Architecting Yasu, by John in 't Hout, CTO, Yasu Cloud
I’m often asked what sets our technology apart from the myriad cloud management solutions available in the market. The answer is simple: at Yasu, AI isn’t just infused into the infrastructure but the whole foundation on which our platform is built.
How an expensive problem became our mission.
Cloud platforms have transformed the world of engineering, but with that new agility comes a massive problem: unpredictable cloud spend. Studies show that nearly one-third of global cloud spend (over $500 billion annually) is wasted. Some significant areas contributing to this include idle resources, ineffective pricing strategies, decentralized governance, a lack of real-time visibility, and delayed or missed optimizations. My Co-Founder, Vikram, and I saw this first-hand through our years of working at global enterprises and scale/start-ups. The pattern was always the same - Engineers spending countless hours chasing cost spikes, leaving behind very little room for actual innovation, and in parallel, losing customer satisfaction.
How we laid the Agentic AI foundation.
The existing solutions simply weren’t enough. Most rely on rule-based alerts and post-hoc analytics - catching waste after it’s hurt the bottom line. So, we designed Yasu’s core as a network of autonomous AI agents powered by our “agentic” architecture. These are not just automation scripts; each agent has short-term and long-term memory, reasoning capabilities, and the ability to act independently, continuously learning from billions of billing and telemetry events. And every interaction that the user has with Yasu.
Our AI leverages our proprietary trained embedding model (yasu-cloud-infra-v1) and accompanying reranker trained on millions of cloud billing records, achieving an industry-leading accuracy. This powers our temporal knowledge graphs to track behavior over time and perform anomaly detection and pattern recognition in real time. Rather than centralizing all logic, we orchestrate agent tasks through Langraph, allowing for specialization; some agents monitor spend, others flag misconfigurations, handle security and compliance, etc.
Yasu’s AI is constantly learning, adapting, and evolving.
The heart of Yasu’s AI is a combination of Agentic Reinforcement Training (ART), our proprietary embedding models, and rerankers. Every agent adapts based on real-world user feedback—accepted, rejected, or modified suggestions all feed back into the system to improve future decision-making. This enables emergent behavior: agents autonomously prioritize the optimizations that best fit your engineering workflows and business priorities, always striving to maximize impact.
Building for Developers - a seamless, proactive platform.
We designed Yasu to meet teams where they work - not as another data silo. Our platform embeds within established workflows, integrating natively with Slack, GitHub, GitLab, and in the CI/CD pipelines. Rather than presenting lengthy reports, Yasu’s agents intercede directly in development and deployment processes, flagging costly mistakes when they’re easiest and cheapest to fix.
Turning billions of data points into actionable cost-saving measures.
Yasu’s data accuracy and insight rely on our extensive ETL pipelines. Agents process millions of records - usage, billing, infra telemetry - digesting them into unified signals. That raw data serves not just for reporting, but for real-time detection of anomalous patterns, behavioral changes, and pattern recognition, enabling us to flag cost-saving opportunities near real-time that typical audits might miss for months, if at all.
Watch this space for what is next - our roadmap.
We’re already building toward supporting even more complex, multi-cloud environments. The roadmap includes self-service onboarding, richer and more extensive integrations across AWS, GCP, Azure, and next-generation compliance and security agents.
Our ambition is to create an autonomous AI “Cloud Engineer” that becomes an indispensable part of every team. Yasu automates away not just the tedium, but the cognitive load of infrastructure management itself. We are giving you the colleague you wished you had hired from the start.
AI for your thought.
The result? Engineers can focus on building remarkable products, not reconciling invoices. Yasu is proof that cloud management driven by true autonomous intelligence isn’t just possible - it’s here to stay