MVS Buildper month
$25/month
- Up to 1M vectors with BYO embeddings
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Start here for the decision-making essentials: what Mixpeek does, who it is for, how it is accessed, and the first-party sources behind this profile.
$25/month
$25/month
Mixpeek is a multimodal data processing and retrieval platform that makes media archives searchable by decomposing video, images, audio, and documents into features, combining hybrid dense/sparse/BM25 search, and returning timestamped results from existing object storage.
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Short answers to the questions buyers and builders commonly ask about Mixpeek. Each answer cites the shared ledger below, where every source is listed once.
Hybrid dense, sparse, and BM25 search with semantic JOINs, aggregations, and cross-shard t · multimodal data processing and retrieval platform · Turns stored video, image, and audio into ranked, timestamped results through one API for · Embeds multiple files from one object into a single 3072-d vector (one embedding per objec
Dense, sparse, and BM25 search.
Semantic retrieval across unstructured and multimodal data: video, images, audio, and PDFs · Professional video editors searching raw cinema footage (RED R3D, ARRI RAW) across cloud-s
Mixpeek is the semantic retrieval layer for unstructured and multimodal data
Holds no SOC 2 or HIPAA certification today · No European or Asia-Pacific hosted region; data sent to the hosted Service is processed in · multi_content query input is only valid for feature URIs backed by gemini_multifile_extrac
We hold no SOC 2 or HIPAA certification today
MVS Build | $25/month | up to 1M vectors, BYO embeddings · MVS Scale | $250/month | up to 25M vectors, priority support · Managed Build | $25/month | up to 100K objects/mo with included usage pool · Managed Scale | $250/month | up to 1M objects/mo, SSO, priority support
Build starts at $25/mo with up to 1M vectors
Python SDK, MCP server, REST API, and LangChain integration · Documents can be upserted via POST /v1/namespaces/{namespace_id}/documents/upsert; Enterpr
Python SDK, MCP, REST, and LangChain.
Self-hostable in customer's own cloud (BYO-Cloud) with encryption, RBAC, SSO, audit trails · Hosted SaaS plus self-hosting option for content residency · Stores extracted features on the customer's existing object storage, decomposed across cos
Deploy in your own cloud (BYO-Cloud) with encryption, role-based access, SSO, audit trails, and namespaces.
This profile connects the jobs Mixpeek is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
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Video Search API: Find Any Scene by Description | Mixpeek
Hybrid dense, sparse, and BM25 search capability · Semantic retrieval layer for unstructured and multimodal data · Modalities: video, images, audio, and documents
Hybrid dense, sparse, and BM25 search with semantic JOINs, aggregations, and cross-shard transactions
Semantic retrieval across unstructured and multimodal data: video, images, audio, and PDFs
MVS Build | $25/month | up to 1M vectors, BYO embeddings
MVS Scale | $250/month | up to 25M vectors, priority support
Managed Build | $25/month | up to 100K objects/mo with included usage pool
Managed Scale | $250/month | up to 1M objects/mo, SSO, priority support
Enterprise | $10,000/month | single-tenant dedicated infrastructure, SSO, audit logs, dedicated Slack support
Reads from existing S3, GCS, R2, Azure, or any S3-compatible bucket; customer's storage remains system of record
Self-hostable in customer's own cloud (BYO-Cloud) with encryption, RBAC, SSO, audit trails, and namespaces
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
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Mixpeek Studio can deploy a complete namespace from a template hosted on mixpeek.com/templates, with the inaugural video-moderation template provisioning one namespace, three buckets, eight collections, and six retrievers.
View source [5]Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
These tools share a workflow, capability or audience with Mixpeek. They may complement it rather than replace it, and are not presented as integrations or endorsements.
Python SDK, MCP server, REST API, and LangChain integration
Holds no SOC 2 or HIPAA certification today
multimodal data processing and retrieval platform
text, images, video, audio, and documents
Build | $25/month | up to 1M vectors
Mixpeek Inc.
915 Broadway, Suite 1200, New York, New York 10010
Google Cloud us-east1 and us-central1; AWS us-east-1 (United States only)
Hosted SaaS plus self-hosting option for content residency
Data encrypted in transit and at rest; production access restricted and logged
Professional video editors searching raw cinema footage (RED R3D, ARRI RAW) across cloud-stored media libraries
No European or Asia-Pacific hosted region; data sent to the hosted Service is processed in the United States regardless of customer location
Mixpeek
Make media and creative archives searchable by decomposing video, audio, images, and documents into features and reassembling them into ranked, timestamped answers on demand.
Turns stored video, image, and audio into ranked, timestamped results through one API for teams and agents, operating as a warehouse for unstructured data with multi-stage retrieval.
Video, audio, images, and documents
Stores extracted features on the customer's existing object storage, decomposed across cost tiers.
Single REST API for ingestion, retrieval, and search across multimodal assets
Runs nine managed extractors including intfloat/multilingual-e5-large-instruct (1024-d text), google/siglip-base-patch16-224 (768-d image), google/vertex-multimodal (1408-d), google/gemini-embedding-2 (3072-d), insightface ArcFace (512-d fa
Documents can be upserted via POST /v1/namespaces/{namespace_id}/documents/upsert; Enterprise supports POST /v1/namespaces/{namespace_id}/models for uploading custom Hugging Face-format weights.
Twitter (https://twitter.com/mixpeek), GitHub (https://github.com/mixpeek), LinkedIn (https://www.linkedin.com/company/mixpeek)
gemini-embedding-exp-03-07 (3072 dimensions)
Embeds multiple files from one object into a single 3072-d vector (one embedding per object, not per file)
Uses array input_mappings to collect multiple blob fields from one object into a single list for one API call
multi_content query input is only valid for feature URIs backed by gemini_multifile_extractor; using it with any other extractor returns a 400 error
Gemini Embedding 2 supports truncated dimensions for storage cost reduction
One charge covers all N files within an object (not per file)
Multimodal search across video, images, audio, and PDFs with timestamped results · Hybrid dense, sparse, and BM25 search combined via reciprocal-rank fusion · Automatic extraction of faces, scenes, transcripts, OCR, labels, and embeddings from raw f
