Introduction
Managing AI infrastructure across an organization isn’t just complex — it can be chaotic. As teams scale their AI efforts, they’re often met with a fragmented mess of tools, dashboards, and spreadsheets just to answer basic questions:
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How much are we spending?
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Which models are running, and where?
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What’s the current usage across teams or projects?
This kind of scattered visibility becomes a real bottleneck, especially for teams that are just trying to deploy models and get work done. Whether it’s budgeting, tracking compute hours, analyzing performance, or even knowing who triggered what action, having to manually piece this together from different tools can be overwhelming and error-prone.
For fast-moving AI teams, these operational gaps create friction across the organization, affecting engineers, data scientists, product managers, and finance teams. Without clear visibility, everything slows down.
In this blog, we’ll look at why visibility is often a challenge for AI teams and how a centralized solution can solve it. We’ll break down what’s not working today and show how a unified view can streamline your operations, bring real-time clarity, and give you complete insight into your platform usage.
Why It’s Hard to Manage AI Workflows Today
Building and running AI systems is already complex. But managing them day to day? That’s even harder. Many teams struggle to keep track of everything that’s happening — from model usage to compute spend.
Here are some of the common issues:
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Too many tools: You have to jump between dashboards, cloud billing pages, and monitoring systems. There’s no single place to see what’s going on.
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Hard to track compute: If you’re deploying models on your own GPU clusters or across cloud providers, it becomes difficult to monitor what’s running, where it’s running, and how much it’s costing you.
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No clear usage history: Most platforms don’t let you easily see how often your models are being used, who is using them, or when training jobs are triggered.
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Limited visibility into costs: Without a proper breakdown of usage and spend, it’s easy to go over budget without noticing until it’s too late.
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Lack of transparency: When something goes wrong, like slow predictions or errors, it’s hard to know why it happened or how to fix it.
Even when tools offer some level of monitoring, they’re usually focused on one part of the system. You don’t get a full view of your models, data, teams, and spend in one place.
That’s where Clarifai’s Control Center comes in.
What is Control Center?
Control Center is a unified dashboard that gives you complete visibility into how your organization is using the Clarifai platform, all in one place.
It acts as your central command dashboard, bringing together metrics, usage data, financial insights, and team activity into a single, intuitive experience. Instead of juggling multiple tools or switching between tabs, the Control Center allows you to monitor and manage everything from a single screen.
With modular tabs, interactive charts, tables, and customizable filters, the Control Center provides a comprehensive view of your operations and evolves with your needs.
Here’s how the Control Center helps teams stay focused and in sync:
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Streamline operations by consolidating all relevant information into a single screen, reducing context switching and improving decision-making efficiency.
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Track resource utilization with visual tools like charts, graphs, and tables that reflect real-time activity across your AI workflows.
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Centralize financial data to monitor costs, break down spending across projects, and identify opportunities for optimization.
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Transform raw platform data such as model predictions, search operations, stored inputs, and training hours into actionable insights that guide development.
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Understand team dynamics and how different users and departments are contributing to platform usage and overall spend.
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Audit user activity by tracing events back to their origin, ensuring accountability and transparency across your deployments.
The Control Center is designed to be the single source of truth for your Clarifai usage. It gives teams a unified view of operations, model training, predictions, input data, and more.
Now that you know what the Control Center is and why it matters, let’s take a closer look at the different tabs inside it — each designed to give you visibility into a specific part of your AI operations.
Control Center Tabs
Now let’s dive into the different tabs within the Control Center. Each tab is purpose-built to help you monitor specific aspects of your AI workflows — from resource usage to team activity. Here’s a breakdown of what each tab offers and how you can use it to stay in control of your operations.
Overview Tab
The Overview tab is the first thing you see when entering the Control Center. It acts as a customizable dashboard, allowing you to pin the most important data and charts from other tabs into one view. This helps you build a high-level summary of your account activity, tailored to what matters most to you or your team.
Key Metrics
Right at the top of the Overview, you’ll find a set of quick stats that summarize your platform usage for the selected date range. These include:
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Total operations (such as model predictions and search requests)
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Total training hours consumed
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Average number of stored inputs
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Number of models used
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Types of models used
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Total number of predictions made
These metrics are automatically updated based on the time filter, giving you instant insight into how your resources are being used.
Date Range Filters
To give you more control over the data you see, the Overview includes a date range selector. This lets you filter your view by selecting a preset range (like the current billing cycle or last 3 months) or setting a custom range using the date picker.
Even if you’re on the free plan, you can still track activity across these timeframes. Paid plans give you additional visibility and access to more detailed features.
Custom Charts
One of the most powerful features of the Overview tab is the ability to pin charts from other sections of the Control Center. This turns the Overview into your own personalized dashboard.
Pinned charts help you monitor the metrics you care about without having to navigate away. You can rearrange them to suit your workflow or remove charts as priorities shift. Whether you’re tracking model training trends or input data over time, the Overview gives you a flexible way to stay informed at a glance.
Usage & Operations Tab
The Usage & Operations tab gives you a detailed view of how your organization is using the Clarifai platform. From predictions to training to data storage, it surfaces the metrics that matter most.
You can monitor:
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Total number of operations, including model predictions and search activity
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Training hours, broken down by model type (transfer learning and deep training)
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Inputs stored, showing the total and average number of inputs you’ve added to the platform
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Model predictions, filtered by type, model ID, and date
These insights are presented through interactive charts and summaries that make it easy to spot usage trends and operational patterns. You can filter everything by custom date ranges and pin specific charts to your Overview tab for quick access.
Each metric supports drill-down views so you can go from a high-level summary to detailed reports when needed. You can also change the chart type by clicking the icons in the upper-right corner. Choose the chart type that works best for you — bar chart or line chart.
This level of visibility helps teams stay informed and make better decisions about how they manage and scale their AI workflows.
Costs & Budget Tab
The Costs & Budget tab gives you a comprehensive look at the financial side of your operations on the Clarifai platform. It highlights where your spending is happening—across predictions, training, storage, and more—so you can manage costs with confidence.
You can monitor:
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Total spend across all billable operations within a selected date range
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Training costs, broken down by model type (transfer learning and deep training)
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Model prediction costs, filtered by type, model ID, and date
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Input storage costs, showing the cost of storing data on the platform
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Operation costs, including predictions and search activity
Each category is visualized through interactive charts that let you track spend over time, filter by custom date ranges, and drill into specific cost types. You can also pin charts to your Overview tab for easier access to the insights that matter most.
Detailed reports are just a click away, giving your team a clear view into the cost breakdown behind each workflow—helping you stay within budget and scale usage efficiently.
Teams & Logs
The Teams & Logs tab gives you full visibility into your organization’s activity on the Clarifai platform. It’s built for transparency and control—helping teams monitor key events, reinforce security, and maintain detailed audit trails.
You can monitor:
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Organization and team membership activities, including creating teams, sending invites, and managing users
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Collaborator changes, such as adding, editing, or removing collaborators
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Application-level actions, like creating, updating, deleting, or duplicating apps
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Model, workflow, and module operations, including training models, publishing workflows, or modifying modules
Each operation log captures essential context, including who performed the action, when it happened, what was done, where the request came from, and whether it succeeded. You can view logs across all your apps or narrow the focus using filters for specific apps and custom date ranges.
The interface includes expandable sections for each event—giving you the option to quickly skim through a summarized view or dive into the full operation details when needed.
This feature is currently available for users on Professional and Enterprise plans.
Want a deeper look at how audit logging works and how you can track every operation in detail? Check out our detailed blog post on audit logging.
Conclusion
Managing AI at scale doesn’t have to mean juggling dashboards and digging through logs. The Control Center brings everything into one place so you can quickly understand usage, track costs, monitor model performance, and see how teams are working across your platform.
From high-level overviews to detailed logs, it gives you the visibility you need to keep things running smoothly and make smarter decisions without the overhead. It’s built to reduce friction and give every team a clear view of what’s happening and why.
Also, once you deploy your own models to dedicated compute using Compute Orchestration, managing everything that comes after should be effortless. That’s why we’re launching a new Compute Orchestration tab in the Control Center in the coming weeks.
This new tab gives you full visibility and control over your compute environment — from managing deployed models and monitoring workloads to tracking GPU clusters and reviewing detailed spending breakdowns. Everything you need to manage and monitor your infrastructure will be centralized in one place.
Ready to give it a try? Sign up and explore the Control Center for yourself. Watch the tutorial below to see how the Control Center works.
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