Streamlining LLM Cost Analysis and Monitoring
Our customers put together LLM-powered workflows that they either use for automations or as part of their core infrastructure. We essentially encapsulate all the AI parts of their product into our platform, into a single API call.
— Tal Globus, Founding Engineer, Wordware
The Challenge: Understanding Costs and Performance at Scale
Wordware builds a no-code platform that enables companies to create AI-powered workflows without writing code. As their customer base expanded, they faced increasingly complex challenges tracking and analyzing LLM usage across thousands of customer "flows":
1. Cost Attribution and Analysis
When customers asked "How much did this particular set of runs cost?", Wordware's team struggled to efficiently aggregate costs across multiple workflow runs. With numerous flows accessed by both humans and APIs, understanding the precise cost of specific customer usage became critical but challenging.
2. Limited Visibility Into Usage Patterns
The team needed deeper insights into how customers were utilizing their platform, but found it difficult to analyze patterns across thousands of requests flowing through their system. Identifying trends and optimizing performance required better data organization.
3. Insufficient Data Aggregation Tools
Without adequate tools, Wordware's team resorted to manually downloading CSV files and writing custom scripts to parse JSON data. This time-consuming process diverted valuable engineering resources from product development.
The Impact of Better Observability
We use [Helicone] all the time. I find your team awesome and everyone else here really appreciates what your team does. You're top of the line.
— Tal Globus, Wordware
Implementing Helicone's observability platform transformed Wordware's ability to track and analyze their LLM usage. The comprehensive data collection provides visibility into every aspect of their AI workflows, from costs to performance metrics.
This visibility is critical for two of Wordware's most common use cases: cost analysis and prompt debugging. Whether it's calculating customer usage costs or investigating unexpected LLM outputs, Helicone provides the data they need to support their customers.
Impact and Efficiency
Helicone's platform has become foundational to Wordware's operations, providing the observability and analytics they need to support their customers while continuously improving their AI-powered workflow platform.
| Before Helicone | With Helicone |
|---|---|
| Manual calculation of workflow costs by downloading and processing CSVs | Centralized visibility of all LLM calls and associated costs in one platform |
| Limited insight into which prompts were used in specific workflow runs | Ability to filter and search through requests to identify specific runs or patterns |
| Difficulty correlating LLM calls with specific customer workflows | Organization-level filtering to focus on specific customer data |
| Time-consuming process to gather metrics for customer inquiries | Faster access to key metrics through the dashboard and request filtering |
Bring Clarity to Your LLM Workflows
Want to track and analyze your AI agent processes like Wordware? Try Helicone free today and see how our observability tools can transform your development workflow.
