Welcome! Sensible is a developer-first platform for extracting structured data from documents, for example, business forms in PDF format. Sensible is highly configurable. You can get simple data about text and images in documents in minutes by leveraging GPT-4 and other large language models (LLMs), or you can tackle complex and idiosyncratic document formatting with Sensible’s powerful layout-based document primitives.
See the following list for an overview of going live with Sensible:
This guide gets you started with the first step, extracting data.
Let’s get started with extracting document data from an example bank statement. We’ll author a prompt for a large language model (LLM) to extract a checking account number in minutes.
In this guide, you’ll:
Get an account at sensible.so. If you don’t have an account, you can still read along to get a rough idea of how things work.
Log into the Sensible app
To view an example bank statement extraction, navigate to https://app.sensible.so/editor/instruct/?d=sensible_instruct_basics&c=bank_statement&g=bank_statement.
Sensible displays an example document in the left pane, and fields of extracted data in the right pane.
Take the following steps to create a prompt to extract more data from the document.
To extract document data automatically, take the following steps:
Click Query group:
Click Auto generate, then click Generate:
Sensible automatically generates queries and extracts their answers from the document:
(Optional) Add more queries by clicking Suggest queries, selecting the field IDs that interest you, and clicking Add selected queries:
To test the automatically generated extraction configuration with another document, see Test the prompt. To author your own extraction configurations, see the following steps.
checking account number (not savings)
in the query field. Click Extract.8347-32348
, in the Extracted data section:Congratulations! You extracted the checking account number from the bank statement.
To extract checking account numbers from other bank statements in production, publish the “config” containing your prompt.
Click Publish configuration, click Production, then click Publish to production:
Let’s see if the config containing your prompt works with other bank statements. To test the prompt, take the following steps:
8347-32348
to 9876-12345
:It looks like your prompt was successful at extracting the checking account number from another document. Great!
Try extracting more complex pieces of information. For example, try extracting the time period for each account using the List method. See the accounts_list
field in this config for an example of using the List method.
Publish the config to save your changes.
Sensible recommends grouping similar documents, for example, bank statments, into a document type. To extract data from your documents, first check if they’re on Sensible’s list of out-of-the-box supported document types. If not, create document types and configure your custom extractions by using the interactive tutorial or taking the following steps:
Explore extracting lists, tables, and single data points with other interactive examples:
For advanced extraction strategies, see Choosing an extraction approach
Get extracted document data out of Sensible and put it to work in Excel files, databases, and other destinations. See Integrating.
Welcome! Sensible is a developer-first platform for extracting structured data from documents, for example, business forms in PDF format. Sensible is highly configurable. You can get simple data about text and images in documents in minutes by leveraging GPT-4 and other large language models (LLMs), or you can tackle complex and idiosyncratic document formatting with Sensible’s powerful layout-based document primitives.
See the following list for an overview of going live with Sensible:
This guide gets you started with the first step, extracting data.
Let’s get started with extracting document data from an example bank statement. We’ll author a prompt for a large language model (LLM) to extract a checking account number in minutes.
In this guide, you’ll:
Get an account at sensible.so. If you don’t have an account, you can still read along to get a rough idea of how things work.
Log into the Sensible app
To view an example bank statement extraction, navigate to https://app.sensible.so/editor/instruct/?d=sensible_instruct_basics&c=bank_statement&g=bank_statement.
Sensible displays an example document in the left pane, and fields of extracted data in the right pane.
Take the following steps to create a prompt to extract more data from the document.
To extract document data automatically, take the following steps:
Click Query group:
Click Auto generate, then click Generate:
Sensible automatically generates queries and extracts their answers from the document:
(Optional) Add more queries by clicking Suggest queries, selecting the field IDs that interest you, and clicking Add selected queries:
To test the automatically generated extraction configuration with another document, see Test the prompt. To author your own extraction configurations, see the following steps.
checking account number (not savings)
in the query field. Click Extract.8347-32348
, in the Extracted data section:Congratulations! You extracted the checking account number from the bank statement.
To extract checking account numbers from other bank statements in production, publish the “config” containing your prompt.
Click Publish configuration, click Production, then click Publish to production:
Let’s see if the config containing your prompt works with other bank statements. To test the prompt, take the following steps:
8347-32348
to 9876-12345
:It looks like your prompt was successful at extracting the checking account number from another document. Great!
Try extracting more complex pieces of information. For example, try extracting the time period for each account using the List method. See the accounts_list
field in this config for an example of using the List method.
Publish the config to save your changes.
Sensible recommends grouping similar documents, for example, bank statments, into a document type. To extract data from your documents, first check if they’re on Sensible’s list of out-of-the-box supported document types. If not, create document types and configure your custom extractions by using the interactive tutorial or taking the following steps:
Explore extracting lists, tables, and single data points with other interactive examples:
For advanced extraction strategies, see Choosing an extraction approach
Get extracted document data out of Sensible and put it to work in Excel files, databases, and other destinations. See Integrating.