Ongkanon is an AI platform designed to be your personal companion, capable of learning and adapting to your preferences. Whether you need someone to chat with or a partner for various activities, Ongkanon is always ready. The platform leverages advanced language models to offer coherent and contextual dialogues. Additionally, it supports multi-platform integration, enabling seamless interaction across digital spaces. From social media to personalized learning modules, Ongkanon provides a versatile solution for conversational needs.

Project Alice is an advanced AI agent focused on natural language processing, allowing users to have interactive dialogues. It understands context, making conversations feel more intuitive while assisting with task management, information searches, and personalized recommendations. Its capabilities include managing schedules, providing reminders, and offering advice based on user inquiries, therefore acting as a virtual assistant tailored to individual needs.

The Azure AI Travel Agents sample is an end-to-end reference implementation of a conversational agent that helps users plan trips by generating personalized travel itineraries, sourcing flight and hotel options, and answering travel-related questions. Built on the Azure AI Agent framework, it integrates OpenAI’s GPT models for natural language understanding and generation, uses Azure Functions for hosting skills such as weather lookup, and connects to external APIs for real-time booking information. Developers can run the sample locally or deploy it to Azure, extend existing skills or add new ones for currency conversion, local attraction recommendations, or travel alerts. This sample highlights how to orchestrate multiple AI-powered skills and manage context state across turns, enabling a robust, scalable travel assistant solution.

Dialogflow CX Chatbot is an AI-driven conversational agent built on Google's Dialogflow CX framework. It processes natural language inputs, identifies user intents, and extracts entities to maintain context-aware dialogues across multi-turn interactions. With features like slot filling, conditional flows, and webhook integrations, it can dynamically fetch external data and trigger backend services during conversations. The chatbot supports custom event handling, fallback strategies for unrecognized queries, and multilingual setups, providing consistent responses. Developers can design visual state machines in the Dialogflow CX console, mapping conversation paths and testing interactions in real time. Easily deployed via webhooks or client SDKs, this chatbot integrates with websites, messaging platforms, and voice channels to streamline customer service, automate FAQs, and drive user engagement.

Layra is designed to simplify developing LLM-powered agents by providing a modular architecture that integrates with various tools and memory stores. It features a planner that breaks down tasks into subgoals, a memory module for storing conversation and context, and a plugin system to connect external APIs or custom functions. Layra also supports orchestrating multiple agent instances to collaborate on complex workflows, enabling parallel execution and task delegation. With clear abstractions for tools, memory, and policy definitions, developers can rapidly prototype and deploy intelligent agents for customer support, data analysis, RAG, and more. It is framework-agnostic toward modeling backends, supporting OpenAI, Hugging Face, and local LLMs.