Zelaros connects to every AI provider your team uses, both APIs and SaaS tools, and shows you spend by service, team, and developer. Set alerts. Assign ownership. Stop reconstructing costs after the fact.
Request Early AccessYour current workflow for AI cost monitoring is reactive by design: check AWS Cost Explorer for Bedrock occasionally, log into OpenAI monthly, ask a platform engineer to pull usage stats when Finance or the CTO needs a number. There are no automated alerts. There is no squad-level attribution. You find out about cost anomalies when the invoice arrives or when the CTO forwards a Finance email asking what happened. As your team grows past 30 engineers across multiple products, this problem does not get easier.
What changes when you have attribution.
Zelaros monitors daily consumption across every connected provider and alerts you when spend crosses a threshold you define. You find out about a 40% OpenAI spike on day two of the sprint, not at billing close. You know which service drove it and when it started. Investigation takes minutes instead of hours, and the fix happens while the billing cycle is still open.
You give each squad lead a Zelaros view scoped to their team's spend. They see their own API consumption, their own SaaS tool usage, and their own trend data. Cost accountability decentralizes without requiring a mandated governance process. Visibility alone changes how engineers make decisions about model selection and call frequency.
Before the Cursor or GitHub Copilot renewal, you pull a per-seat utilization report. You see which seats have been active in the past 30 days and which have not. You remove the inactive seats, present the utilization data for the active ones to Finance, and make a renewal decision grounded in actual usage rather than a general sense that the team finds the tool useful.
Zelaros maps billing data to your team structure automatically. No tagging conventions to enforce, no aggregation pipeline to build.
Configurable thresholds with email and Slack notification so you know about anomalies before they become invoice line items.
Last active date and activity frequency for every Cursor, GitHub Copilot, and Claude.ai Teams seat, filterable by inactivity threshold.
[PLACEHOLDER: Quote in Sarah's voice. Target sentiment: 'We had a production API cost spike that added $11,000 to our monthly OpenAI bill. Before Zelaros I would have found out three weeks later. With Zelaros I found out 36 hours after it started, traced it to a specific endpoint, and had a fix deployed before the week was out. That one alert paid for a year of the product.']
Get squad-level AI cost visibility running before end of week. No engineering work required.
Request Early Access → See How It Works