Turn Azure into a cost-aware console. Every resource shows cost, owner, and history.
Atmoz measures the cost of every model, agent and workload as it happens, identifies inefficient usage, and helps engineering teams act before waste reaches the bill.
Control spend. Optimize usage. Prove AI ROI.
AI Engineering • Platform • DevOps • Cloud Operations • FinOps
A single AI task can trigger reasoning, model calls, tool calls, retries, expanding context and multiple agents – turning one task into dozens of billable events. Most companies discover the economics afterward.
Atmoz moves AI financial control upstream – from the invoice to the engineering decision.
Measure spend against users, teams, agents, workloads and business outcomes.
Detect inefficient usage and intervene while the workload is still running.
Bring recommendations, policies and actions directly into the IDE, Slack and Teams.
Reduce redundant prompts and oversized context that consume tokens without improving the result.
Identify when a lower-cost model can deliver the required quality and reserve premium models for work that needs them.
Identify repeated context, unnecessary model calls, and workloads that can execute more efficiently.
Detect excessive loops, retries, overlapping calls, and abnormal agent consumption before costs escalate.
Track projected consumption and set thresholds by user, task, team, project, or agent before budgets are exceeded.
Escalate abnormal or costly behavior to the right engineer, with approval required for consequential actions.
Turn Azure into a cost-aware console. Every resource shows cost, owner, and history.
Prioritized recommendations with generated commands, to be fixed immediately via chat
Complex discount programs made simple and effective. Atmoz calculates the optimal reservation mix, maximizing savings while matching real usage.
Automatic owner assignment, runtime limits, proactive reminders.
Finius proactively checks in before resources drift off-budget.
Conversational FinOps with escalation flows for stalled actions.
Atmoz scans continuously for unused assets, detached disks, idle IPs, storage, and initiates a process to safely retires or downgrades them
Read-only by default, fully customer-controlled, and deployable inside your environment when security, data residency, or compliance requires it.
Atmoz analyzes metadata without accessing workload or application data.
You retain control of permissions and can revoke access at any time.
SSO and RBAC integrate Atmoz with your existing identity and access policies.
Track ownership, policy changes, approvals, and actions with complete audit trails.
Deploy Atmoz inside your own environment to meet strict security, data residency, and compliance requirements.
Unlike %-of-spend models, Atmoz is priced per resource to stay aligned with reducing waste.
Traditional cost tools start with billing. Atmoz starts where cost is created – inside engineering.
Reconstruct cost and identify inefficiencies before they appear in billing data.
Bring cost, context, ownership, and recommended actions directly into Slack, Teams, and the IDE.
Create one efficiency layer across models, agents, AI tools, and cloud environments.
Route issues to the right owner and move from recommendation to approved action without another dashboard.
Atmoz helps teams understand, govern, and optimize AI usage across models, agents, API calls, tokens, projects, and teams before inefficient usage becomes unnecessary spend.
Atmoz identifies inefficient cloud resources as they are created, assigns ownership automatically, and helps engineers take action before inefficiencies reach production and generate unnecessary cost.
Finius, our AI bot, delivers recommendations, ownership information, and one click fixes directly in Slack, Microsoft Teams, and IDE, allowing engineers to act without leaving their workflow.
Atmoz automatically maps cloud resources and AI usage to the teams and individuals responsible for creating and managing them, improving accountability and remediation speed.
Atmoz applies governance through budgets, quotas, permissions, usage policies, ownership controls, and audit trails, helping organizations manage AI usage at scale.
Yes. Atmoz supports budgets, quotas, usage limits, and threshold notifications to help organizations control AI and cloud usage before costs exceed expectations.
Atmoz allocates AI costs across users, teams, projects, models, agents, and business units, providing clear visibility into ownership and consumption.
Yes, but not only. Atmoz focuses on AI and cloud efficiency, governance, ownership, and remediation. While it provides visibility into AI usage, its primary goal is helping teams take action before inefficiencies become waste.
No. Atmoz uses a secure read-only architecture with SSO, RBAC, governance controls, and audit trails designed for enterprise environments.
Bring real-time AI and cloud efficiency into engineering workflows.
CLASS OF 2026