AgentOS

Imagine a telecom company that gets thousands of roaming questions every day. Before AgentOS, that meant either a chatbot that could handle "check my balance" but nothing more, or a human agent for everything else. Now, an AI agent on AgentOS understands "I'm traveling to Japan next week, what do I need to set up?" It checks the customer's plan, activates roaming, sends a confirmation over WhatsApp, and follows up with a rate summary via email. If the question gets complicated, it hands off to a human agent with the full conversation context intact.

That's what AgentOS(opens in new tab) does. It's Infobip's platform for building, deploying, and running AI agents that handle real customer conversations across 15+ channels: SMS, WhatsApp, RCS, Email, Voice, Viber, live chat, and more.

One platform instead of four

AgentOS brought together what used to be four separate Infobip products: marketing automation, customer data, chatbots, and contact center, all into one system. Instead of stitching tools together, teams now design entire customer journeys in a single place: the AI agent that greets you, the data that personalises your experience, and the human agent who steps in when needed, all connected.

How people build on it

There's no single "right way" to build on AgentOS. A marketing team might use the visual drag-and-drop builder to create a campaign journey without writing a line of code. A development team might use the Python SDK with LangGraph to build a multi-step agent that checks inventory, processes returns, and updates the CRM, all in one conversation.

The platform exposes APIs and SDKs in Python, Node.js, Java, PHP, and .NET, plus OpenAPI specs and Postman collections. Agents can connect to external systems like Salesforce, HubSpot, or Shopify through pre-built integrations, or to any internal system through custom MCP connections.

Open by design

AgentOS isn't locked to one AI provider. You can plug in agents built on OpenAI, Anthropic, or your own models. Infobip handles the orchestration, routing conversations across channels, preserving context, and managing handoffs, while you choose the intelligence layer that fits your use case.

A fashion retailer, for example, might use one agent to handle order tracking over WhatsApp and a completely different agent for personalized style recommendations via the app, both running on the same platform, both with access to the same customer data.

The bigger picture

Why are we writing about this? This shows the mindset that we live inside the company, together with the AI-first approach. This is how we think as the company when trying to find solutions for clients to help them with user interactions. We design for our clients, think for them, and in the end, build for them, and that's what we are recognized for year after year.

For twenty years, Infobip connected businesses to their customers through messages. AgentOS is the next step: instead of just delivering messages, the platform now understands them, acts on them, and learns from them.

The shift isn't just technical; it changes what our engineering teams think about every day. We used to optimize for message delivery at scale. Now we also think about conversation quality, agent reasoning, and how AI and humans work together in real time. That's a fundamentally different kind of engineering challenge, and it's what makes this work exciting.

Sources & further reading

• AgentOS Product Page(opens in new tab)
• AI Agent Documentation(opens in new tab)
• Infobip launches AgentOS — Press Release(opens in new tab)
• Infobip at 20: the AI Era Is Here(opens in new tab)
• Beyond Bots: Infobip's AgentOS Unifies AI(opens in new tab)