Make your ML models explainable with conversational AI
Stop struggling with black-box ML models. Our AI assistant helps you understand, explain, and trust your machine learning predictions through natural conversation. No coding required.
Why choose Explainability Assistant?
Natural conversation
Ask questions in plain English or other languages. No need to learn complex APIs or write code to understand your models.
Deep insights
Get feature importance, counterfactual explanations, and what-if scenarios to understand model behavior.
Enterprise ready
Deploy on-premises or in your cloud. Your data never leaves your infrastructure. You are in control of all AI providers and your data.
Example use cases
Healthcare
Explain medical diagnosis predictions, understand risk factors, and ensure regulatory compliance.
Energy
Optimize energy consumption predictions, identify key factors, and improve efficiency.
Transportation
Understand traffic predictions, optimize routes, and improve safety models.
See it in action
Watch how Claire, our AI assistant, helps you understand your ML models through natural conversation.
Built for privacy & reliability
Your data never leaves your infrastructure
Deploy on-premises or in your private cloud. Complete privacy with full control over all AI providers and no external data transmission.
Function-based architecture
Pre-defined functions prevent AI hallucinations and ensure deterministic, reliable explanations. JSON-specified functions with Python back-end execution.
REST API integration
Easy integration with existing systems. Standard REST API allows multiple front-ends and seamless integration with your current workflow.
How it works
Integrate your data
Start by adding your tabular dataset in CSV format and your trained Machine Learning model (e.g., scikit-learn model saved as a pickle file). The system will automatically analyze and prepare your data for exploration and explanation.
Select your AI model
Choose from multiple Large Language Model providers including Google, OpenAI, or Hugging Face. You can switch between different models at any time to find the one that best understands your domain.
Start exploring
Begin a conversation with the AI assistant to explore your data and model predictions. Ask questions about specific features, individual predictions, or request explanations for how your model makes decisions.
Deploy securely
Deploy the solution to your preferred environment or run it locally on your infrastructure. Your sensitive data remains completely private with full control over all AI providers and no external data transmission.
Frequently asked questions
What data formats are supported?
Generally, any tabular data format is supported. You need to provide a CSV file and a pickle file for the Machine Learning model.
Is my data secure?
Absolutely. You can deploy on-premises or in your private cloud. Your data never leaves your infrastructure and you are in control.
Do I need coding skills?
No! Our conversational interface lets you explore your models using natural language. No coding required, but you can also integrate over API.
Which LLM models are supported?
We support OpenAI, Google, and Hugging Face providers with models like Gemini, Llama, GPT, and more. You can switch between models anytime.
Ready to make your ML models explainable?
Join researchers and practitioners who are already using Explainability Assistant to build trust in their ML models. You can get access to an interactive demo or request a consultation to see how it can help your organization.
