Enter Gains GenAI Cost Visibility and Cloud Spend Control with nOps

Overview

Enter, a Sequoia-backed Brazilian startup building collaborative developer tools, is growing rapidly across AWS and OpenAI. As their use of GenAI grew for document processing and experimentation, they faced growing cloud spend, especially related to OpenAI usage, without a dedicated cloud economics team.

With hundreds of thousands of credits in the cloud across providers, Enter’s finance and engineering teams needed better visibility into how those credits were burning down, and more control over how AI-related costs were being tracked, forecasted, and allocated across teams and projects.

The Challenge

Enter’s primary goals were to:

• Track credit usage and burndown across cloud platforms
• Gain visibility into OpenAI costs per user, project, and model
• Forecast future GenAI spend with enough clarity for planning and governance
• Give finance and leadership teams, including the CFO, visibility into cloud costs and margins, including R&D vs COGS, through unit economics and showbacks
• Improve container efficiency and reduce unnecessary EKS resource waste
  

The Solution

nOps implemented a phased approach to help Enter build visibility and control:

• Enabled cost allocation dashboards to track credit burn and map spend across teams, projects, and environments using workload-aware attribution.
• Backfilled historical data to populate burndown tracking dashboards for immediate clarity
• Enabled OpenAI cost forecasting at the daily, user, and model level
• Identified EKS optimization opportunities through container rightsizing and spot recommendations
• Set up Compute Commitment Management to assess long-term savings strategies without introducing risk

With nOps, Enter gained a centralized platform to manage cloud spend, track GenAI costs, and prepare for long-term scale.

Their finance and engineering teams now speak the same language, backed by real-time dashboards that surface optimization opportunities and provide clarity for leadership and investors alike.

As Enter expands its AI footprint, nOps continues to support their cost governance journey with scalable automation and deep visibility into both GenAI and infrastructure spend.

“nOps allowed us to understand where our credits were going and build confidence that we were not spending more than we should. The automated cost allocation rules were a great help to bridge the gap while we improved tagging and governance on each provider.”

Mike Mac-Vicar, Co-Founder / CTO , Enter

Results

Through nOps, Enter now has:

• Full visibility into credit utilization and burn-down across cloud providers, helping build confidence in spend tracking
• The ability to forecast OpenAI usage and allocate costs by project, user, or model, improving alignment between engineering and finance
• A foundation for rightsizing Kubernetes workloads to reduce waste and improve cluster efficiency
• Support for commitment planning, including Reserved Instance strategies during rapid product development

Business Impact

With nOps, Enter gained a centralized platform to manage cloud spend, track GenAI costs, and prepare for long-term scale.

Their finance and engineering teams now speak the same language, backed by real-time dashboards that surface optimization opportunities and provide clarity for leadership and investors alike.

As Enter expands its AI footprint, nOps continues to support their cost governance journey with scalable automation and deep visibility into both GenAI and infrastructure spend.

“The usability and depth of the exploration tools helped our engineers to identify the drivers of our costs quickly. To plan reserved instances while building a new product is almost a contradiction; nOps’ Commitment Management came to rescue us”

Mike Mac-Vicar, Co-Founder / CTO , Enter