One line of code reveals exactly where every dollar goes.

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January 6, 2026

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Cloudir | LLM Ops

API management

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One line of code reveals exactly where every dollar goes.

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Overview

LLM Ops is an AI tool dedicated to tracking and optimizing the costs related to various AI platforms such as OpenAI, Claude, and Google's Gemini. Designed for AI-first teams, it features a user-friendly integration process with just two lines of code, offering an effective way to gain clear insights on where each expense goes by model, agent, and API call.

It provides real-time visibility across these AI platforms, enabling users to see which models consume most of their budget. It is also capable of detecting cost peaks before they reflect on the invoice allowing for better management of resources.

Another major feature of LLM Ops is its recommendatory system for data-driven decisions based on AI-powered optimization suggestions. The tool is designed with a major focus on security; it does not store any API key and maintains less than 10ms latency overhead.

Currently, it is trusted by numerous AI teams for API cost tracking and is practiced by startups to enterprises. The LLM Ops tool is in its early access phase, giving early users certain benefits like influencer status in roadmap decisions and free lifelong access.

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January 6, 2026

Khursheed Hassan

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Initial release of Cloudir | LLM Ops.

Author

Khursheed Hassan

@khursheed-hassan

I spent years building products at AWS, Western Digital, and Motorola. Now I'm founder & CEO of Cloudidr, where we help AI companies cut infrastructure costs 30-40%.

www.cloudidr.com

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API management Cloudir | LLM Ops

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Pros and Cons

Pros

Detailed API cost breakdown

Single line of code integration

Multi-provider cost tracking

Secure, no API key storage

Low latency overhead

Compatibility with existing code

Real-time cost visibility

Cost peak detection

Model-wise expense visibility

Aids data-driven decisions

Ideal for diverse business sizes

Only retains metadata

No actual content access

Insight into budget-consuming models

Easy setup process

Startup-friendly

Trustworthy and in practice

Early access benefits

Influence in development decisions

Free lifetime access for early adopters

Suitable for enterprise-level technology solutions

Supports multiple Ai platforms

Easy collection of cost insights

Highly secure API handling

Early warning for cost spikes

Free for tracking and alerts

Encourages FinOps principles adoption

Transparent about no API key storage

Minimal latency addition

67-second setup

Easy to stop using

Live action dashboard

Real-world data for insights

Open-source future plan

Safe even if compromised

Content untouched by logging

Allows for revoking API keys

Completely free core features

Potential for premium future upgrades

View 34 more pros

Cons

Potential latency overhead

Integration requires code manipulation

Early access phase

Potential future paid tiers

No content or data storage

Limited model tracking

Reliance on user code adjustment

Limited security transparency

No direct content access

View 4 more cons

Q&A

What is LLM Ops?

LLM Ops is an artificial intelligence tool designed to assist AI-first teams in efficiently managing and optimizing their AI API costs. It offers cost tracking across multiple AI providers and furnishes detailed breakdowns of spending by model, agent, and individual API calls. It doesn't require API key storage and operates securely, only retaining metadata.

How does LLM Ops help manage and optimize AI API costs?

LLM Ops aids in managing and optimizing AI API costs by providing a comprehensive visibility across your API usage and cost patterns. It allows you to track costs across different AI service providers and offers AI-powered recommendations for cost optimization, guiding users towards cost-saving decisions.

How can LLM Ops track costs across multiple AI providers?

LLM Ops can track costs across multiple AI providers like Anthropic, OpenAI, and Google's Gemini. This is achieved by integrating a single line of code that brings an expanded view of an entity's spending patterns. The cost breakdown can be viewed by the model, agent, and individual API calls, offering a clear picture of where the money goes.

What is the process to integrate LLM Ops in my existing code?

To integrate LLM Ops into an existing code, users just need to integrate one line of code. The process doesn't require any migration or changes to your application. Furthermore, LLM Ops ensures a quick setup that does not necessitate the storage of your API keys.

Does LLM Ops provide a detailed breakdown of spending?

Yes, LLM Ops provides a detailed breakdown of spending. By integrating just one line of code, users get a comprehensive line-item view of spending by model, agent, and specific API calls. This helps identify exactly where every dollar goes in terms of resource allocation.

What kind of visibility does LLM Ops provide for API usage and cost patterns?

LLM Ops provides increased visibility of your API usage and cost patterns. This includes a detailed view of the spending across big AI service providers like Anthropic, OpenAI, and Google's Gemini, down to the level of specific models, agents and API calls. This level of detailed visibility allows users to make data-driven decisions and identify the cost spikes before they become substantial.

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Can LLM Ops help identify cost spikes before they reflect in my invoice?

LLM Ops can help identify cost spikes before they reflect in your invoice. It offers detailed insights on spending by models, agents, and individual API calls in real time, allowing businesses to catch cost spikes as they occur and avoid unexpected expenses.

How does LLM Ops offer optimization recommendations?

LLM Ops offers AI-powered optimization recommendations. By analyzing your AI API usage and cost patterns, it provides guidance towards cost-saving decisions. This enables businesses to make data-driven decisions and optimize their AI API costs effectively.

Do I need to store my API keys to set up LLM Ops?

No, to set up LLM Ops, storage of API keys is not necessary. This adds an extra layer of security to the process as it leaves no traces of your API keys, hence diminishing any associated security risks.

Can startups and large enterprises both use LLM Ops effectively?

Yes, LLM Ops is designed to suit the requirements of different business sizes, from startups to large enterprises. It has a simple and flexible setup process and doesn't require any migration or changes to existing code, allowing diverse needs to be catered to.

Does LLM Ops ensure secure operations?

LLM Ops ensures secure operations by not storing any API keys, which typically represent a security risk. The tool retains only metadata, ensuring that even in the event of a security breach, sensitive information would not be compromised.

How does LLM Ops handle data privacy and metadata storage?

In terms of data privacy, LLM Ops does not access or store actual content or data passed through the APIs it tracks. It only retains metadata, effectively nullifying risks associated with data privacy. It operates by proxying requests, logging token usage and costs, and returning the responses unchanged, ensuring that actual content never interacts with its database.

Can LLM Ops be used with APIs from companies like Anthropic, OpenAI, and Google's Gemini?

Yes, LLM Ops can be used with APIs from companies like Anthropic, OpenAI, and Google's Gemini. It provides the ability to track costs across these multiple AI providers, giving a clear and detailed view of the spending patterns.

What are the latency implications of using LLM Ops?

The use of LLM Ops has low latency implications. It maintains a latency overhead of less than 10ms, causing minimal impact on the performance or response times of the APIs it tracks.

What is the LLM Ops setup process like?

The LLM Ops setup process is simple and quick. It only requires the integration of a single line of code and does not necessitate the storage of your API keys. Since it integrates into your existing code, there's no need for any migration or app changes.

How can LLM Ops help with budgeting and financial management?

LLM Ops assists with budgeting and financial management by providing detailed insights into your AI API usage costs. It offers a comprehensive breakdown of spending and allows you to identify cost spikes before they reflect in your invoice. This information can be instrumental in making informed budgeting decisions and efficient financial management.

Does LLM Ops require any migration or app changes?

No, LLM Ops does not require any migration or app changes. Its setup process is designed to be straightforward and easily integrates into existing code.

Does LLM Ops store actual content or data passed through the APIs it tracks?

LLM Ops does not access or store actual content or data passed through the APIs it keeps track of. It only logs metadata like model name, token counts, timestamps, and calculated costs, ensuring data privacy and secure operations.

What kind of AI service providers can LLM Ops aid with?

LLM Ops can aid with APIs from a wide range of AI service providers. Its design and capabilities allow for effective cost tracking and optimization of APIs from companies like Anthropic, OpenAI, and Google's Gemini, among others.

Does LLM Ops offer insights about API usage?

Yes, LLM Ops offers comprehensive insights about API usage. By successfully integrating it, businesses can get detailed and instant visibility across their API usage, understanding which models are draining their budget and identifying potential cost spikes before they impact invoices.

What is LLM Ops?

LLM Ops is an Artificial Intelligence tool that primarily features optimization and management of AI API costs for AI-first teams. Its main functions include tracking costs across multiple AI providers, providing a detailed break down of spending by model, agent, and individual API calls, and offering AI-powered optimization recommendations. One significant aspect of LLM Ops is its simple setup process. It does not call for storage of your API keys while ensuring low latency overhead.

How does LLM Ops help optimize AI API costs?

LLM Ops optimizes AI API costs through a multi-step approach. It offers immediate visibility of your API usage and cost patterns via a single line of code. LLM Ops features an AI-powered recommendation system that uses these patterns to guide you towards decisions that save costs. Furthermore, the tool enables you to identify any cost spikes before they manifest in your invoice by analyzing and tracking every model, agent, and API call.

Which AI providers does LLM Ops track costs for?

LLM Ops tracks costs for several AI providers. Some of these include Anthropic, OpenAI, and Google's Gemini.

What is the process to integrate LLM Ops in my existing code?

The integration of LLM Ops into your existing code is simple and straightforward. It requires just the addition of two lines of code. This convenient process does not require any migration or adjustments to your existing apps.

Does LLM Ops store my API keys?

No, LLM Ops prioritizes user security and does not store any API keys. It is designed to execute secure operations by retaining only metadata related to the API usage.

How does LLM Ops maintain a low latency overhead?

LLM Ops maintains low latency overhead by adopting an efficient operation system that ensures the latency overhead is under 10 milliseconds. This mechanism promotes a smooth user experience while operating the tool.

Does LLM Ops access or store the actual data passed through the APIs?

No, LLM Ops does not access or store the actual content or data passed through the APIs. It is designed to uphold user privacy and confidentiality. LLM Ops focuses only on metadata related to API usage, including model names, token counts, timestamps, and calculated costs.

Can LLM Ops be used by big enterprises as well as startups?

Yes, LLM Ops is an adaptable tool that can be effectively used by organizations of all sizes. Whether it's a budding startup or a large enterprise, LLM Ops is designed to integrate into any existing code and provide a comprehensive solution for AI API cost management.

What does the LLM Ops recommendation system do?

The recommendation system in LLM Ops is engineered with AI technology that aids in making data-driven decisions. It analyzes the information on API usage and cost patterns to make optimization recommendations. This mechanism guides the users to cost-effective decisions.

What information does LLM Ops show in the detailed breakdown of spending?

The LLM Ops tool provides a comprehensive breakdown of spending. This includes details by model, agent, and individual API calls. The aim is to provide users with a full visibility of their API usage and spending.

Does LLM Ops require any changes or migration to my existing apps?

No, LLM Ops does not require any changes or migration to your existing apps. It is designed to integrate seamlessly with minimal alterations, requiring only the addition of two lines of code.

How does LLM Ops ensure secure operations?

LLM Ops ensures secure operations by not storing any API keys. Furthermore, it does not gain access to actual content or data passed through the APIs it tracks, adhering to a strict privacy policy. It retains only metadata, thereby maintaining the confidentiality of the user's API information.

Can LLM Ops help me detect cost spikes before they show in my invoice?

Yes, LLM Ops helps users detect cost spikes before they reflect in their invoice. By tracking every model, agent, and API call and providing real-time visibility of the AI API usage and costs, the tool can identify and alert about any unusual increases in spending.

What are the benefits of being an early user of LLM Ops?

Early users of LLM Ops get a host of benefits. They can lock in free access before the introduction of paid tiers, have their feature requests prioritized for development, receive direct support via Discord from the founding team, and moreover, they get to shape the product by influencing roadmap decisions.

How does LLM Ops help in making data-driven decisions?

LLM Ops assists in making data-driven decisions through its AI-powered optimization recommendations. By analyzing and tracking API usage and cost patterns, the tool provides valuable insights that guide users towards efficient and cost-effective choices.

What advantages does LLM Ops offer in tracking and optimizing costs related to AI platforms?

LLM Ops offers significant advantages in tracking and optimizing costs related to AI platforms. By providing a detailed spending breakdown by model, agent, and API call, it ensures cost transparency. Moreover, it helps to foresee cost spikes before they appear in your invoice, enhancing investment management. The tool doesn't store API keys ensuring data security and operates with low latency overhead enabling efficient usage.

What is the latency overhead maintained by LLM Ops?

LLM Ops maintains a latency overhead under 10 milliseconds. This promotes fast and efficient operation of the tool.

How does LLM Ops provide AI cost tracking and AI budget optimization?

LLM Ops provides AI cost tracking by monitoring costs across multiple AI providers and offering a detailed break down according to the model, agent, and individual API calls. It supports AI budget optimization with its AI-based recommendation system, which analyses cost patterns and suggests cost-saving decisions.

What is the process of AI platform integration in LLM Ops?

LLM Ops integrates AI platforms through a simple two-line code addition. It supports a variety of AI providers including Anthropic, OpenAI, and Google's Gemini, allowing users to track their costs effectively across these platforms.

What features does LLM Ops provide for expense management and cost efficiency?

LLM Ops comes loaded with features for expense management and cost efficiency. Its robust AI cost tracking mechanism allows users to keep a comprehensive check on their spending. The tool provides AI-powered optimization recommendations for better budget management. Furthermore, its real-time visibility and alert system help in detecting cost spikes, consequently avoiding unnecessary expenses.

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