The best LLM analytics
Request Logs, Error Logs, Function Calling, Bug Reporting, Prompt Versions,
LLM Model Comparison, Sentiment Analysis, Personal Info Leakage Catcher, and more
Use cases
How many prompt and function calling changes do you test each day?
Can you ask team members for feedback? How do you retrain your models?
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Function Calling
Understand how function calling is used in order to validate, improve or change your approach.
Prompt Feedback
With the user feedback, you can enable users to vote for each response as 👍, 👎, or ❤️ and leave comments for improvements.
Model Comparison
You can see if GPT-4 performed better or worse in terms of latency and cost vs GPT-3.5-turbo.
JSON Export for Re-training
You can download selected prompts by certain tags or namespaces and use them to fine-tune and retrain the models.
Error logs and debugging
“A month ago, a colleague recommended GPTboost. I connected the tracking, and then totally forgot about it.
A week ago I was debugging an app for several hours, when I remembered GPTBoost had error logs, which might help. I logged in, found the errors and that literally saved me hours of work! Now I use GPTBoost almost daily and it also helps me with pricing alatency.”
G.A.
Data scientist
Meet the Annotation Agents
Build your army of AI Annotation Agents or use the pre-configured ones to analyze chat communication and get insights for re-training your LLM apps.
Sentiment Analysis
Want to know if your users are frustrated before or after interacting with the AI chatbot?
Activate the Sentiment Analysis agent to find out how users feel. Then work towards improving their experience.
No Answers
If response accuracy is crucial for your LLM app, and hallucination temperature is at 0, some requests might be left without an answer.
But are you tracking them?
Now you can track them with the 'No Answer' agent.
Privacy Officer
Is it possible for your LLM app to encounter or request sensitive personal information from customers?
Use the Privacy officer AI agent to detect and prevent sensitive data exposure.
Up and running with GPTboost in 5 minutes
Effortless Setup
One line of code is all you need to integrate GPTboost
Free for Life Package
Choose from a range of packages starting with Freemium for life
Versatile Integration
Our platform smoothly integrates with your preferred tool
How do I get started?
Step 1: Create an Account
Create an account at GPTboost. Google account login is available.
Step 2: Authorize a Key
Add an OpenAI API key at
GPTboost.
Step 3: Add Code
Add the GPTboost code snippet to your app. You will soon see data on the dashboard.
F.A.Q.
What is GPTboost?
GPTboost is a SaaS tool for apps using OpenAI API. By adding a simple code snippet to your LLM app, GPTboost empowers you to monitor your LLM usage, incl. Function Calling, Version Controls, AI Response Feedback, History and Debug Logs, GPT Model Comparison,. These insights will help you improve your app performance and overall user experience, which in turn can lead to better business results.
Can I use GPTBoost with the LangChain framework?
Yes, you can absolutely use GPTBoost with LangChain. Add one line of base_URL code to your LLM app and you will be able to use both LangChain and GPTBoost functionalities.
Can I use GPTBoost with LiteLLM by Vercel?
Yes, you can use GPTBoost with LiteLLM. Add one line of base_URL code to your LLM app and you will be able to use both LiteLLM and GPTBoost functionalities. We'll soon be announcing the release of out LiteLLM integration to make it even easier to use GPTboost analytics with LiteLLM.
Can I use GPTBoost with Azure OpenAI?
You can use GPTBoost with your Azure-OpenAI deployment, and it requires no additional code changes beyond replacing the Azure endpoint with the GPTBoost URL. Check Azure integration documentation for more detail
Can I do Sentiment analysis with GPTBoost?
Yes, with the Annotation agent tools we recently added in GPTBoost, you can run sentiment analysis on top of user requests, mark them accordingly and analyze only the ones that matter to you in order to improve your prompts. You can use our "Sentiment Analysis" agent or create a custom one on your own.
Can I use GPTBoost if I am building Customer Support AI app?
Yes, majority of our clients are building customer support apps based on LLM models and GPTBoost tools are optimized for this use case:
· You have logs of the chat communication
· You can activate feedback functionality
· You can use Annotations Agents to automatically analyze aspects of the AI implementations
· Bug reposting features are also available
· And downloads in JSON format allows for easier model retraining
We'll be happy to hear your feedback and add more features, which you need - reach out via chat or contact form.
What if user prompts or generated responses contain personal data (PII)?
GPTBoost Omit Logging feature will take care of that. You have the option to hide either the prompot, or the response, or both. Check documentation on omit logging for more details.
You can also activate Privacy Officer or another custom Annotation Agent to monitor and notify you in case of PII leakage.
How does GPTBoost compare to other tools?
Here are some of the GPTBoost tools, which our users love and prefer us over similar SaaS products:
· User feedback API
· Bug reporting
· Prompt and function call progress tracking
· Data export in JSON for model retraining
· NEW: Sentiment analysis annotation agent
· NEW: Annotation agent for chats without answers
· NEW: Privacy leakage tracker
· and more.
We put our customers needs first and work closely with developers building their OpenAI/Chat GPT apps. GPTBoost is a collaborative solution that will help your whole team speed up development and go from POC (proof of concept) to a fully functional product in no time.
What LLMs do you support?
Currently, GPTBoost supports OpenAI and Azure OpenAI. We're working on adding support for other LLMs incl. Bard, Claude, LLaMA and more. Send us a note at hello@gptboost.io to let us know which models you would like us to prioritize for you.
Can I store the data on my own server?
Yes, storing data on your own server is possible. Please contact us for details.
Coming up in GPTBoost
Image Analysis with AI
Would you like to use AI to interpret and annotate visual data? Would you like to be able to tag your images or identify if certain objects are present in them or not?
To see Image Analytics features in GPTBoost sooner rather than later, click the link below and vote!
Text Analysis with AI
You have tons of user-generated information, but you have no way to analyze and use it in raw format.
With AI text analysis you can turn this data into valuable insights:
· Sentiment analysis
· Key phrase extraction
· Named entity recognition
· Language detection
Testing for GPT Models
LLMs are not deterministic - even small changes in the GenAI algorithms may lead to outcome deterioration. Or your model might be under data poisoning attack.
If you want to make sure your users have the same experience with your LLM app over time, there is no other way, but to run tests of the model on a regular basis and compare the results.
LiteLLM Integration
LiteLLM by Vercel calls 100+ LLMs using the same Input/Output format. Are you already using it? Would you like to have GPTBoost as a native LiteLLM integration?
Fill in the form below to prioritize GPTBoost -LiteLLM integration.
