Go V7labs V7 Go API

Name: V7 Go API
Brand: V7 Go API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLMl InferenceapiKey, bearer274 EndpointsREST

For Agents

Run V7 Go AI document workflows: upload files, define properties to extract, execute skills and agent builders, and read structured results. Designed for high-volume document automation.

Install Jentic One Beta

Connect the V7 Go API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the V7 Go 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.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fgo.v7labs.com%2Fv7labs" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fgo.v7labs.com%2Fv7labs" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic 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 V7 Go API.

Upload and confirm file ingestion into a workspace project for AI extraction

Define properties on a project so V7 Go knows what fields to extract from each document

Execute agent-builder requests against entities to produce structured outputs

GET STARTED

Start building with V7 Go API

Explore with Jentic One

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for V7 Go API, keeping it validated and agent-ready. V7 Go is V7 Labs' AI workflow platform for processing unstructured documents into structured data using large language models. The API exposes workspaces, projects, properties, entities, files, hubs, skills, agent builders, MCP integrations, and case management - letting teams automate knowledge work like contract review, claims processing, and document extraction. It supports both API-key and bearer authentication and covers 274 endpoints for orchestrating AI agents, file uploads, tool integrations, and downstream reporting.

Use Cases

Patterns agents use V7 Go API for, with concrete tasks.

★ Contract Review Automation

Upload signed contracts to V7 Go and define properties such as effective date, governing law, and termination clause. The platform runs an extraction skill against each document and returns structured field values that an agent can write into a contract management system. The API handles file upload confirmation, property definition, and entity-level result retrieval.

Upload contract.pdf to project 7700, define properties for effective_date and counterparty, and return the extracted entity values.

Claims Processing Pipeline

Insurance teams stream claim documents through V7 Go to extract structured fields and route exceptions to human reviewers. The cases endpoint set lets an agent confirm tool runs, mark cases as read, and queue follow-up messages, so claim triage runs without manual document handling.

Process claim 4521 by uploading attachments, running the claims-extraction skill, and flagging missing fields back to the case timeline.

Knowledge Base Ingestion

Bulk-ingest a folder of internal documents into a V7 Go hub, run an extraction skill across them, and surface entities for downstream search. Hubs and folders provide the organisational structure; properties drive what each skill extracts; and the entities endpoints expose the resulting structured rows.

Upload all PDFs from a hub folder into project 8800, run the summary-extraction skill, and list the resulting entities.

AI Agent Tool Orchestration

An AI agent uses Jentic to drive V7 Go end-to-end: search for the right operation, load the schema, and chain calls (upload, run skill, read entities). Bearer tokens stay in your Jentic One instance, and the agent only ever sees the input/output schemas.

Search Jentic for 'extract data with v7 go', load the agent_builder execute schema, run it against case 9100, and return structured results.

Key Endpoints

274 endpoints — jentic publishes the only available openapi specification for v7 go api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/api/workspaces/{workspace_id}/files/confirm

Confirm a completed file upload

POST

/api/workspaces/{workspace_id}/agent_builder/{request_id}/execute

Execute an agent builder request

POST

/api/workspaces/{workspace_id}/projects/{project_id}/entities/filter

Filter entities in a project

GET

/api/workspaces/{workspace_id}/projects/{project_id}/billing/usage

Get token usage for a project

GET

/api/workspaces/{workspace_id}/folders/tree

Read the folder tree for a workspace

POST

/api/workspaces/{workspace_id}/cases/{case_id}/confirm_tool_run

Confirm a tool run on a case

GET

/api/workspaces/{workspace_id}/integrations/all/connections

List integration connections

GET

/api/workspaces/{workspace_id}/skills/{skill_id}/settings

Read skill settings

POST

/api/workspaces/{workspace_id}/files/confirm

Confirm a completed file upload

POST

/api/workspaces/{workspace_id}/agent_builder/{request_id}/execute

Execute an agent builder request

POST

/api/workspaces/{workspace_id}/projects/{project_id}/entities/filter

Filter entities in a project

GET

/api/workspaces/{workspace_id}/projects/{project_id}/billing/usage

Get token usage for a project

GET

/api/workspaces/{workspace_id}/folders/tree

Read the folder tree for a workspace

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the V7 Go API by hand means handling both its X-API-KEY header and bearer auth and mapping its 274-endpoint workspace surface yourself. Through Jentic you install once, import the V7 Go API from the API Directory, store the credential once, and your agent calls it.

Permission scoping

V7 Go puts the workspace id in the URL path (/api/workspaces/{workspace_id}/...), so a rule can pin your agent to one workspace: it can run document AI operations there and nothing else. You choose the operations it may call, so it confirms files or executes builders only when you include those operations.

Credential isolation

Your V7 Go API key or bearer token is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'extract data with V7 Go' or 'filter project entities', and Jentic returns the matching V7 operation with its input schema so the agent calls the right endpoint without browsing 274 paths.

FAQs

Specific to using V7 Go API through Jentic.

Why is there no official OpenAPI spec for V7 Go API?

V7 Labs does not publish an OpenAPI specification for the V7 Go product. Jentic generates and maintains this spec so AI agents and developers can call V7 Go via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.

What authentication does the V7 Go API use?

V7 Go supports two schemes: an API key sent via the X-API-KEY header, and HTTP bearer tokens. Through Jentic, both credential types are stored encrypted and injected at execution time so the agent never sees the raw secret.

Can I run an agent builder execution with the V7 Go API?

Yes. POST /api/workspaces/{workspace_id}/agent_builder/{request_id}/execute runs a configured agent builder request and returns the execution result. Pair it with the case endpoints to track tool runs and queued follow-up messages.

What are the rate limits for the V7 Go API?

The OpenAPI spec does not declare numeric rate limits. V7 Labs publishes plan-tier limits in its product documentation; in practice, batch file uploads and back off on HTTP 429 responses.

How do I extract structured data from a document through Jentic?

Run a Jentic search for 'extract data with v7 go', load the schema for the file upload and skill execution endpoints, then call them in sequence. Install with pip install jentic and use the async search, load, and execute pattern.

Does the V7 Go API support MCP integrations?

Yes. The /api/workspaces/{workspace_id}/mcp-integrations endpoints let you list and configure MCP servers that V7 skills can call as tools during an agent run.

Go V7labs V7 Go API

Connect the V7 Go API to your agent

Capabilities

Start building with V7 Go API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs