Your agent is only as smart
as its retrieval.

Search text, PDFs, tables, images, and videos across 100+ languages. No infrastructure, no embeddings to tune, no 3-stage pipeline to manage.

Get Started

One API. Every modality. End to End.

1

Upload

Supports text, images, PDFs, video, and audio across 100+ languages.

Mixedbread automatically understands and processes your data with our own models and search engine.

2

Search

Perfect results in sub 200ms. High-quality parsed content ready for any downstream task and your AI.

1
from mixedbread import Mixedbread
2
from pathlib import Path
3
4
client = Mixedbread()
5
6
client.stores.files.upload(
7
  store_identifier="my-store",
8
  file=Path("api_handler.py"),
9
)
10
11
results = client.stores.search(
12
  store_identifiers=["my-store"],
13
  query="How do we validate API tokens?",
14
)
Try with
and more
Higher accuracy. Fewer tool calls.
Mixedbread delivers state-of-the-art accuracy on agentic search evals while using a fraction of the tool calls.
View all evals
Pushing the frontier of retrieval.
Our latest work on retrieval, embeddings, and multimodal search.
  1. mxbai-rerank-v3.1-listwise
    Meet listwise v3.1, a small upgrade to listwise v3. Now in Mixedbread Search, matching gpt-5.6-sol (high) quality at 61x lower latency.
  2. 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.
  3. 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.
  4. 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.
All the tools you need.
Integrate the best search into your workflow.
Dashboard
Get started with our platform
SDK
Build with Python or TypeScript
MCP
Integrate search in your favorite LLM
Skills
Drop-in recipes for coding agents
Claude Code
Give your coding assistant the right context
CLI
Sync thousands of documents in minutes
SOC2 Type II
Certified security
ISO 27001
Certified compliance
Region Deploy
Deploy in your region
On-premise
Self-hosted available
Stop tuning embeddings. Start shipping.
Free to try. Production-ready in minutes.
Start shipping