10. Conclusion

As we approach an environment where multi-model, multi-agent collaboration becomes mainstream, aevatar.ai as a pioneer of the next-gen multi-agent AI framework, provides a cross-platform, cross-language model, low-barrier and highly extensible solution.

By fully utilising the Orleans Actor model, event sourcing, and cloud-native architecture, it achieves the following key values:

• Comprehensive Multi-Agent Collaboration: Breaking through the limitations of single model and closed ecosystems, enabling different AI agents to share information and communicate effectively.
• Visualisation and Low Code: Significantly reducing development and maintenance barriers, helping users at different levels quickly implement AI agent solutions.
• High Concurrency and Traceability: Distributed Actor and Event Sourcing ensure stability and auditability in large-scale scenarios.
• Security and Scalability: Cloud-native DevSecOps solution flexibly meets industry customisation needs while ensuring compliance.

Looking ahead, aevatar.ai will continue to iterate and upgrade, building a fully functional and robust Agent-as-a-Service platform. We aim to bring convenient and powerful AI collaboration experiences to more industries and individual users.

We would like to invite you, our community, partners, and enterprise users to participate in the ecosystem's growth and work together to promote the openness and success of AI agent systems. For further information, please refer to our official documentation, GitHub repository, or contact our team at [email protected] to discuss ways aevatar.ai can best meet your needs.

Disclaimer: This white paper provides an overview of aevatar.ai’s architecture and capabilities. Feature specifications may evolve; please refer to official releases for the most up-to-date information.