ColBERTFuture Data Systems
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Related Products
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About
ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. It relies on fine-grained contextual late interaction: it encodes each passage into a matrix of token-level embeddings. At search time, it embeds every query into another matrix and efficiently finds passages that contextually match the query using scalable vector-similarity (MaxSim) operators. These rich interactions allow ColBERT to surpass the quality of single-vector representation models while scaling efficiently to large corpora. The toolkit includes components for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. ColBERT integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts.
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About
Company data stored in object storage as video, images, audio and documents can be difficult to search by content.
Mixpeek connects to your bucket and runs extractors over each file. A video becomes scenes, keyframes, transcripts, faces and on-screen text. A PDF becomes pages, tables and figures. Each piece is embedded and stored with its timestamps and source path.
Then you query it. Retrievers combine vector search, filters and reranking in one call. Taxonomies label files against your own categories. Clusters group what nobody has labeled yet.
It ships as an API, Python and JavaScript SDKs, an MCP server for agents, and Studio, a web app.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Academic researchers and developers seeking a tool for implementing and evaluating listwise reranking with large language models
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Audience
Developers, media and ad-tech teams, and data teams that keep large video, image, audio and document archives in S3, GCS or Azure.
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
$25/month
The Build plan starts at $25 per month and includes $10 in monthly usage credits; additional usage is billed based on consumption.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationFuture Data Systems
United States
github.com/stanford-futuredata/ColBERT
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Company InformationMixpeek
Founded: 2022
United States
mixpeek.com
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Categories |
Categories |
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Integrations
Amazon Bedrock
Not Supported
Amazon S3
Not Supported
Azure Blob Storage
Not Supported
Cloudflare R2
Not Supported
Fireworks AI
Not Supported
Google Cloud Storage
Not Supported
Model Context Protocol (MCP)
Not Supported
Mux
Not Supported
Together AI
Not Supported
iconik
Not Supported
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Integrations
Amazon Bedrock
Supported
Amazon S3
Supported
Azure Blob Storage
Supported
Cloudflare R2
Supported
Fireworks AI
Supported
Google Cloud Storage
Supported
Model Context Protocol (MCP)
Supported
Mux
Supported
Together AI
Supported
iconik
Supported
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