Zerverless uses generative and agentic AI to turn system context into clearer answers, stronger decisions, and bounded next steps — while ownership and control stay with the team building on AWS.
We use generative AI to turn architecture notes, AWS details, product knowledge, and operational signals into clearer explanations and drafts. It helps us surface the relationships behind a system and gives teams a stronger starting point for a decision. The model is never the source of truth: its output is grounded in approved context and remains open to engineering review.
Learn about serverless generative AI
We use agentic AI for bounded technical work: tracing a question through architecture material, proposing a focused path, and assembling the evidence a person needs to act. Agents use narrow tools and explicit instructions, never open-ended AWS or customer-data access. They can prepare, compare, and recommend; people remain responsible for consequential changes.
Learn what agentic AI is
A short description of the user, the decision or action, the available data, and the cost of a wrong answer is enough to start.
