We envision a future where AI systems are not just powerful but inherently trustworthy, fostering confidence and ethical governance across all enterprises and public sectors. Our mission is to illuminate the complex workings of AI through comprehensive observability, making every decision and outcome transparent, understandable, and fair.
By pioneering advanced AI observability technologies and responsible AI frameworks, we empower organizations to detect bias, monitor model performance, and manage AI risks proactively throughout the entire machine learning lifecycle. We believe that true innovation arises when AI systems are held to the highest standards of accountability and ethical stewardship.
Through cutting-edge tools and human-centered approaches, we are building the infrastructure for a future where AI deployment is secure, explainable, and aligned with societal values—unlocking new potentials for industries and governments to harness AI confidently and responsibly.
Our Review
We've been tracking the AI governance space for a while now, and Fiddler AI keeps popping up in conversations about responsible AI deployment. After digging into their platform, we can see why they're gaining traction with enterprise customers who need more than just "black box" AI solutions.
What started as Krishna Gade's frustration with opaque ML systems at Facebook has evolved into a comprehensive AI observability platform. The founding story resonates—anyone who's tried to explain why an AI model made a particular decision knows the pain point Fiddler is solving.
What Makes Them Stand Out
Fiddler's approach to AI observability is refreshingly comprehensive. While many companies focus on either monitoring or explainability, Fiddler tackles the full spectrum: model performance tracking, bias detection, security monitoring, and actual interpretability tools like Shapley values and their proprietary Fiddler Shap method.
We're particularly impressed by their human-in-the-loop capabilities. For mission-critical applications—think government agencies or financial institutions—having humans verify AI decisions isn't just nice-to-have, it's essential for maintaining trust and compliance.
The Customer Base Tells a Story
Here's what caught our attention: Fiddler isn't just serving typical tech companies. They're working with government agencies on national security applications and financial services firms dealing with regulatory scrutiny. That's not an easy customer base to crack—it requires serious security chops and proven reliability.
The fact that In-Q-Tel (the CIA's venture arm) invested in them speaks volumes about the platform's enterprise readiness. These aren't customers who take risks on unproven technology.
Room for Growth
With $63.2 million raised and only 86 employees, Fiddler appears well-capitalized for their current stage. However, the AI governance market is heating up fast, and they'll need to stay ahead of both established players and well-funded newcomers.
Their $12.2 million in annual revenue suggests solid traction, but scaling enterprise sales in this space requires significant investment in both technology and go-to-market efforts. The good news? They're addressing a real pain point that's only getting more critical as AI adoption accelerates across industries.
Feature
Model Monitoring: Continuous tracking of ML and large language models performance, fairness, and security in production
Explainable AI: Techniques such as Shapley values, Integrated Gradients, proprietary methods for interpreting model decisions and bias detection
Bias Detection & Responsible AI: Real-time bias and fairness monitoring with alerts, root cause analysis, and actionable insights
Security & Compliance: Monitoring AI risks including biases, model drift, and regulatory compliance
Human-in-the-loop capabilities for mission-critical AI decisions
Jobs
FAQs
Fiddler AI
