
What this tier adds
Custom pricing with unlimited collections, single-tenant infrastructure, custom model training, and dedicated support.
Where the pricing makes sense
The company stage and team size where Mixpeek's pricing actually pencils out — and where peers do it cheaper.
Mixpeek's pricing fits mid-size teams with existing video archives; the Pro tier ($99/mo) is cheaper than comparable managed services like Twelve Labs for moderate usage, but the $0.05/min video extraction fee is higher than some alternatives. For startups with small archives, the free tier is generous.
Setup time & first value
How long it actually takes to get something useful out of Mixpeek — broken out by persona, not the marketing-page minute.
For developers: first search in under 10 minutes using the Quickstart guide. Connecting an S3 bucket and configuring basic extraction takes about 30 minutes. Full pipeline with multi-stage retrievers may take a few hours.
Switching to or from Mixpeek
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Pinecone: You can keep your vectors and use Mixpeek's MVS (first 1M free), adding extraction for file-based data.
- →From Elasticsearch: Migrate text indexes and combine with multimodal extraction via Mixpeek's migration guides.
- ↗To Pinecone: Export vectors via the API and re-index in Pinecone, but you'll lose the perception layer.
Integrations
Resources & Guides
- Documentationmixpeek.com
Introduction
Mixpeek gives AI agents the ability to see, hear, and understand multimodal content
- Tutorialmixpeek.com
Tutorials
Step-by-step guides to build with Mixpeek
- Learnmixpeek.com
Multimodal Data Infrastructure
Multimodal data infrastructure for AI applications.
- Resourcemixpeek.com
Release Notes
Stay up to date with the latest Mixpeek features and performance improvements. Deep links to docs and examples for every release.
- Resourcemixpeek.com
Blog - Insights on Multimodal AI
Multimodal data infrastructure for AI applications.
- Documentationmixpeek.com
Llms
Full product docs from mixpeek.com
Tutorials & Learning
Official links
Tools that pair well with Mixpeek
Common stack mates teams adopt alongside Mixpeek, with the specific reason each pairing earns its keep.
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