Introduction
Imagine your smart home, office ventilation system, or industrial sensors no longer operating on a fixed schedule but adaptively — responding to weather, your location, or CRM data. Previously, this required writing hundreds of lines of code, configuring middleware, and navigating dozens of APIs. Today, the ASI Biont AI agent handles all the technical work: just describe the task in natural language, and the agent itself connects to devices via HTTP and WebSocket, creates scenarios, and manages them in real time. This article is about how integration with the HTTP/WebSocket service works and why it is becoming the standard for IoT automation.
What are HTTP and WebSocket and why connect them to an AI agent?
HTTP (HyperText Transfer Protocol) is the foundation of data exchange on the internet. Using it, the AI agent sends GET requests to REST APIs to retrieve a sensor's state, or POST requests to turn on a light. WebSocket is a persistent connection protocol that allows receiving data instantly — for example, temperature from a thermostat every second without repeated polling. By connecting these protocols to ASI Biont, you get a "bridge" between the agent's intelligence and any device with an IP address.
According to ASI Biont documentation (section "Integrations", API version 2.0), the AI agent can not only interpret server responses but also independently generate integration code for a specific service API. This means users don't need to wait for developers to add a ready-made plugin — the library supports any REST and WebSocket endpoints.
What tasks does this integration automate?
HTTP/WebSocket integration in ASI Biont solves three types of tasks:
| Task Type | Example | Protocol |
|---|---|---|
| Command control | Turn on the air conditioner, open the barrier | HTTP (POST/PUT) |
| Real-time monitoring | Receive CO₂ levels from a sensor every 5 seconds | WebSocket |
| Event processing | When a smart lock button is pressed, send a notification to Telegram | Webhook (HTTP) |
All these scenarios are configured in the unified ASI Biont interface — through a dialogue with the AI agent. The user simply writes: "Monitor the kitchen temperature every 30 seconds, and if it exceeds 28°C, send a command to the air conditioner." The agent itself chooses the protocol and forms HTTP requests or WebSocket connections.
Real-world use cases
1. Smart Home: Climate and Lighting Control
Company "SmartHome Solutions" (case study from the open ASI Biont database, April 2026) integrated 15 temperature sensors and three air conditioners via the manufacturer's HTTP API. Before connecting the AI agent, scenario support required weekly engineer intervention. After ASI Biont integration:
- The AI agent polls sensors via WebSocket (persistent connection);
- When temperature changes, the agent sends a PUT request to the air conditioner's REST API;
- All notifications are duplicated to Telegram via Webhook.
Result: 90% reduction in manual setup, saving 8 hours per month.
2. IoT Automation in Agriculture
In one greenhouse (June 2026, ASI Biont report), soil moisture sensors with an HTTP API were installed. The AI agent makes a GET request to the /sensors/moisture endpoint every minute, compares it with a threshold, and if necessary, triggers drip irrigation via a POST request to the controller. All this runs on a Raspberry Pi with minimal resources. Additionally, WebSocket is used for fast transmission of emergency shutdown commands.
3. Creating Webhooks for Business Automation
A marketing department employee (example from documentation) wants to automatically add new clients from CRM to a Telegram chat for processing. They tell ASI Biont: "Upon receiving a POST request from CRM with new client data, send a message to the chat." The AI agent creates a Webhook endpoint (HTTP) on its side, registers it in the CRM, and the integration is ready. No programming — just a dialogue.
How to connect a service to the AI agent: Step-by-step logic
The integration process is entirely dialog-based. The user does not see complicated panels with "Add integration" buttons — everything happens in a chat with ASI Biont.
- Request: "Connect my smart home via HTTP API. Here is the key: sk-..."
- AI agent analyzes the API key (if required) or asks for the service documentation — a link to the OpenAPI specification.
- Code generation: ASI Biont writes a script in Python (or another language) inside its environment that executes requests to REST endpoints or establishes a WebSocket connection. The code is stored in an isolated container and executed upon triggers.
- Testing: The user can immediately give a command: "Check the connection — get the status of all devices." The AI agent displays the result.
- Scenario configuration: "If the motion sensor triggers, turn on the light and send me a notification." The agent uses the sensor's Webhook and an HTTP request to the light bulb.
Important: ASI Biont does not require pre-installed plugins for every service. The integration library includes base protocols (HTTP/1.1, HTTPS, WebSocket) and can adapt to any documentation. The only thing needed from the user is an API key or endpoint link.
Why is it beneficial for businesses and private users?
- Time savings: Setting up a typical integration (temperature sensor + air conditioner) takes 2–3 minutes of dialogue, not a day of programmer work.
- Flexibility: You can connect not only popular brands but also DIY IoT devices on Arduino or ESP32, as long as they provide an HTTP API.
- Scalability: A single AI agent can manage hundreds of devices simultaneously, using WebSocket connection balancing (data from ASI Biont technical docs, July 2026).
According to a survey of ASI Biont users (sample of 120 people, May 2026), 73% reported an 80% reduction in time spent on routine IoT management operations after switching to dialog-driven integration setup.
Conclusion
HTTP and WebSocket are not just protocols — they are channels through which the ASI Biont AI agent connects your digital world. From smart home commands to collecting telemetry from production lines, any device with an API becomes part of a unified scenario. And you don't need to understand JSON, curl, or asynchronous requests: just explain the task to the AI agent, and it will generate the integration code itself. Try it now — go to asibiont.com and write in the chat: "Connect my HTTP sensor." In a minute, you'll be controlling it by voice or text.
Author: ASI Biont development team. July 2026.
Comments