Alan AI basics¶
Before you start building a conversational experience with Alan AI, it is important to see the big picture. This section provides a high-level overview of Alan AI’s fundamentals, outlines available tools, components and how they work together.
The Intelligent App Platform¶
Alan AI is the complete Intelligent App Platform for building, deploying, and managing AI‑driven interfaces in just days. AI‑driven interfaces built with Alan AI can interact with users via voice or text in natural language, taking actions within any app to boost productivity and delight users.
The Alan AI Platform provides a comprehensive AI stack for building AI‑driven interfaces, including:
Alan AI Studio: web-based IDE featuring a toolkit for dialog design, testing, management and analytics
Alan AI Cloud: AI backend including natural language understanding and natural language generation, speech recognition, speech-to-text and text-to-speech conversion modules
Alan AI SDK: toolset for building and deploying conversational experiences across multiple platforms, OSes and devices
Alan AI takes care of all the heavy lifting, eliminating the need to configure separate speech components, set up the infrastructure for voice and text command processing and train speech recognition software. All deployment, maintenance and data processing tasks are managed by Alan AI, allowing businesses to focus on their core objectives.
To create AI‑driven interfaces with the Alan AI Platform, you need to:
Voice and text Agentic Interfaces¶
The Alan AI Platform enables the rapid development and deployment of voice and text Agentic Interfaces.
Alan AI Agentic Interfaces are AI-powered virtual agents that employ artificial intelligence and natural language processing to handle conversations with users and fulfill their requests. They can perform a variety of tasks: provide information, collect data, navigate in the app, complete app-specific activities and so on, all through voice- or text-based interactions.
Alan AI Agentic Interfaces are in-app agents. They are embedded into the app and designed to provide guidance and support within the context of this particular app, software or platform. Due to their in-app nature, Alan AI Agentic Interfaces extend the app functionality with conversational capabilities, making it more user-friendly and intuitive.
You can design the following types of Agentic Interfaces with Alan AI:
Voice Agentic Interfaces: AI-powered agents that understand users’ voice requests, respond to them by voice and takes actions in the app
Voice and text Agentic Interface: AI-powered chatbots or agents that leverage the Agentic Interface to handle conversations, provide information and take actions through text- or voice-based messaging
Multimodal conversational design¶
Human interaction is a complex process that goes beyond speech and text. To convey information and meaning, we use a wide range of non-verbal cues and signals.
Alan AI employs a multimodal approach to enable organizations to create conversational experiences that closely resemble human communication. It allows combining several modalities: voice, text and visuals, for a more natural and intuitive user experience.
When performing users’ requests, Agentic Interfaces can leverage the app’s GUI to provide better context and visual support for users. For example, if the user wants to know about a product, the Agentic Interface can navigate to the product page for the user to lean on. Or, it can display the cart during the checkout process. Blending voice and text with the app’s visuals helps increase accessibility and improve the reliability of performed actions and requested information.
Dialog scripts¶
To build an Agentic Interface, you must write a dialog script in Alan AI Studio. The dialog script describes the anticipated conversation between users and the Agentic Interface, including all topics, questions and phrases that users may ask or say, as well as the replies and actions that the Agentic Interface must take in response.
Dialog scripts are written in JavaScript, which provides unlimited flexibility for creating customized conversation flows.
To streamline dialog design, it can be helpful to map out all potential conversation paths and prototype alternative routes that users may take beforehand. With a clear “navigation flow” of the conversation, creating a dialog script becomes much more straightforward.
Dialog models¶
Alan AI offers two approaches to dialog design: intentless. You can use either approach independently or combine them.
Intentless dialogs¶
The intentless dialog model does not require prior knowledge of the user’s intent — the goal or purpose behind the user’s message. It employs the capabilities of Large Language Models (LLMs) and Application-level AI to understand the user’s goal and respond appropriately.
The intentless dialog approach significantly accelerates dialog development. The script developer does not need to think up all possible utterances and phrases that users may say to express their need and purpose. Rather, the developer needs to provide content for the Agentic Interface as a list of plain-text strings or URL-based data in the dialog script.
At the dialog model built time, Alan AI ingests the content from the specified data sources to produce the app- and business-specific AI model. When the user asks a question or gives a command, Alan AI analyzes the user’s input, derives meaning from it and generates an appropriate response based on the context of the conversation.
The intentless dialog model is designed to handle undirected, open-ended conversations. It can be advantageous when the user’s goal is unclear or when the dialog is free flowing. It enables users to freely express their requests without being constrained by predefined intents and answers.
To build a dialog script using the intentless dialog approach, you can use the Q&A service.
Dialog tools¶
The Alan AI Platform offers a set of tools and functions for dialog design.
Q&A service¶
The Q&A service enables you to develop dialog scripts using the intentless approach. With it, you can instantly build an Agentic Interface that responds to users’ questions in the natural language without requiring to specify their intent first.
To use the Q&A service, the script developer needs to provide a collection of texts in the corpus() function in the dialog script. These can be any types of materials: product manuals, guidelines, FAQ pages, articles, policies and so on, provided as plain-text strings or URL-based data. The Q&A service ingests the text input and crawls the specified URLs to obtain the content and build an app-specific AI model for the Agentic Interface, which is then used in dialogs with users.
Built-in JavaScript libraries¶
The script developer can utilize the following JavaScript libraries when developing dialog scripts:
axios and request to make API calls from the dialog script
moment-timezone and luxon to work with time
lodash to work with arrays, strings, objects and so on
Alan AI SDK¶
To bring the voice and text conversational experience to the app, you need to integrate the Agentic Interface to the client app. Upon integration, the app receives a draggable button on top of its UI that allows users to interact with the Agentic Interface. The Agentic Interface button is located in the bottom left corner by default and can be moved around as needed.
Alan AI integrates with client apps through Alan’s AI SDKs. To learn about integration details, check out:
The Integrations view in Alan AI Studio
Alan AI SDK documentation
Client API methods¶
To let businesses design customized and personalized conversational experiences, the Alan AI SDK exposes a set of client API methods. The client API methods can be used to implement any business logic in the client app. Through client API methods, the client can interact with Alan AI and initiate conversational activities in the app.