Algodocs API
★ Only Publicly Available OpenAPI DocumentData EnrichmentData TransformationapiKey10 EndpointsREST
For Agents
Upload PDFs and images to Algodocs, route them to an extractor, and retrieve structured JSON data for invoices, receipts, and other documents.
Use for: I need to upload an invoice PDF for data extraction, Get the structured JSON data extracted from a document, List every extractor configured in my Algodocs account, Pull all extracted data for an extractor for a nightly export
Not supported: Does not handle document signing, e-signature workflows, or generic file storage — use for routing documents to configured extractors and retrieving structured JSON only.
Jentic publishes the only available OpenAPI specification for Algodocs API, keeping it validated and agent-ready. Algodocs is an intelligent document data extraction service for invoices, receipts, and other structured documents. The REST API lets users upload documents (file or base64), route them to a configured extractor, list and inspect documents, organise them into folders, and retrieve the extracted JSON for downstream automation. Authentication uses an API key in the Authorization header.
Install Jentic One Beta
Connect the Algodocs API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Algodocs API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Algodocs API.
List the configured extractors in an Algodocs account with /extractors
Upload a document file via multipart with /documents/upload or as base64 with /documents/upload-base64
Inspect documents and their processing status with /documents and /documents/{id}
Retrieve extracted data for a single document via /documents/{id}/extracted-data
Pull all extracted data for an extractor in bulk for downstream loading
List the folders associated with an extractor to organise document batches
Use Cases
Patterns agents use Algodocs API for, with concrete tasks.
★ Invoice ingestion into accounting
An AP automation flow uploads supplier invoice PDFs to Algodocs by POSTing to /documents/upload with the chosen extractor id, polls /documents/{id} for completion, then pulls the structured JSON via /documents/{id}/extracted-data and writes line items into the accounting system. The integration replaces manual data entry with a controlled, auditable pipeline.
POST /documents/upload with the invoice file and extractor id, poll GET /documents/{id} for status, then GET /documents/{id}/extracted-data and post line items to the accounting system
Receipt capture from a mobile app
A receipt capture mobile app sends base64-encoded images to /documents/upload-base64 alongside the receipt extractor id. Algodocs returns a document id, and the app polls /documents/{id}/extracted-data once processing completes, displaying the parsed merchant, total, and date back to the user.
POST /documents/upload-base64 with the encoded image and extractor id, then GET /documents/{id}/extracted-data once status reports completion
Bulk extracted-data export to a warehouse
A data team exports all extracted data for a given extractor into a warehouse table once a day by calling /extractors/{extractorId}/extracted-data. Because the endpoint already returns structured JSON, the team avoids per-document polling for historical loads.
GET /extractors/{extractorId}/extracted-data with the date range and append the rows to the warehouse table
Agent-driven document parsing through Jentic
A Jentic agent receives an intent like 'extract data from this invoice' along with a file, uploads it to Algodocs, and returns the parsed JSON to the user. The agent never needs to handle the Authorization header — Jentic manages the credential and resolves the right extractor id from the user's account.
Search Jentic for 'extract data from a document', execute POST /documents/upload with the chosen extractor id, then chain GET /documents/{id}/extracted-data to return the structured JSON
Key Endpoints
10 endpoints — jentic publishes the only available openapi specification for algodocs api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
GET
/extractors
List all extractors
POST
/documents/upload
Upload a document for extraction
POST
/documents/upload-base64
Upload a base64-encoded document
GET
/documents/{id}
Retrieve a document and its status
GET
/documents/{id}/extracted-data
Retrieve extracted data for a document
GET
/extractors/{extractorId}/extracted-data
Retrieve all extracted data for an extractor
GET
/extractors
List all extractors
POST
/documents/upload
Upload a document for extraction
POST
/documents/upload-base64
Upload a base64-encoded document
GET
/documents/{id}
Retrieve a document and its status
GET
/documents/{id}/extracted-data
Retrieve extracted data for a document
GET
/extractors/{extractorId}/extracted-data
Retrieve all extracted data for an extractor
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
The Algodocs Authorization key is stored encrypted in the Jentic credential vault and injected at call time. The agent never sees the raw key in its prompt or response.
Intent-based discovery
Agents search Jentic by intent (e.g. 'upload an invoice for extraction'), and Jentic returns the matching Algodocs operation with its input schema, including the extractor id parameter.
Time to first call
Direct Algodocs integration: 1-2 days for upload handling, polling, and extracted-data parsing. Through Jentic: under an hour with search, load, and execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Algodocs API through Jentic.
Why is there no official OpenAPI spec for Algodocs API?
Algodocs does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Algodocs API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Algodocs API use?
Algodocs uses an API key sent in the Authorization request header. Jentic stores the key encrypted in its credential vault and injects the header at execution time so the raw key never enters the agent's prompt or response context.
Can I upload an invoice PDF for extraction with the Algodocs API?
Yes. POST /documents/upload as multipart with the file and the extractor id. Algodocs returns a document id you can poll with GET /documents/{id}; once processing completes, GET /documents/{id}/extracted-data returns the structured JSON.
What are the rate limits for the Algodocs API?
The OpenAPI spec does not declare rate limits. Algodocs enforces plan-based limits server-side, so throttle high-volume document uploads and consider the bulk extracted-data endpoint instead of per-document polling for backfills.
How do I extract data from a document through Jentic?
Search Jentic for 'extract data from a document', load the schema for POST /documents/upload, and execute it with the file and extractor id. Jentic chains the call to GET /documents/{id}/extracted-data once the document completes processing.
Can I send a base64-encoded document instead of a file upload?
Yes. POST /documents/upload-base64 with the encoded payload and the extractor id. This is useful for mobile clients that already hold the file bytes in memory and prefer not to write to disk.
GET STARTED