Omnichannel AI agents: When the channel changes, the context remains the same
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The omnichannel experience is revealed when switching channels
Many customer service solutions today support multiple contact channels. Customers can chat, call or use messaging services. However, this variety of channels does not in itself create a seamless omnichannel experience if customers have to start from scratch every time they switch channels. The benefits of a holistic omnichannel architecture become apparent the moment a customer wishes to switch channels.
Sometimes, typing is the easiest way to interact. You’re sitting on the S-Bahn. Then you reach your stop. You get off. Put your headphones on and, with a single click, continue your conversation with the voice AI agent or be transferred to a contact centre agent.
It goes without saying that customers do not want to have to start all over again.
The context of the conversation so far, information already recorded and the current status of the process must also be available in the next channel. That’s when multichannel truly becomes omnichannel.
What does a handover mean for an omnichannel AI agent?
A handover refers to the transfer of an ongoing customer interaction to another channel, another AI agent or a human agent.
In the CreaLog omnichannel scenario, for example, a customer can start a conversation via web chat and switch directly from that interaction to a voice conversation via WebRTC.
Possible handovers include:
• from a chat AI agent to a voice AI agent,
• from chat to a contact centre agent,
• from an automated conversation to a human agent,
• from a voice conversation back to chat.
A change of channel does not necessarily mean that the interaction in the previous channel has failed. A good omnichannel service gives customers the freedom to adapt their communication channel to their current situation and receive the right help for their enquiry.
Technically channel-agnostic, channel-specific in dialogue
A unified omnichannel architecture does not mean that every channel should be designed in the same way.
Voice, chat and messaging utilise different interaction patterns.
CreaLog combines these technical and design perspectives. In addition to the platform architecture, the solution approach also encompasses conversational user interface design, persona development, sound design and the design of backend processes.
Voice is not simply a chat read aloud
Speech is fleeting and sequential. Information must be structured concisely, follow-up questions must be phrased unambiguously, and interruptions (barge-ins) must be taken into account.
Chat relies on visibility
In chat, information remains visible. Users can scroll back, compare options and be guided via buttons, links or structured content.
Messaging is often asynchronous
In messaging, there may be minutes or hours between two messages. The design must therefore take into account how a dialogue can be meaningfully continued after an interruption.
Our architectural cornerstones: Context is not tied to the channel
It is precisely this point that distinguishes seamless omnichannel architecture from a collection of individual bots and isolated communication channels. Data access and service logic are not set up separately for chat, voice or a specific language model. All communication channels access a shared process and architectural foundation.
This means, for example, that access to CRM/ERP data, contract information, order status or other back-end systems does not depend on whether a chat, voice or other AI agent is interacting with the customer at the front end.
Channel-independent back-end access
Developing AI agents on a channel-by-channel basis quickly creates new silos. As a result, with every new channel and every new AI technology, not only does functionality increase, but so does the complexity of integration.
At CreaLog, the Service Delivery Platform acts as this common layer. It connects communication channels, AI components and enterprise systems. This enables different communication channels to access the same services and processes. This is what makes the difference when using AI agents that not only generate responses but also securely access enterprise data, execute defined processes and are thus able to resolve cases independently.
With its MCP architecture, CreaLog separates AI-based conversation management from controlled backend execution. The AI agent understands the enquiry and steers the dialogue. The platform defines which data, tools and processes may be accessed.
AI models may change, but processes must remain stable
AI technologies, too, are changing rapidly. In the long term, companies will not necessarily continue to use the same LLM or the same provider.
Business processes should therefore not be rigidly tied to a specific model.
New channels, new AI solutions or new AI initiatives from different departments need not create new back-end silos. Existing services and integrations can be reused. Processes can be designed to be consistent across multiple touchpoints.
Omnichannel requires a shared architecture
The future of customer service will not consist of a single channel or many parallel specialist bots.
Channels, interfaces and AI technologies will continue to evolve. A viable omnichannel architecture must therefore establish a stable foundation beneath them: for context, data access, processes, governance and integration.
Then a customer can start in a chat, switch to a voicebot and, if necessary, continue with a member of staff. That is omnichannel, rather than multichannel.
Omnichannel means consistently continuing the same customer journey across differently designed channels.
Find out more about omnichannel agents and the CreaLog AI architecture
