Catio’s platform acts as a digital twin, providing blueprint-like visualizations of an enterprise’s architecture. It can plan new tech stacks and continuously evaluate architecture, serving as an “ongoing AI advisor.” This strategic observability into subsystems allows for better decision-making and investments by enterprise leaders.
Traditionally, enterprises have relied on high-priced architects and expensive consultancies to build their tech stacks. However, this approach often results in designs that “live in people’s heads” and are not easily translated into concrete plans. Catio’s platform solves this problem by creating a “canonical view” of architecture requirements and providing dashboard-level analytics. A 24/7 AI advisor offers recommendations, ensuring that leaders have a clear understanding of their tech stack.
Catio’s platform is built on a sophisticated workflow of AI agents that collaborate to create design proposals. This multi-agent system includes a chief architect agent, retrieval agents, and agents specialized in areas such as data, messaging, and security. The lower-level AI analyzes the stack and makes recommendations based on business context, which are then filtered back up to the chief AI architect. This context-aware use of foundational models provides precise and valuable insights.
The platform also allows users to integrate their tech stack components and create policies around them, forming a codebase that codifies the entire architecture. Users can see changes from snapshot to snapshot and gain a true understanding of their architecture. They can also analyze raw data to understand parent and child relationships and save different teams as views.
Catio has already garnered interest from larger startups and Fortune 100 companies. Major design partners are actively testing the platform, and the company has raised $4 million in pre-seed funding. The commercial release is expected in the fall, with another round of fundraising on the horizon.
The potential impact of Catio’s platform is significant. Jordan Rosen, former SVP and GM at Disney, highlighted the challenge of quantifiable visibility on cost performance in cloud operations. He believes that Catio’s dashboard-level visibility and recommendations could greatly improve tracking and evaluation of roadmaps and performance. Satish Raghunath, VP of engineering at Salesforce, praised Catio for tackling the complex issues faced by infrastructure engineers and making the CTO’s life easier.
In conclusion, Catio’s AI copilot for tech stack architecture offers a data-driven solution to the increasing complexity of enterprise architectures. By providing strategic observability, precise recommendations, and a comprehensive view of the tech stack, Catio aims to revolutionize how CTOs and chief architects approach their infrastructure building and management. With its commercial release approaching, Catio has the potential to become an essential tool for enterprise leaders in optimizing their tech stacks.
