High-throughput inference for high-leverage AI and data teams
High-throughput inference for high-leverage AI and data teams
Securely transform, structure, and generate unstructured datasets at the speed of thought. 20x faster, 10x cheaper, near-limitless scale - all via one simple Python SDK
From Idea to Millions of Requests, Simplified
Sutro takes the pain away from testing and scaling LLM batch jobs to unblock your most ambitious AI projects.
import sutro as so
from pydantic import BaseModel
class ReviewClassifier(BaseModel):
sentiment: str
user_reviews = '.
User_reviews.csv
User_reviews-1.csv
User_reviews-2.csv
User_reviews-3.csv
system_prompt = 'Classify the review as positive, neutral, or negative.'
results = so.infer(user_reviews, system_prompt, output_schema=ReviewClassifier)
Progress: 1% | 1/514,879 | Input tokens processed: 0.41m, Tokens generated: 591k
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Rapidly Prototype
Shorten development cycles by getting feedback from large batch jobs in as little as minutes before scaling up.
Reduce Costs
Get results faster and reduce costs by 10x or more by parallelizing your LLM calls through Sutro.
Scale Effortlessly
Confidently handle millions of requests, and billions of tokens at a time without the pain of managing infrastructure.
From Idea to Millions of Requests, Simplified
Sutro takes the pain away from testing and scaling LLM batch jobs to unblock your most ambitious AI projects.
import sutro as so
from pydantic import BaseModel
class ReviewClassifier(BaseModel):
sentiment: str
user_reviews = '.
User_reviews.csv
User_reviews-1.csv
User_reviews-2.csv
User_reviews-3.csv
system_prompt = 'Classify the review as positive, neutral, or negative.'
results = so.infer(user_reviews, system_prompt, output_schema=ReviewClassifier)
Progress: 1% | 1/514,879 | Input tokens processed: 0.41m, Tokens generated: 591k
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Rapidly Prototype
Shorten development cycles by getting feedback from large batch jobs in as little as minutes before scaling up.
Reduce Costs
Get results faster and reduce costs by 10x or more by parallelizing your LLM calls through Sutro.
Scale Effortlessly
Confidently handle millions of requests, and billions of tokens at a time without the pain of managing infrastructure.
From Idea to Millions of Requests, Simplified
Sutro takes the pain away from testing and scaling LLM batch jobs to unblock your most ambitious AI projects.
import sutro as so
from pydantic import BaseModel
class ReviewClassifier(BaseModel):
sentiment: str
user_reviews = '.
User_reviews.csv
User_reviews-1.csv
User_reviews-2.csv
User_reviews-3.csv
system_prompt = 'Classify the review as positive, neutral, or negative.'
results = so.infer(user_reviews, system_prompt, output_schema=ReviewClassifier)
Progress: 1% | 1/514,879 | Input tokens processed: 0.41m, Tokens generated: 591k
█░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
Rapidly Prototype
Shorten development cycles by getting feedback from large batch jobs in as little as minutes before scaling up.
Reduce Costs
Get results faster and reduce costs by 10x or more by parallelizing your LLM calls through Sutro.
Scale Effortlessly
Confidently handle millions of requests, and billions of tokens at a time without the pain of managing infrastructure.
Pricing That Scales
A Simple Workflow For Batch Jobs
A Simple Workflow For Batch Jobs
Prototype
Test prompts and models on a small sample. Get feedback in minutes.
Scale
Scale
Scale
Scale your LLM workflows so your team can do more in less time. Process billions of tokens in hours, not days, with no infrastructure headaches or exploding costs.
Progress: 1% | 1/2.5M Rows
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Progress: 1% | 1/2.5M Rows
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Progress: 1% | 1/2.5M Rows
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Data Orchestrators
Object Storage and Open Data Formats
Notebooks and Pythonic Coding Tools
Data Orchestrators
Object Storage and Open Data Formats
Notebooks and Pythonic Coding Tools
Data Orchestrators
Object Storage and Open Data Formats
Notebooks and Pythonic Coding Tools
Integrate
Seamlessly connect Sutro to your existing LLM workflows. Sutro's Python SDK is compatible with popular data orchestration tools, like Airflow and Dagster.
Built For Any Research workload
Synthetic Data Generation
Create high-quality instruction-tuning datasets at scale.
Synthetic Data Generation
Create high-quality instruction-tuning datasets at scale.
Scale RL Rollouts
Run high-speed, large-scale model rollouts to continuously improve task-specific model performance.
Scale RL Rollouts
Run high-speed, large-scale model rollouts to continuously improve task-specific model performance.
Large-Scale Model Evals
Rigorously test model performance across millions of data points.
Large-Scale Model Evals
Rigorously test model performance across millions of data points.
Agentic Simulations
Simulate thousands of interacting agents to test emergent behaviors.
Agentic Simulations
Simulate thousands of interacting agents to test emergent behaviors.
Population and Market Modeling
Run social simulations against massive populations of synthetic respondents and economic agents.
Population and Market Modeling
Run social simulations against massive populations of synthetic respondents and economic agents.
Scientific Modeling
Run large-scale simulations for genomics, climate science, and more.
Scientific Modeling
Run large-scale simulations for genomics, climate science, and more.
Purpose-Built Tools for Scalable LLM Workflows
Ship faster results without complex infrastructure to scale up any LLM workflow.
Synthesize
Generate high-quality, diverse, and representative synthetic data to improve model or RAG retrieval performance, without the complexity.
Classify
Automatically organize your data into meaningful categories without involving your ML engineer.
Evaluate
Benchmark your LLM outputs to continuously improve workflows, agents and assistants, or easily evaluate custom models against a new use-case.
Extract
Transform unstructured data into structured insights that drive business decisions.
Embed
Easily convert large corpuses of free-form text into vector representations for semantic search and recommendations.
Label
Enrich your data with meaningful labels to improve model training and data preparation.
Purpose-Built Tools for Scalable LLM Workflows
Ship faster results without complex infrastructure to scale up any LLM workflow.
Synthesize
Generate high-quality, diverse, and representative synthetic data to improve model or RAG retrieval performance, without the complexity.
Classify
Automatically organize your data into meaningful categories without involving your ML engineer.
Evaluate
Benchmark your LLM outputs to continuously improve workflows, agents and assistants, or easily evaluate custom models against a new use-case.
Extract
Transform unstructured data into structured insights that drive business decisions.
Embed
Easily convert large corpuses of free-form text into vector representations for semantic search and recommendations.
Label
Enrich your data with meaningful labels to improve model training and data preparation.
Purpose-Built Tools for Scalable LLM Workflows
Ship faster results without complex infrastructure to scale up any LLM workflow.
Synthesize
Generate high-quality, diverse, and representative synthetic data to improve model or RAG retrieval performance, without the complexity.
Classify
Automatically organize your data into meaningful categories without involving your ML engineer.
Evaluate
Benchmark your LLM outputs to continuously improve workflows, agents and assistants, or easily evaluate custom models against a new use-case.
Extract
Transform unstructured data into structured insights that drive business decisions.
Embed
Easily convert large corpuses of free-form text into vector representations for semantic search and recommendations.
Label
Enrich your data with meaningful labels to improve model training and data preparation.
Common Use Cases
Unlock Product Insights
Easily sift through thousands of product reviews and unlock valuable product insights while brewing your morning coffee.
Unstructured ETL
Convert your massive amounts of free-form text into analytics-ready datasets without the pains of managing your own infrastructure.
Personalize Content
Tailor your marketing and advertising efforts to thousands, or millions of individuals, personas, and demographics to dramatically increase response rates and ad conversions.
Enrich Data
Improve your messy product catalog data, enrich your CRM entries, or gather insights from your historical meeting notes without involving your machine learning engineer.
Structure Web Pages
Crawl millions of web pages, and extract analytics-ready datasets for your company or your customers. Run standalone or successive batch jobs to explore complex link tree structures.
Improve Model Performance
Improve your LLM or RAG retrieval performance with synthetic data. Generate diverse and representative responses to fill statistical gaps.
Synthetic Data Generation
Create high-quality instruction-tuning datasets at scale.
Scale RL Rollouts
Run high-speed, large-scale model rollouts to continuously improve task-specific model performance.
Large-Scale Model Evals
Rigorously test model performance across millions of data points.
Agentic Simulations
Simulate thousands of interacting agents to test emergent behaviors.
Population and Market Modeling
Run social simulations against massive populations of synthetic respondents and economic agents.
Scientific Modeling
Run large-scale simulations for genomics, climate science, and more.