Install Jentic One Beta

Connect the Conduit API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Conduit 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%2Fconduit.ai%2Fconduit" | 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%2Fconduit.ai%2Fconduit" | 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 Conduit API.

Run and simulate AI chat agents against a conversation and poll their runs

Resolve, close, and reopen support tickets and post messages to them

Send a proactive message to a contact and read their tickets, calls, and appointments

Search the knowledge base and create or update knowledge nodes

Read automation-rate and resolution-rate insights for the workspace

GET STARTED

Start building with Conduit API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Conduit API for, with concrete tasks.

★ Automated Ticket Resolution

A support agent reads an open ticket, searches the Conduit knowledge base for the relevant answer, posts a reply, and resolves the ticket when the issue is handled. Conduit exposes the ticket's message history and resolve, close, and reopen actions, so the agent can work a ticket end to end and hand off only the cases that need a human.

Search the knowledge base with POST /v1/kb/search, post the answer with POST /v1/tickets/{id}/messages, then call POST /v1/tickets/{id}/resolve

Proactive Contact Outreach

An agent identifies a contact that needs follow-up, reads their recent tickets and conversations for context, and sends a proactive message from the workspace. Conduit links contacts to their tickets, calls, reservations, and appointments, so the outreach is grounded in the full history rather than a cold message.

Read the contact with GET /v1/contacts/{id}, then send a follow-up with POST /v1/contacts/{id}/messages

Support Performance Monitoring

An operations agent polls Conduit for the workspace automation and resolution rates to track how much support load the AI agents are carrying. The insights endpoints return the metrics as structured JSON the agent can chart or alert on, without pulling the full conversation log.

Call GET /v1/insights/automation_rate and GET /v1/insights/resolution_rate to report current support automation

AI Agent Integration via Jentic

An AI agent reaches Conduit through Jentic without handling the bearer token itself. It searches by intent, receives the matching operation and its input schema, and executes the call with the credential injected at run time. This lets a builder wire an external agent into Conduit's ticketing and knowledge-base operations without managing the token in code.

Search Jentic for 'resolve a support ticket', load the POST /v1/tickets/{id}/resolve schema, and execute it with Jentic-managed credentials

Key Endpoints

150 endpoints — the conduit api runs ai chat agents that handle customer conversations across tickets, contacts, and knowledge bases.

METHOD

PATH

DESCRIPTION

POST

/v1/agents/{id}/run

Run a V2 chat agent

GET

/v1/tickets

List support tickets

POST

/v1/tickets/{id}/messages

Send a message to a ticket

POST

/v1/tickets/{id}/resolve

Resolve a ticket

POST

/v1/kb/search

Search the knowledge base

POST

/v1/contacts/{id}/messages

Send a proactive message to a contact

GET

/v1/insights/automation_rate

Get the workspace automation rate

POST

/v1/agents/{id}/run

Run a V2 chat agent

GET

/v1/tickets

List support tickets

POST

/v1/tickets/{id}/messages

Send a message to a ticket

POST

/v1/tickets/{id}/resolve

Resolve a ticket

POST

/v1/kb/search

Search the knowledge base

POST

/v1/contacts/{id}/messages

Send a proactive message to a contact

GET

/v1/insights/automation_rate

Get the workspace automation rate

Why Jentic?

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

Setup

Wiring Conduit by hand means managing its bearer token, scoping write access correctly, and threading the token through every ticket, conversation, and knowledge-base call. Through Jentic you install once, import Conduit from the API Directory, store the token once, and your agent calls it.

Permission scoping

Conduit puts the ticket id in the URL path (/v1/tickets/{id}/...), so a rule can pin your agent to the ticket operations and leave agent creation, workspace settings, and portal templates out of reach. You choose which operations it may call, so destructive ones like knowledge-node deletion are not included unless you add them.

Credential isolation

Your Conduit 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 'resolve a support ticket' or 'search the knowledge base', and Jentic returns the matching Conduit operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Conduit API through Jentic.

What authentication does the Conduit API use?

The Conduit API authenticates with a bearer token in the Authorization header, per its OpenAPI spec, where read and write endpoints require a token with write access. Through Jentic the token is stored encrypted by your own Jentic One instance and injected at execution time, so it never reaches the agent.

Can I resolve support tickets with the Conduit API?

Yes. A ticket exposes its message history and resolve, close, and reopen actions, so an agent can post a reply and then resolve the ticket in one flow. Ticket notes can also be created and updated for internal context that customers do not see.

What are the rate limits for the Conduit API?

The OpenAPI spec does not publish specific rate-limit numbers; check https://docs.conduit.ai for the current limits on your plan. The billing usage endpoint reports your workspace consumption so an agent can gauge how much headroom it has before a batch of runs.

Is there a Conduit MCP server?

You don't need an MCP server to give your agent Conduit. Jentic connects it directly from the API Directory: import it, store your credential once, and your agent calls the ticketing, conversation, and knowledge-base operations. Nothing extra is loaded into the agent's context until an operation is actually invoked.

Can I limit what my agent is allowed to do with the Conduit API?

Yes. Conduit puts the ticket id in the URL path, so write a rule that allows only the ticket message and resolve operations under /v1/tickets, and the agent can work tickets while leaving agent creation and workspace settings untouched. Every call runs through your own Jentic One instance and is logged for you to review.

How do I resolve a ticket with the Conduit API through Jentic?

Search Jentic for 'resolve a support ticket', and it returns the Conduit resolve operation with its input schema. Load the schema and execute POST /v1/tickets/{id}/resolve with the credential injected at run time. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Conduit API

AI ReadinessAI-Aware (B-)60/100

See full scorecard

Official vendor OpenAPI document · agent-readyCRMCustomer Supportbearer150 EndpointsREST

For Agents

Run AI support agents over customer conversations, manage tickets and contacts, search the knowledge base, and read automation and resolution metrics. Authenticated with a bearer token.

Use for: Run a chat agent to answer an open customer conversation, Resolve a support ticket and post a closing message, Search the knowledge base for an answer to a customer question, Send a proactive message to a contact

Not supported: Does not handle payment processing, outbound marketing campaigns, or phone-network provisioning. Use for AI-assisted customer-support conversations, tickets, and contacts only.

The Conduit API runs AI chat agents that handle customer conversations across tickets, contacts, and knowledge bases. It exposes conversations and their messages, helpdesk and support tickets with resolve, close, and reopen actions, contact records with proactive messaging, and a searchable knowledge base of nodes. Agents can be created, run, and simulated, and the API reports automation and resolution rates so a team can measure how much support work the agents absorb.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A-Signals: 4

91%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: BSignals: 4

Example Density

How richly the API is illustrated with examples.

98%

Example Validity

Percentage of examples that conform to their schemas.

52%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: DSignals: 4

23%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

57%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: BSignals: 1

67%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: B-Signals: 1

60%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A-Signals: 1

78%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Conduit API to your agent

Capabilities

Start building with Conduit API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Conduit API

Jentic AI Readiness Score

Conduit API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness