Puddl
Puddl: LLMOps Tool for Prompt Engineering & Cost Tracking
Puddl is an LLMOps platform that helps teams track OpenAI costs, refine prompts, and analyze LLM requests to build smarter, more cost-efficient AI workflows.
Overview
Puddl is a purpose-built LLMOps tool that gives prompt engineers and AI developers deep visibility into how their LLMs are performing and what they're costing. Instead of guessing at spend or manually testing prompts in scattered notebooks, Puddl centralizes cost tracking, detailed breakdowns, currency localization, and model-wise spend reporting so teams can see exactly where their budget is going and identify opportunities to optimize.
Beyond cost control, Puddl includes a sleek playground for crafting and testing prompts, complete with history logging and annotation capabilities. This makes it easy to iterate on prompt design, compare outputs, and keep a searchable record of what's worked and what hasn't. Paired with deep analytics for organizing and tracking requests across multiple deployments, Puddl turns fragmented LLM experimentation into a structured, data-driven workflow.
Whether you're a solo developer trying to keep OpenAI bills in check or a data science team managing requests across several projects, Puddl acts as a control center for your LLM operations—combining financial oversight with the creative tooling needed to build better prompts faster.
Capabilities & Features
- LLMOps
- Prompt engineering
- OpenAI
- Cost tracking
- LLM analytics
- Prompt playground
- Python library
Core Features
- OpenAI cost tracking with detailed breakdowns and currency localization
- Model-wise spend analysis to compare costs across different LLMs
- Prompt playground for real-time prompt creation and testing
- Request history and annotation tools for tracking iterations
- Deep analytics for organizing requests across multiple deployments
- Python library for programmatic LLM request tracking
Use Cases
- Monitoring and reducing OpenAI API spend across projects
- Iterating on and refining prompts in a dedicated testing environment
- Auditing historical LLM requests with annotations for team collaboration
- Comparing costs across different models to choose the most efficient one
- Centralizing analytics for LLM usage across multiple deployments
Best For
- Prompt engineers
- LLM developers
- AI researchers
- Data scientists
- Startups managing OpenAI API budgets
Pros
- •Free cost tracking makes budget oversight accessible from day one
- •Model-wise spend breakdowns help pinpoint the most cost-efficient LLMs
- •Integrated playground streamlines prompt creation and testing in one place
- •Annotation and history features support better team collaboration and auditing
- •Python library enables seamless integration into existing development workflows
Cons
- •Currently appears focused primarily on OpenAI, which may limit multi-provider flexibility
- •No publicly listed paid tiers, making it unclear how the tool scales for larger enterprise needs
- •Deep analytics features may require some onboarding time to fully leverage
- •Browser-based key storage may raise questions for teams with strict security policies
How to Use
1. Sign up for a free Puddl account. 2. Connect your OpenAI API key (stored securely in your browser) to start tracking costs automatically. 3. Review cost breakdowns and model-wise spend insights to identify savings opportunities. 4. Use the built-in playground to create and test prompts. 5. Install the Python library to send LLM requests programmatically and automatically log history and annotations. 6. Dive into deep analytics to organize and monitor requests across all your deployments.
Frequently Asked Questions
Connect & Contact
Pricing
Puddl offers free OpenAI cost tracking with no publicly listed paid tiers at this time.
Pricing data is provided as a summary. Visit the vendor website for full tier details.