Mixedbread
mixedbread.com
AI Development Tools
AI Agents
Vector Search & RAG
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Financials
Funding and backers
Total raised
$6.4M
2 rounds on record
Latest round
$5.5M
Seed · 2025 · 15 mo ago
Team
11-50
employees, estimated range
The money's age
Due for its next round
15 months since the last round · not hiring
Momentum
0/100
no fresh signals
Last sign of life
this month
a posting or a news item
The story so fareach stage dated by its source: the company's releases, the press, registers, filings
Aug 14
On the Hacker News front page Introducing Toast 1 · 219 points
Jun 29
On the Hacker News front page Asymmetric Quantization: Near-Lossless Retrieval with 97% Storage Reduction · 110 points
Oct 10, 2025
On the Hacker News front page Show HN: Semantic search over the National Gallery of Art · 145 points
Oct 7, 2025
Launched on Hacker News Show HN: Search 4 Cute Cats
2025
Raised a round Seed $5.5M
2024
Raised a round Pre-Seed $860k
2023
Founded
Tractionpublic signals, read monthly
Funding rounds
| Round | Date | Amount | Investors | Source |
|---|---|---|---|---|
| Seed | 2025 | $5.5M | — | seedtable.com |
| Pre-Seed | 2024 | $860k | — | crunchbase.com |
Founders and leadersfrom filings, registers and the company's site
Aamir ShakirCo-founder
Julius LippCo-founder
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Overview
Mixedbread builds retrieval infrastructure that lets AI agents search company documents, slides, code, videos and workplace data. The platform handles parsing, OCR, transcription, chunking, embedding and indexing, and combines its Toast search agent, Wholembed omnimodal embedding model, a listwise reranker and the Silo multi-vector database on object storage, after releasing open-weight embedding and reranking models on Hugging Face. Founded in Berlin in 2023 by Aamir Shakir and Julius Lipp, it reports more than five billion indexed documents, customers such as Vercel and Prime Intellect, and a $5.5 million seed round in 2025.
News
Building a Robust Ingestion System for Any File of Any Size
A 300GB video does not fit on one machine, and a 4MB PDF can render into gigabytes of images. This is how our slicer and parser architecture processes arbitrary files with bounded compute and memory.
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Report
Asymmetric Quantization: Near-Lossless Late Interaction Retrieval with 97% Storage Reduction
Late interaction makes retrieval more precise but turns every document into many vectors. Asymmetric quantization keeps query vectors precise and stores document vectors as binary signs, cutting corpus storage 32x while holding 89.65 vs 90.26 NDCG@10.
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Dense Retrievers Know More Than They Can Express
Demonstrating that dense retrieval models learn much more information than they can express through their usual scoring mechanism: they also contain an indexable, natural-language-like sparse vocabulary, which is plug-and-play with BM25.
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Beyond the Limit: Introduce Mixedbread Wholembed v3
Announcing Mixedbread Wholembed v3, our new unified omnimodal multilingual retrieval model, setting a new state of the art for search across languages, modalities, and real-world retrieval tasks.
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Report
Inside Mixedbread: How We Built Multimodal Late-Interaction at Billion Scale
Technical deep-dive into Mixedbread Search - the first production-ready late-interaction search with native multimodality. Learn how we achieve 80ms end-to-end latency on billion-scale document collections.
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Mixedbread AI团队发布新一代超小型检索模型：17MB也能超越130MB巨头_腾讯新闻
这项来自Mixedbread AI的最新研究发表于2025年10月研究团队包括来自Mixedbread AI和早稻田大学的四位研究者：Rikiya Takehi、Benjamin Clavié、S....
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Report
Fantastic (small) Retrievers and How to Train Them: mxbai-edge-colbert-v0
Introducing our new family of extremely efficient ColBERT models, to serve as backbones for modern late interaction research while outperforming ColBERTv2 with just 17 million parameters.
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A Delicious Free Lunch: Better Projections Improve ColBERT
Discussing the unique learning constraints introduced by the MaxSim operator, and demonstrating that simple architecture improvements to accommodate for these limitations can increase performance in a free-lunch fashion.
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maxsim-cpu: Maximising Maxsim Efficiency
Introducing maxsim-cpu, a much faster way to compute the late interaction's MaxSim operator on modern CPU hardware, optimised for both x86 and Mac ARM.
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Report
The Hidden Ceiling: How OCR Quality Limits RAG Performance
Benchmarking shows OCR errors cap text-based RAG: top OCR still misses 4-5% NDCG@5, while Mixedbread's multimodal vector store beats perfect text by 12% and recovers 70% of lost answer accuracy.
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Products
Silo
A multi-vector database engine built on S3-compatible storage. It powers the platform's index.
mixedbread.com
Wholembed and mxbai rerank models
Omnimodal embedding model covering 100+ languages and a listwise reranker. Earlier mxbai embedding and reranking models are open weights on Hugging Face.
mixedbread.com
Mixedbread Search
Managed ingestion and retrieval over PDFs, video, code, Slack and Drive data for agents. It reports under 80 ms median search latency.
mixedbread.com
People
Aamir Shakir
Co-founder
Co-founded Mixedbread in 2023 after working as a research assistant at EPFL.
Julius Lipp
Co-founder
Co-founded Mixedbread in 2023 after working as a software developer at Crossnative; his LinkedIn headline now names a new company, so his current role is unclear.
Names and roles come from public filings, company registers and the company's own site. Is this you? Correct or remove · How we handle this data
Offices
Where the company hires and what each office is for
Cities
1
Hiring now
0
Countries
1
Berlin
Germany
HQ
10-50 est. staff