AI-ASSISTED AUTOMATION · IT & Technology Operations

Catch unexpected cloud and AI spend before invoices arrive.

Attribute cloud and AI service costs to usage sources and flag unusual spend before budgets are breached.

  • Ingest provider usage and billing data.
  • Monitor budgets.
  • Attribute unexpected spend changes.

Tell us what you need; we will define the scope and setup steps with you.

Explore the workflow
Cloud & AI Spend ManagementExample workspace
Review a spend deviation against policyIllustrative workspace
A critical service approaches its budget threshold
Input
Cloud and AI usage records and budget thresholds
Action / check
Compare the increase with its usage source and stop policy
Output
A spend alert and review proposal for the authorized owner
Source: Authorized service usage and cost records
Cloud and AI spend visibility
Budget anomaly alerts

KEY FEATURES

What this product will handle for your team.

Practical capabilities with a clear role in your workflow.

Cloud and AI spend visibility

Ingest provider usage and billing data.

Budget anomaly alerts

Monitor budgets.

Cost driver analysis

Attribute unexpected spend changes.

USE CASES

How could this fit your day-to-day work?

Explore the need, the proposed approach and your team's role.

SELECTED USE CASE

A model's token spend rises unexpectedly

  1. 01
    THE NEED

    A model's daily token cost rises without anyone noticing the trend.

  2. 02
    AI APPROACH

    Combine provider billing and usage records and report cost drift by model or project.

  3. 03
    NEXT STEP

    Deliverable: Service-level spend and limits view. Success metric: Spend above budget.

YOUR QUESTIONS

What to know before implementation.

Review the product scope, connection requirements and approval points.

How does this solution work?

Cloud and AI API costs can rise unnoticed across providers.

Source and need

A model's daily token cost rises without anyone noticing the trend.

Will it automatically stop spending?

Alerts and limits depend on provider capabilities; automatic stopping requires explicit policy and authority.

What is included in the scope and outputs?

Deliverable: Service-level spend and limits view. Success metric: Spend above budget.

Deliverable: A spend warning, cost attribution and policy-based control decision.

Implementation is scoped after checking access and data in the customer’s systems; no prebuilt connection is assumed.

How do quoting, setup and connections work?

Let’s define the scope together.

Workflow setup, integration assessment for suitable systems, testing, monitoring and ongoing management. Core deliverable: Service-level spend and limits view.

AWS, Azure or GCP usage and billing APIs

Which steps belong to AI and your team?

Analysis and workflow

Combine provider billing and usage records and report cost drift by model or project.

Proposed output

Deliverable: Service-level spend and limits view. Success metric: Spend above budget.

Team review

Authorization, approval steps and exception owners are agreed with your team during setup.

Business rules

Implementation is scoped after checking access and data in the customer’s systems; no prebuilt connection is assumed.

How are data, access and security handled?

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What data and systems are needed for cloud and ai spend visibility?

Setup reviews access to AWS, Azure or GCP usage and billing APIs. Data scope, permissions and transfer methods depend on the client environment; a ready-made connector is not assumed.

OTEMATIK · NEXT STEP

Let’s define the right scope for your business.

Share your current process and required connections. Our team will help define the implementation scope and next steps.

AI-ASSISTED AUTOMATION

Tell us what you need to implement.

Tell us what you need and how your team works today. We will review scope, required connections and implementation steps with you.

Inquiry subject: Cloud & AI Spend Management

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