Introducing

Explain & Align mission-critical AI

For use cases, where transparency, reliability and accuracy matters, AryaXAI provides state of the art components to Explain & Align your mission-critical AI models.

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Platform Feature

EXPLAIN

Highly accurate, stable and reliable explanations for your mission-critical solutions

Enabling reliable and explainable models

Transparency

Compliance

Pruning

Acceptability

DL- Backtrace

Pioneering Model Explainability

Introducing ‘DL-Backtrace’, a new XAI technique to deliver highly accurate, stable and faithful explanations for any deep learning model.

LLMs

Text Classifications

Function calling

Chat completion

Image generation

Image classification

Predictive modelling

Image segmentation

Summarization

91%

Image data

better faithfulness values as compared to SmoothGrad, IG or  GradCam

88%

Text/LLMs

Better in delta MoRef and LeRF compared to GradCam for transformer models

18%

Tabular data

Better MPRT values as compared to SHAP and 40% better as compared to LIME

Research Paper

November 20, 2024

DLBacktrace: A Model Agnostic Explainability For Any Deep Learning Models

Text Translation using T5

Translation using the T5 (Text-to-Text Transfer Transformer) small model is an NLP task where the model converts text from one language to another. T5 frames translation as a text-to-text generation problem.

Text Translation

Text Summarization using T5

Text summarization using the T5 (Text-to-Text Transfer Transformer) small model is a natural language processing (NLP) task where the model generates concise summaries of input text. T5 is a transformer-based model developed by Google that treats every NLP problem as a text-to-text task.

Text Summarization

Object Detection (Example 2)

Objection detection is one of the key use cases for CV. The job requires to detect the objects and coordinates in a given image. In this image, we. are showing the examples for single object detection. The same can be expanded to multiple objects.

Object Segmentation

Object Detection (Example 1)

Object Segmentation

Object Segmentation on ClinicDB

For object segmentation, we are using U-Net model trained on ClincDB data. For this example, we are showing benchmarking of DL Backtrace (Default Mode), DL Backtrace (Contrastive Positive & Negative modes) & GradCam

Object Segmentation

Object Segmentation on CamVid

For object segmentation, we are using U-Net model trained on CamVid data. For this example, we are showing benchmarking of DL Backtrace (Default Mode), DL Backtrace (Contrastive Positive & Negative modes) & GradCam

Object Segmentation

Supports multiple OSS & experimental XAI methods, out-of-the-box

OpenSource (OSS) XAI models

AryaXAI supports multiple traditional explainability methods like SHAP, LIME and other traditional models as out-of-the-box.

LIME

CEM

SHAP

Integrated Gradients

Simplified Gradients

Similar cases as explanations

Compare current data points to previously encountered patterns. Inspired by prototypes as explanations, this method provides clear, relatable insights, making model decisions more intuitive and understandable.

Observations as explanations

AryaXAI supports multiple traditional explainability methods like SHAP and others traditional models.

Explainability Evals

For use cases that needs accurate and true-to-model explainability, AryaXAI offers multiple evals to validate XAI techniques to pick the best for your data and models.

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How we support

Scale as you go 🚀 !

Run ML workloads serverlessly with AryaXAI’s FaaS components, eliminating infrastructure management. Scale dynamically without being tied to specific infrastructure.

Localize your ML workloads to dedicated instances across any cloud, easily scale or migrate between servers with a click, ensuring flexibility and seamless cloud management.

Deploy your ML models fully in your own public/private cloud or on-premise data center, ensuring complete control, security, and customization for your infrastructure needs.

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Unlock more resources on AI Governance

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Article

Explainability (XAI) techniques for Deep Learning and limitations

Videos

On-demand webinar: AI Broadcast Series #1 - What's next after ChatGPT in Banks, Insurers and financial services?

Whitepaper

AryaXAI: Accelerating the path to ML transparency

Article

Decoding the EU's AI Act: Implications and Strategies for Businesses

DLBacktrace: A Model Agnostic Explainability For Any Deep Learning Models

Research paper

November 20, 2024

Is Explainability critical for your 'AI' solutions?

Schedule a demo with our team to understand how AryaXAI can make your mission-critical 'AI' acceptable and aligned with all your stakeholders.

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AryaXAI provides the most accurate explainability and alignment stack to deliver accurate, true-to-model explainability, monitoring, risk management, and alignment techniques essential for highly mission-critical or regulated AI solutions.

Products

Explainable AI ML Monitoring ML Audit Policy Control Pricing

Resources

Articles Videos White papers Research paper Podcasts Events Wikis

Company

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