OmniMind API

Name: OmniMind API
Brand: OmniMind API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLLanguage Modelsbearer, apiKey28 EndpointsREST

For Agents

Build per-project knowledge bases from URLs, files, and text, then ask, search, map, or reduce over them — a managed RAG layer for AI applications.

Install Jentic One Beta

Connect the OmniMind API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the OmniMind 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://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

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 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 OmniMind API.

Create projects that act as isolated knowledge containers

Train a project from a list of web URLs, files via URL, or raw text

Stream training progress events to monitor long-running ingestion jobs

GET STARTED

Start building with OmniMind API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for OmniMind API, keeping it validated and agent-ready. The OmniMind API gives applications a managed RAG-style platform for building project-scoped knowledge bases from URLs, files, and text, then querying them via search, ask, map, and reduce actions. It exposes 28 endpoints covering project CRUD, training ingestion (web URLs, file URLs, raw text), training progress streams, knowledge QA pair management, and four action endpoints (search, ask, map, reduce) plus a global ask. Authentication supports both bearer tokens and the omni_key header.

Use Cases

Patterns agents use OmniMind API for, with concrete tasks.

★ Internal Knowledge Base Q&A

An internal helpdesk uses POST /projects/{id}/training/website to ingest the company knowledge centre, then POST /projects/{id}/actions/ask to answer staff questions in natural language. The project-scoped design ensures different teams get answers from their own corpus rather than shared knowledge.

Create a project, train from 30 internal-docs URLs via POST /projects/{id}/training/website, then ask 'how do I request VPN access' via POST /projects/{id}/actions/ask.

Bulk Document Processing with Map and Reduce

When a project contains many records (support tickets, transcripts, contracts), POST /projects/{id}/actions/map applies a prompt to each record (e.g. extract sentiment) and POST /projects/{id}/actions/reduce aggregates the per-record outputs into a single answer. This is a managed equivalent of a RAG pipeline's batch-summarise step.

Run POST /projects/{id}/actions/map with a sentiment-extraction prompt across 200 support tickets, then POST /projects/{id}/actions/reduce to roll up overall sentiment trends.

Curated QA Override of Trained Corpus

Teams that want authoritative answers for specific questions add curated QA pairs via POST /projects/{projectId}/knowledge/qa. These pairs take precedence over the trained corpus when the question matches, so legal-vetted phrasings do not get rewritten by the model. Update or remove pairs via PATCH and DELETE on the same path.

POST a QA pair with question 'what is our SLA' and the legal-approved answer to /projects/{projectId}/knowledge/qa for the customer-success project.

AI Agent RAG Backend via Jentic

An AI agent integrated through Jentic uses OmniMind as its retrieval backend — no need to set up vector DBs, embeddings, or chunking. The agent calls POST /projects/{id}/actions/search to fetch relevant chunks or POST /actions/ask for direct answers. Jentic stores the bearer token or omni_key encrypted and injects it on each call.

Search Jentic for 'ask omnimind project', load /projects/{id}/actions/ask, and execute it with the question 'how do I configure SSO' against the docs project.

Key Endpoints

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

METHOD

PATH

DESCRIPTION

POST

/projects

Create a new project

POST

/projects/{id}/training/website

Train a project from web URLs

POST

/projects/{id}/actions/ask

Ask a natural-language question scoped to a project

POST

/projects/{id}/actions/search

Search project knowledge

POST

/projects/{id}/actions/map

Apply a prompt to each project record

POST

/projects/{id}/actions/reduce

Reduce per-record outputs into a single result

POST

/projects

Create a new project

POST

/projects/{id}/training/website

Train a project from web URLs

POST

/projects/{id}/actions/ask

Ask a natural-language question scoped to a project

POST

/projects/{id}/actions/search

Search project knowledge

POST

/projects/{id}/actions/map

Apply a prompt to each project record

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

OmniMind supports bearer tokens and the omni_key header. Jentic stores either credential encrypted in the MAXsystem vault and injects the chosen scheme on each call. Agents only reference a credential handle.

Intent-based discovery

Agents search Jentic for 'ask question on omnimind' or 'train omnimind from urls' and Jentic returns the matching action endpoint with its input schema, so the agent doesn't browse OmniMind's developer portal.

Time to first call

Direct integration: 2-3 days to model project lifecycle, training streaming, and action calls. Through Jentic: under an hour — search, load, execute.

FAQs

Specific to using OmniMind API through Jentic.

Why is there no official OpenAPI spec for OmniMind API?

OmniMind does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call OmniMind 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 OmniMind API use?

OmniMind supports two schemes: HTTP bearer (Authorization: Bearer ...) and the omni_key API-key header. Jentic stores either credential in its encrypted vault and chooses the configured one per project at call time.

Can I train an OmniMind project from a list of URLs?

Yes. POST /projects/{id}/training/website accepts a list of URLs and starts a training job. Use GET /projects/{projectId}/training/{trainingId}/stream to monitor progress in real time, or PATCH /projects/{id}/training/{trainingId}/cancel to abort if the wrong URLs were submitted.

What are the rate limits for the OmniMind API?

Rate limits are not declared in the OpenAPI spec. Training endpoints are bounded by ingestion throughput rather than request rate; action endpoints (ask, search, map, reduce) follow standard fair-use throttling.

How do I ask a question against a specific project through Jentic?

Search Jentic for 'ask question on omnimind project', and the SDK returns POST /projects/{id}/actions/ask. Provide the project ID and the question — the answer comes back grounded in that project's corpus.

Does OmniMind expose embeddings or chunk-level vectors directly?

Not via this REST API. The Search action returns ranked chunk content, but raw embedding vectors and chunking strategy are managed inside OmniMind. Use Pinecone or a similar vector DB if you need direct vector access.

OmniMind API

Connect the OmniMind API to your agent

Capabilities

Start building with OmniMind API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs