Use Cases

Docs

Pricing

Resources

Researchers

Get Access

Use Cases

Docs

Pricing

Resources

Researchers

Get Access

Generate Embeddings Without Infrastructure Headaches

A platform for generating embeddings from large datasets. Process billions of documents up to 20x faster and 90% cheaper.

Get Started

import sutro as so

import polars as pl

apple_patent_chunks = pl.read_parquet("apple-patent-chunks-4m.parquet")

results = so.infer(

apple_patent_chunks,

column="text",

model="qwen-3-embedding-8b",

job_priority=1,

)

print(results.head())

┌─────────────────────────────────┬─────────────────────────────────┐

│ text ┆ embedding │

│ --- ┆ --- │

│ str ┆ list[f64] │

╞═════════════════════════════════╪═════════════════════════════════╡

│ hine-learning model may determ… ┆ [-10.9375, -3.65625, … -1.1328… │

│ may be able to perceive that … ┆ [-10.5, -5.15625, … 0.4921875] │

│ cheering. However, for some a… ┆ [-7.75, -7.5625, … -0.408203] │

│ icult to differentiate from a … ┆ [-13.5, -8.0, … -4.09375] │

│ when the video was taken, as d… ┆ [-10.1875, -6.5625, … -2.84375… │

└─────────────────────────────────┴─────────────────────────────────┘

From Raw Data to Vector DB, Faster

Generate Embeddings in Minutes, Not Days

Process billions of tokens at a time. Our purpose-built batch engine is optimized for embedding workloads, delivering results up to 20x faster.

Slash Your Embedding Costs

Up to 90% cost reduction. Efficient job packing and resource allocation make large-scale vectorization financially feasible, even for massive backfills.

Simple SDK, No Infrastructure Hell

Abstract away rate limits, backoffs, and parallelization. Replace brittle processing scripts with a few lines of code. We handle the errors, you get the vectors.

Any Model, Any Scale

Use powerful open-source models or your own private models. Scale from a small sample to your entire dataset with the same simple code.

Powering the Next Wave of AI Applications

RAG & Semantic Search

Build comprehensive vector indexes for your RAG pipelines. Embed your entire knowledge base—docs, tickets, messages—to provide accurate, context-aware answers.

Improve Search & Retrieval Products

Generate Q&A pairs and related synthetic data to improve semantic retrieval performance.

Data Clustering & Analysis

Vectorize your entire dataset to uncover hidden patterns, group similar items, and perform large-scale topical analysis.

Data Backfills & Re-Indexing

Running a new model? Re-indexing your database? Effortlessly backfill embeddings for billions of items without writing custom infrastructure.

Classification & Feature Engineering

Generate consistent, high-quality embeddings to use as features for downstream machine learning models.

Literature Search Engines

Embed massive corpora of scientific literature, legal, texts, or patent data to accelerate research and discovery.

Powering the Next Wave of AI Applications

RAG & Semantic Search

Build comprehensive vector indexes for your RAG pipelines. Embed your entire knowledge base—docs, tickets, messages—to provide accurate, context-aware answers.

Improve Search & Retrieval Products

Generate Q&A pairs and related synthetic data to improve semantic retrieval performance.

Data Clustering & Analysis

Vectorize your entire dataset to uncover hidden patterns, group similar items, and perform large-scale topical analysis.

Data Backfills & Re-Indexing

Running a new model? Re-indexing your database? Effortlessly backfill embeddings for billions of items without writing custom infrastructure.

Classification & Feature Engineering

Generate consistent, high-quality embeddings to use as features for downstream machine learning models.

Literature Search Engines

Embed massive corpora of scientific literature, legal, texts, or patent data to accelerate research and discovery.

Powering the Next Wave of AI Applications

RAG & Semantic Search

Build comprehensive vector indexes for your RAG pipelines. Embed your entire knowledge base—docs, tickets, messages—to provide accurate, context-aware answers.

Improve Search & Retrieval Products

Generate Q&A pairs and related synthetic data to improve semantic retrieval performance.

Data Clustering & Analysis

Vectorize your entire dataset to uncover hidden patterns, group similar items, and perform large-scale topical analysis.

Data Backfills & Re-Indexing

Running a new model? Re-indexing your database? Effortlessly backfill embeddings for billions of items without writing custom infrastructure.

Classification & Feature Engineering

Generate consistent, high-quality embeddings to use as features for downstream machine learning models.

Literature Search Engines

Embed massive corpora of scientific literature, legal, texts, or patent data to accelerate research and discovery.