Catio, the Architecture IDE: the control plane over Claude Code, built on Claude
5 min
to a ship-ready spec per ticket
~10%
enterprise-wide cost savings
~$9M
in modeled returns
About Catio
Catio is the Architecture IDE: the reasoning, decision, design, and governance layer for modern tech stacks. It is the control plane above Coding AI. Claude Code is the execution plane, and Catio defines what Claude Code executes. Backed by RRE Ventures, Eniac Ventures, Celero Ventures, Vermillion, and Jefferies, Catio won the VentureBeat Transform 2025 "Coolest Tech" award, is SOC 2 Type II compliant, and is in production with large $5B+ enterprises and scaling tech companies alike. The platform runs largely on Claude. Proxet has supported the build as a development partner over multiple years.
Challenge
- With AI-accelerated coding, architecture decisions have become the bottleneck. AI coding tools such as Claude Code force-multiplied software execution, while the decisions that guide and govern that execution still happen across fragmented context, disconnected tools, and isolated trade-offs. Software delivery has a system, where architecture decisions do not.
- The cost lands at enterprise scale. Across the industry, 30-40% of engineering effort goes to rework from drift and technical debt, sprawling tech debt turns into optimization fire drills, and features get built to designs that are oblivious to the system and its objectives. With AI coding, that cost now grows at AI speed.
- Enterprises running large tech estates needed a control plane above the coding IDE: a system for understanding the stack, deciding and designing what gets built, and keeping everything aligned as it evolves, at the speed of AI-assisted coding. That control plane needed a reasoning engine capable of judgment at system scale, and a bridge into the coding environments where the work ships.
Solution
- Catio built the Architecture IDE and, in production, runs it largely on Claude. Claude Opus carries the most demanding reasoning in the product: weighing objectives, constraints, and trade-offs across multi-billion-dollar enterprise tech estates to turn an architecture question into a decision-grade plan, and a decision into a system-aligned, execution-ready spec. This is judgment at system scale, the work Anthropic's models were built for, and Catio organized its product around that strength.
- Catio built Catio MCP, the bridge between the control plane and the execution plane. Developers working in Claude Code query Catio's model of their system in context, generate Blueprints (a design, a recommendation, or a plan), and pull approved, system-aligned specs into the editor to ship against. Architects review exceptions, not every design. Anthropic's intelligence sits on both sides; Catio connects them. For enterprises this is the Architecture-Led AI SDLC; for consultancies and SIs it is a delivery multiplier across every client engagement.
- Proxet supported the build as a development partner over multiple years, contributing engineering capacity alongside Catio's engineering team as the product grew from architecture intelligence into a full control plane above Coding AI. Proxet can now equally leverage that layer, with Claude Code alongside it, as the platform that powers its own delivery for its clients.
Outcome
- Mean Time to Informed Decision (MTID) of roughly minutes to hours for 7-9 figure tech estate modernization, re-architecture, and optimization plans, down from weeks to months.
- MTID of 5 minutes to a system-aligned spec for each ticket or PRD that developers can ship again (from one reviewed design per week before).
- Roughly 10% enterprise-wide savings identified from cost optimization programs on 8-figure tech estates.
- $10M+ modernizations and re-architectures informed regularly, with directional ROI in that range on single initiatives.
- Roughly $9M in modeled returns from the Architecture-Led AI SDLC: less rework, MTID from weeks to minutes, and architect capacity scaled.