Continuously monitor the key operational challenges in AI - data drift, outliers and model decay. Get a fast turnaround to real-time issues with explainability and model analytics to ensure business value is intact.Get Started
Hired layered Fiddler's Platform on its proprietary AI models to generate deeper insights into how its algorithms make decisions and eliminate any potential bias. This allows Hired's team to build trust with its algorithms and further its commitment to building a truly equitable future for tech talent from all walks of life.See the Case Study
Fiddler’s Explainable AI Platform enables companies to explain, monitor and analyze their AI solutions to drive successful AI deployments, build trustworthy and responsible AI systems, and bring transparency and positive business impact.
Fiddler's Explainable AI Platform unlocks the AI blackbox with continuous Monitoring and 360-degree Explainability. Get complete visibility into AI systems, understand the "why" behind AI predictions, and drive business impact with actionable insights from Explainable ML Monitoring.Get Started
Fiddler Labs recognized as a Cool Vendor by Gartner in the Cool Vendors in Enterprise AI Governance and Ethical Response.
AI in production is different and more complex than in training. Performance fluctuations can be staggering. Continuous model monitoring and Explainable AI help:
Find and solve data drift issues quickly to ensure end-users are well served
Understand the ‘why’ behind problems using explanations to efficiently root cause issues
Detect and address outliers and to ensure continued high-performance
The problem: complex AI systems are inherently blackboxes with minimal insight into their operation.
The solution: Explainable AI or XAI makes these AI blackboxes more like AI glass-boxes by enabling users to always understand the ‘why’ behind their decisions.
The benefit: Identify, address, and share performance gaps and biases quickly for AI validation and debugging.
Given the complex operational challenges in ML, like data drift and outliers, maintaining high-performance is difficult. Continuous model monitoring and Explainable AI help:
Efficiently solve operational challenges like drift, and outliers with always-on real-time ML monitoring.
Get deep model-level actionable insights to understand problem drivers using explanations and efficiently root cause issues.
Give data scientists immediate visibility into performance issues and resolve them before it results in negative business impact.
Responsible AI is the practice of building AI that is transparent, accountable, ethical, and reliable.
Culture of accountability: AI impacts lives, making it imperative that the system is governable and auditable through human oversight.
Ethics at the forefront: building responsibly means AI outcomes and predictions are ethical, fair, and inclusive.
Consistent monitoring: continuous real time monitoring of AI ensures precise and rapid error detection with insight into the ‘why’.
Trust: Explaining a black-box with another black-box does not establish trust. We ensure transparency through visibility.
Production-quality: Fiddler augments top AI explainability techniques in the public domain including Shapley Values and Integrated Gradients to enhance performance.
Enterprise scale: Our solutions are built at enterprise scale and power our industry leading explainability toolset for a robust and reliable experience.
Research-focused: Fiddler's paper 'Explanation Game' introduces confidence intervals and contrastive explanations - a significant upgrade to other Shapley Values implementations.
"At Hired, our mission is to match people with a job they love, and doing that at scale requires advanced technology like AI. Fiddler helps enhance our understanding of the AI algorithms at the heart of this candidate matching process by comparing these insights and explanations with our internally developed solutions to empower our data science and curation teams"