RubiCore is a unified, enterprise-grade Agentic AI platform designed to empower organizations to build, deploy, manage, and govern an intelligent "AI workforce."
Specialized & Autonomous Agents
Create specialized, autonomous, and collaborative agents capable of perceiving multi-modal information, reasoning, planning, acting, and continuously learning. These agents automate complex tasks and augment human capabilities, all under your strict governance and with full explainability.
Comprehensive Platform Pillars
Unlike single-purpose chatbots, RubiCore agents execute sophisticated multi-step processes and securely interact with your enterprise systems. The platform includes:
- Low-Code Studio & Pro-Code SDKs: For intuitive agent creation and customization.
- Intelligent Orchestration Engine: To manage complex multi-agent and human-AI workflows.
- Secure & Dynamic Integration Hub: To seamlessly connect with your existing tech stack.
- Advanced Analytics & Continuous Learning: For monitoring outcomes and driving improvements.
- Robust Human-AI Collaboration Interfaces: Fostering seamless teamwork.
Adaptive Multi-Agent Collaboration
Our innovative Adaptive Multi-Agent Collaboration Framework enables sophisticated agent teams that distribute work by specialization, share context dynamically, learn collectively, and achieve outcomes beyond the reach of individual agents.
High-level conceptual diagram of the RubiCore platform and its interconnected components.
Core Platform Capabilities
Discover the powerful features that make RubiCore the leading Agentic AI platform.
- Visual workflow editor for agent logic
- Prompt engineering suite (basic capabilities available, advanced suite)
- Advanced reasoning designer (chain-of-thought, tree-of-thought, ReAct, self-critique)
- Agentic skill builder for reusable capabilities
- Template library for common agent types
- Versioning and integrated debugging tools
- Sandboxed simulation environment for pre-deployment testing
- Full Python SDK and APIs for pro-code development and extensibility
Built for Enterprise Scale & Trust
Core Architectural Principles
- Backend: Python (FastAPI) for high-performance, async APIs.
- Design: Modular, event-driven microservices.
- AI Core: Leverages LangChain & cutting-edge agentic frameworks.
- Memory: Multi-layered (Vector DBs, Knowledge Graphs, PostgreSQL, Redis).
- Frontend: Next.js/TypeScript for responsive UIs.
- Deployment: Docker & Kubernetes for portability (On-prem, Cloud, Hybrid).
Key innovations include Hierarchical Agent Memory Systems, Resource-Aware Execution, self-correction in tool use, and advanced inter-agent communication protocols, ensuring a powerful, extensible, and maintainable platform.
Integrate OpenAI, Anthropic, Google, Cohere, or open-source LLMs (Llama, Mixtral, etc.). Deploy your own custom or fine-tuned models securely on-premise or in your private cloud. RubiCore's model integration is secure, flexible, and governed, allowing you to choose the best model (or combination of models) for each task.
Easily add new tools/skills for agents (web browsers, RPA bots, database connectors, custom enterprise APIs). Agents intelligently decide when and how to use these tools, with capabilities for self-correction if a tool fails or returns unexpected results. New Model Context Protocol (MCP) Support and automated tool discovery from OpenAPI specs/other sources enable dynamic runtime adaptation. Developers can use the SDK to create and register custom tools.
Robust sandboxing, rate limiting, and permissioning for agent actions. Fallback flows and configurable confidence thresholds for AI outputs. Integrated evaluation frameworks (e.g., for bias, robustness, accuracy) and XAI tools for testing and validating agent behavior before and during production. New Confidence Calibration System ensures agents accurately assess their knowledge limitations and appropriately escalate or seek human input. Proactive monitoring for anomalous agent behavior.
Our state-of-the-art contextual understanding and retrieval systems provide agents with unmatched precision and intelligence. This multi-layered architecture includes: Short-Term Working Memory, Long-Term Episodic & Semantic Memory, Structured Knowledge Memory, Procedural Memory, Consensus Memory, Agentic Retrieval Augmented Generation, Universal File Type Processing, and Agent Context Awareness.
Comprehensive Python SDK, REST/GraphQL APIs, CLI tools, and detailed documentation empower developers to build custom agents, tools, workflows, and integrations. Access to simulation environments for testing and a community hub for collaboration and sharing best practices.
Platform Workflow Visualized
Illustrative diagram of RubiCore's interconnected components and data flow.
RubiCore leverages Model Context Protocol (MCP) for dynamic tool discovery and real-time context sharing. This enables AI agents to adaptively use tools, APIs, and data sources, fostering a composable AI ecosystem and reducing integration overhead. RubiCore acts as both an MCP client and server, allowing seamless interaction with other MCP-compliant systems and exposing its capabilities securely.
RubiCore combines state-of-the-art AI capabilities with enterprise rigor and a commitment to responsible innovation. Whether you're looking to augment human expertise, streamline complex operations, or drive new forms of value, our platform adapts to your needs. Talk to our AI strategists about your goals, or dive into our developer resources to start building. Our team will help design a solution that delivers quick wins and long-term strategic advantage.