Connect Eventee to AI Agents: Automate Invites & Logistics

You want to connect Eventee to an AI agent so your system can autonomously manage attendee invitations, schedule changes, speaker profiles, and live event logistics. Here is exactly how to do it using Truto's /tools endpoint and SDK, bypassing the need to write and maintain complex integration code from scratch.

Giving a Large Language Model (LLM) read and write access to your event management platform requires strict constraints. You cannot afford an agent hallucinating speaker schedules or corrupting partner profiles during a live conference. If your team uses ChatGPT, check out our guide on connecting Eventee to ChatGPT, or if you are building on Anthropic's models, read our guide on connecting Eventee to Claude. For developers building custom autonomous workflows, you need a programmatic way to fetch these tools and bind them to your agent framework.

This guide breaks down exactly how to fetch AI-ready tools for Eventee, bind them natively to an LLM using frameworks like LangChain, LangGraph, or the Vercel AI SDK, and execute complex event operation workflows. For a deeper look at the architecture behind this approach, refer to our research on architecting AI agents and the SaaS integration bottleneck.

The Engineering Reality of the Eventee API

Building an AI agent is a straightforward exercise in prompting and state management. Giving that agent reliable access to external infrastructure APIs is where projects stall. If you decide to build a custom connector for Eventee, you own the entire API lifecycle.

The Eventee API introduces specific integration challenges that break standard REST assumptions. If you hardcode these interactions into your agent, you will spend your sprints writing defensive integration code instead of improving your model's reasoning.

Relational Dependency Chains

Event management data is highly relational. Standard LLMs are trained to expect flat, intuitive JSON objects. When an agent wants to create a lecture, it naturally attempts to send a payload like {"name": "Keynote", "speaker": "Jane Doe"}.

Eventee will reject this. The API requires a heavily relational structure. To create a lecture, the agent must pass valid hall_id, an array of speakers containing valid speaker IDs, and an array of tracks containing valid track IDs. The agent must first query the halls list, the speakers list, and the tracks list, parse those responses, extract the UUIDs, and construct the final payload.

Destructive Array Replacements

When updating complex objects like partner profiles, Eventee utilizes a full-replacement pattern for nested arrays. The eventee_partners_bulk_update endpoint expects the complete state of the partner's profile sections.

Sections without an ID are created. Sections with an ID are updated. Crucially, sections missing from the array are destructively deleted. If an LLM decides to only send the specific section it wants to modify and omits the rest of the existing array, it will silently wipe out the partner's remaining profile data. Your agent's tool layer must enforce strict schema boundaries to prevent this.

Handling API Rate Limits

Event management platforms experience heavy, bursty traffic - especially during the days leading up to an event. Rate limits are strictly enforced.

Truto does not artificially retry, throttle, or apply backoff on rate limit errors. When the upstream Eventee API returns an HTTP 429 Too Many Requests error, Truto passes that error directly back to the caller. However, Truto normalizes the upstream rate limit information into standardized HTTP headers (ratelimit-limit, ratelimit-remaining, ratelimit-reset) conforming to the IETF specification. Your agent framework is responsible for reading these headers and executing deterministic retry and backoff logic. We cover exactly how to implement this in the code section below.

Essential Eventee Tools for AI Agents

A unified tool layer collapses complex API requirements behind a stable schema. Your agent interacts with highly constrained Proxy APIs. Below are the highest-leverage tools available for autonomous Eventee operations.

Create a Lecture

Creates a new session in your Eventee agenda. This is the core primitive for building dynamic schedules.

Usage Notes: The agent must be instructed to provide valid hall_id, speakers, and tracks. It cannot pass raw strings for these references. You must provide the agent with tools to list halls and speakers first.

"Schedule a new lecture called 'Future of AI' for tomorrow at 10 AM. Put it in the Main Hall. The speaker is John Smith. Tag it under the 'Technology' track. Look up the IDs for the hall, speaker, and track before creating the lecture."

List All Participants

Retrieves a complete list of attendees registered for an Eventee event, including their basic info and check-in status.

Usage Notes: Returns critical operational state, including checkedAt and groupId. Useful for agents acting as digital concierges or access control monitors.

"Pull the list of all participants. Filter for anyone who registered yesterday but has a null 'checkedAt' value, and return their names and company details."

Invite Participants

Dispatches invitations to attendees. This triggers the generation of unique QR codes and access URLs for the event.

Usage Notes: Essential for autonomous ticketing workflows. The agent receives the invitation result per attendee, which it can then pass to communication tools (like email or SMS APIs) to distribute the tickets.

"Take this list of three emails: alice@example.com, bob@example.com, and charlie@example.com. Invite them to the event as participants and return the generated QR code URLs for each."

Bulk Update Partners

Replaces all sections of an Eventee partner's profile. Partners act as sponsors or exhibitors.

Usage Notes: This tool replaces the entire profile array. Prompt the agent explicitly to fetch the existing partner profile first, modify the desired section in memory, and pass the entire combined array back to this tool. Do not let the agent send partial arrays.

"Fetch the partner profile for 'Acme Corp'. They want to add a new exhibitor info section with their updated booth number (Booth 42). Keep all their existing sponsor info intact, and apply the bulk update."

Create a Speaker

Provisions a new speaker profile in the event.

Usage Notes: Requires name and phone as a baseline. The agent will receive the generated id back, which it must retain in its context window to associate the speaker with future lectures.

"We have a late addition to the speaker lineup. Create a speaker profile for Sarah Connor. Her company is Cyberdyne Systems and her position is Lead Researcher. Phone is 555-0199. Save her ID for the next step."

Bulk Delete Event

Destructively deletes every hall, lecture, track, pause, speaker, and workshop from the event in a single call.

Usage Notes: Highly dangerous in production. Useful for agents managing staging environments or tearing down test events after CI/CD test suites run. Returns an empty 204 response on success.

"The integration test suite has finished. Target the staging event and execute a bulk delete to wipe all test content (halls, lectures, speakers) so we have a clean slate for the next run."

For the complete inventory of available tools and their exact JSON schemas, review the Eventee integration page.

Workflows in Action

Exposing these tools to an LLM unlocks complex, multi-step agentic workflows that traditionally required hardcoded business logic. Here is how an agent executes real-world event operations.

Scenario 1: The Last-Minute Agenda Shuffle

Event schedules change constantly. When a speaker cancels, an agent can autonomously restructure the agenda based on natural language input.

"Sarah Connor had to cancel her keynote at 10 AM. Delete her speaker profile. Then, update the 10 AM lecture to feature John Smith instead, and change the lecture title to 'AI Safety Fundamentals'."

Execution Steps:

1. The agent calls list_all_eventee_speakers to find the ID for "Sarah Connor".
2. The agent calls list_all_eventee_lectures to find the 10 AM keynote and note its id and current parameters.
3. The agent calls list_all_eventee_speakers again to find the ID for "John Smith".
4. The agent calls update_a_eventee_lecture_by_id, passing the lecture ID, replacing the speakers array with John's ID, and setting the new title.
5. The agent calls delete_a_eventee_speaker_by_id passing Sarah's ID to clean up the directory.

Result: The schedule is updated, the old speaker is removed, and the agent returns a confirmation of the new agenda state.

Scenario 2: Autonomous VIP Ticketing

Sales teams often drop lists of VIP prospects into Slack at the last minute. An agent can process these lists and issue tickets immediately.

"We just approved three new VIPs for the event: executives from Initech, Hooli, and Pied Piper. Here are their names and emails. Add them as participants, trigger their invites, and give me a table of their names and ticket URLs so I can email them."

Execution Steps:

1. The agent parses the unstructured text to extract the names, companies, and emails.
2. The agent formats the data and calls eventee_participants_invite passing the array of users.
3. The tool returns the result envelope containing the url and qr_code for each successfully invited participant.
4. The agent formats the raw JSON response into a markdown table.

Result: The human operator receives a clean list of unique ticket URLs ready for distribution, with all backend provisioning handled instantly.

Building Multi-Step Workflows

To build these agents, you need a programmatic way to retrieve Truto's proxy APIs and bind them to your model. Truto exposes a /tools endpoint that outputs schemas specifically formatted for LLM function calling.

Fetching Tools from Truto

First, retrieve the tool definitions for your integrated Eventee account. Truto handles the OAuth token lifecycle and pagination standardization under the hood.

import { TrutoToolManager } from 'truto-langchainjs-toolset';
 
// Initialize the tool manager with your Truto API key
const truto = new TrutoToolManager({
  apiKey: process.env.TRUTO_API_KEY,
});
 
// Fetch the tools for a specific connected Eventee account
// Find your Integrated Account ID in the Truto dashboard
const accountId = "act_12345eventee";
const tools = await truto.getTools(accountId);
 
console.log(`Successfully loaded ${tools.length} tools for Eventee.`);

Handling Rate Limits Deterministically

As noted earlier, Truto does not absorb rate limit errors. When the upstream API throws a 429, Truto passes it back with standardized headers: ratelimit-limit, ratelimit-remaining, and ratelimit-reset.

Your agent execution loop must catch these errors and handle the backoff. If you rely on the LLM to "decide" what to do on a 429, it will likely hallucinate a success or spam the API. You must handle this in the code layer.

import { ChatOpenAI } from "@langchain/openai";
import { AgentExecutor, createOpenAIToolsAgent } from "langchain/agents";
import { Pull } from "langchain/hub";
import { ChatPromptTemplate } from "@langchain/core/prompts";
 
async function executeEventeeWorkflow(prompt: string) {
  const llm = new ChatOpenAI({
    modelName: "gpt-4-turbo-preview",
    temperature: 0,
  });
 
  // Bind the Eventee tools to the model
  const modelWithTools = llm.bindTools(tools);
 
  const promptTemplate = ChatPromptTemplate.fromMessages([
    ["system", "You are an autonomous event manager. Use the provided tools to interact with Eventee. Always verify IDs before making destructive changes."],
    ["human", "{input}"],
    ["placeholder", "{agent_scratchpad}"],
  ]);
 
  const agent = await createOpenAIToolsAgent({
    llm: modelWithTools,
    tools,
    prompt: promptTemplate,
  });
 
  const executor = new AgentExecutor({
    agent,
    tools,
    maxIterations: 10,
  });
 
  // Wrap execution in a retry block respecting IETF rate limit headers
  let retries = 3;
  while (retries > 0) {
    try {
      const result = await executor.invoke({ input: prompt });
      console.log("Workflow complete:", result.output);
      return;
    } catch (error: any) {
      if (error.response?.status === 429) {
        // Extract standardized Truto headers
        const resetTime = error.response.headers.get('ratelimit-reset');
        const delayMs = resetTime ? (parseInt(resetTime) * 1000) - Date.now() : 5000;
        
        console.warn(`Rate limit hit. Waiting ${delayMs}ms before retrying...`);
        await new Promise(resolve => setTimeout(resolve, Math.max(delayMs, 1000)));
        retries--;
      } else {
        console.error("Agent execution failed:", error);
        throw error;
      }
    }
  }
  throw new Error("Max retries exceeded due to rate limiting.");
}
 
await executeEventeeWorkflow("Find the lecture named 'Opening Remarks' and add a new speaker named 'Elon Musk' with phone '555-9999' to it.");

Execution Flow Architecture

The resulting architecture cleanly separates the reasoning engine from the API transport layer. The LLM simply outputs a JSON command. The framework executes it against Truto, which applies the necessary authentication and routes it to Eventee.

sequenceDiagram
    participant User as User
    participant Agent as Agent Framework (LangChain)
    participant Truto as Truto /tools Endpoint
    participant Eventee as Eventee API

    User->>Agent: "Add a speaker and update the keynote."
    activate Agent
    Agent->>Agent: LLM generates tool call<br>(create_a_eventee_speaker)
    Agent->>Truto: POST /proxy/eventee/speakers<br>Authorization: Bearer <Truto_Key>
    activate Truto
    Truto->>Eventee: POST /api/v1/speakers<br>Authorization: Bearer <Eventee_OAuth>
    Eventee-->>Truto: 201 Created (id: 9876)
    Truto-->>Agent: { "id": "9876", "name": "..." }
    deactivate Truto
    Agent->>Agent: LLM generates next tool call<br>(update_a_eventee_lecture_by_id)
    Agent->>Truto: PUT /proxy/eventee/lectures/1234
    activate Truto
    Truto->>Eventee: PUT /api/v1/lectures/1234
    Eventee-->>Truto: 200 OK
    Truto-->>Agent: { "success": true }
    deactivate Truto
    Agent-->>User: "Speaker created and lecture updated."
    deactivate Agent

If the Eventee API responds with a 429 at any point in this sequence, Truto proxies that 429 directly back to the Agent framework, ensuring the underlying rate limits are respected without silently queueing or dropping requests.

Scaling Autonomous Event Operations

Giving AI agents direct access to your event management infrastructure completely changes how you operate conferences and live events. Instead of a team of human coordinators frantically clicking through dashboards to adjust schedules, revoke badges, or issue last-minute sponsor updates, an LLM handles the execution flawlessly via natural language.

By leveraging Truto's /tools endpoint, you bypass the massive engineering overhead of maintaining Eventee API schemas, handling OAuth token refreshes, and building LLM-specific function wrappers. Your agents receive deterministically validated schemas and normalized rate limit headers out of the box.