OnDimi is an experimental platform exploring how agentic, multi-agent AI can plan, orchestrate, and execute complete customer journeys across multiple channels. It serves as a personal testbed for designing and coordinating Decisioning, Planning, Orchestration, and Specialist AI Agents that work together in real time to deliver dynamic, compliant, and personalized engagement.
Note: OnDimi is a personal experimental project and is not affiliated with any company or organization.
The Decisioning and Planning AI is a decision-driven, agentic intelligence that not only schedules customer interactions but also determines when, how, and which agent should engage the customer. It continuously refines the communication plan based on customer data, behavior patterns, compliance rules, business objectives, and journey context. The agent generates personalized, multi-day, multi-channel action plans—spanning channels, languages, and specialized AI agents—and adapts them in real time as conditions change.
OnDimi is built on a multi-agent, agentic AI architecture where multiple specialized agents work together—each with its own role, intelligence, and capabilities. Instead of a single model handling everything, the system coordinates a network of agents that collaborate, hand off tasks, and execute complex customer journeys end-to-end.
Build intelligent agents visually with a flexible, drag-and-drop builder. The AI Agent Builder lets you assemble powerful agents by connecting the core building blocks they need—data, knowledge, guardrails, tools, and MCP integrations. You can reuse existing resources or create new ones, making it easy to design agents that are consistent, capable, and tailored to their role within the multi-agent architecture.
Every AI agent in OnDimi is powered by a set of modular, configurable building blocks. These components define what the agent knows, what rules it must follow, what actions it can take, and what external systems it can access. By combining and reusing these blocks, you can design agents that are precise, safe, and deeply aligned with your business workflows.
Give each AI agent access only to the data it needs—nothing more.
Agents can reference structured fields such as customer data, business data, appointment details, demographic attributes, and use-case-specific fields.
You choose exactly which fields are available, ensuring privacy, relevance, and contextual accuracy during customer interactions.
Define the rules an agent must follow.
Guardrails can enforce:
This ensures every agent operates safely, ethically, and within your organization’s requirements.
Provide contextual knowledge that the agent can use to answer questions.
OnDimi supports two types:
Extend an agent’s capabilities with custom tools.
Each tool includes:
Connect agents to external systems through Model Context Protocol (MCP) servers.
Agents can:
MCP unlocks powerful integrations like Google Calendar, CRMs, ticketing systems, and internal services—directly from the agent.
AI agents themselves can be exposed as callable tools—allowing one agent to delegate work to another. In this pattern, a specialized agent is wrapped as a function that other agents can invoke when needed. This creates a hierarchical, team-like structure where:
An Orchestrator Agent decides when to call a specialist
This mirrors real organizational collaboration: a manager coordinating experts rather than a single agent attempting everything. By treating agents as tools, the system supports modular delegation, specialization, and scalable multi-agent workflows.
Experiementing the use of GenAI, Whisper model for speech recognition, Google TTS, and openAI LLM to enhance the conversational experience in voice calls. Watch the Video
