Welcome to Structify!¶
We power you to collect, enrich, and update your own custom datasets using our AI agents, built and trained right here at Structify. Structify allows you transform any information from document to web page into structured data with as little as two API calls.
# First, define the schema of your dataset using our Python Objects
table = Table(
name="company",
description="a private company that is interested in raising capital",
properties=[
Property(name="name", description="The name of the company"),
Property(name="business_description", description="The description of the company"),
Property(name="location", description="The location of the company"),
Property(name="website", description="The website of the company", prop_type="URL"),
]
)
# Next, create a dataset with that schema
structify.datasets.create(
name="startups",
description="A dataset of private companies that are interested in raising capital",
tables=[table],
relationships = []
)
# Then, create an agent to index information from defined sources for your dataset
structify.structure.run_async(
dataset="startups",
source=SourceWeb(web=SourceWebWeb(starting_urls=["https://www.techcrunch.com/"])),
save_requirement=[RequiredProperty(table_name="company", property_name="name")]
)
After reading our API documentation, you will be able to use our Python client to do things like:
Create a personalized dataset representing the job history of everyone in your network
Monitor changes in a continuously updating dataset of real estate listings
Extract structured data about startup financing events from a collection of SEC filings and pitch decks
Automate notifications when a new job listing is posted that matches your criteria
Keep reading to learn more about how to use Structify to supercharge your team or an AI tool.
Get Started with Structify¶
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Schema Cookbook¶
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