Introduction
Okibi: Natural Language Platform for AI Agent Development
Okibi is a natural language platform designed to facilitate the creation of AI agents. The primary purpose of Okibi is to simplify the process of building and deploying AI agents, addressing the complexities often associated with traditional AI development.
Key Features and Capabilities:
- Visual Agent Builder: Okibi utilizes a visual interface allowing users to construct AI agents without extensive coding. The platform provides a drag-and-drop environment for defining agent behavior.
- Natural Language Understanding (NLU): The core of the platform leverages NLU to interpret user input, identifying intents and entities within conversational exchanges.
- Response Generation: Okibi enables the creation of dynamic responses based on the interpreted input, offering flexibility in agent behavior.
- Flow Management: Users can define the flow of conversations, guiding the agent through various stages of interaction.
- Pre-built Templates: The platform offers pre-built agent templates for common use cases, accelerating the development process.
- Intent & Entity Definition: Users can define specific intents (what the agent is trying to achieve) and entities (relevant information within the conversation).
Target Audience and Use Cases:
Okibi is designed for a broad range of users, including:
- Business professionals seeking to automate customer interactions.
- Developers building conversational applications.
- Non-technical users wanting to create simple AI-powered solutions.
Potential use cases include:
- Customer support chatbots
- Lead qualification
- Internal knowledge base access
- Task automation
Technical Approach:
Okibi’s methodology centers around a visual, model-driven approach to AI agent development. The platform abstracts away low-level coding details, offering a more accessible entry point for users with varying levels of technical expertise. It employs a proprietary engine for NLU processing and response generation. The platform focuses on providing a streamlined experience for defining conversational logic and connecting it to underlying models.
