Stop guessing costs. Start tracking LLM performance.

Are you struggling to keep track of costs and performance in your AI/ML workflows? Many teams face challenges in understanding the intricacies of their large language model (LLM) operations.

The problem this solves

In the fast-paced world of AI/ML, tracking performance metrics can feel overwhelming. Teams often find themselves guessing about costs, latency, and resource usage, leading to inefficiencies. For example, without clear visibility into token usage or latency, you might overspend on cloud resources or experience unexpected delays in deployment. These issues can hinder your ability to make informed decisions about scaling and resource allocation.

What Spanlens does

Spanlens provides open-source LLM observability, allowing you to log costs, latency, tokens, and agent traces. This transparency leads to better management of your AI/ML workflows. With Spanlens, you gain insights that help you optimize your operations and reduce unnecessary expenses.

What you get out of it

• Clear visibility into costs. Track your spending on cloud resources in real-time, allowing you to adjust your budget effectively.
• Reduced latency. Identify bottlenecks in your model’s performance and address them promptly to improve user experience.
• Accurate token tracking. Monitor token usage to avoid unexpected charges and ensure efficient resource allocation.
• Detailed agent traces. Understand the performance of individual agents within your models, leading to better debugging and optimization.
• Open-source flexibility. Customize the observability tools to fit your specific needs, enabling you to adapt as your projects grow.

Who it's for (and who it isn't)

Spanlens is designed for AI/ML engineers, data scientists, and product managers who need to track and understand their LLM performance. If you work in a team that relies on large language models and seeks to manage costs effectively, Spanlens is for you. However, if you are not involved in AI/ML workflows or do not require detailed performance tracking, this tool may not be relevant to your needs.

Getting started

To begin using Spanlens, visit Spanlens and explore the open-source tools available. You can also check out the listing on SubmitHunt for community insights and feedback.

Bottom line

Spanlens offers essential observability for your LLM workflows, helping you track costs and performance with clarity. For teams looking to enhance their AI/ML operations, the first step is to get started with Spanlens.