Back to blog home

We’re Excited to Be a Part of the AI Infrastructure Alliance as a Founding Member

We’re now a part of the AI Infrastructure Alliance as a core member! This partnership of 25 AI companies creates a more collaborative environment for companies and communities in the artificial intelligence (AI) and machine learning (ML) space.

Partnerships in the Alliance will help create a Canonical Stack for AI, by driving strong engineering standards and creating seamless integration points between various layers of the AI infrastructure ecosystem. Canonical means "a set of rules, standards and principles by which something is judged,” and a Canonical Stack (CS) for AI will set the standard for how enterprises develop and design machine learning models at scale. It will let data scientists and data engineers move up the stack to solve more complex, higher order problems, instead of reinventing the wheel on every data science project.

Core founding members include Algorithmia, CometML, DAGsHub, Determined AI, Fiddler,, Pachyderm, Tecton, and more. These companies have raised over $200M in collective venture capital funding from top firms including Andreessen Horowitz, Benchmark, Gradient Ventures, GV, Lightspeed Ventures, Lux Capital, and Sequoia Capital.

The AI and ML space currently lacks a standard set of tools and solutions, blocking data science teams from sharing their work and collaborating across the world. Rather, there is wild proliferation of proprietary, cloud lock-in solutions that benefit individual companies, but not the data scientists and engineers building the AI applications of today and tomorrow. The Alliance came together to help those data science teams break out of lock-in so they can build on top of a standardized, open platform that works across all of their environments.

Fiddler was founded in October 2018 by CEO Krishna Gade and CPO Amit Paka, with the mission of making AI trustworthy for all enterprises. Gade and Paka believed that there was a need for a new kind of Explainable AI Platform that would enable organizations to get ahead of key issues around AI operationalization and lack of transparency within AI systems. 

Since the launch of Explainable Monitoring Solution last year, Fiddler gathered insights from customers that one of the problems with the current ML workflow is that there is no feedback loop to monitor and control the performance of the ML models. “We argue that this lack of feedback control makes production AI apps more error prone. Because of the increased model complexity, split world of Offline vs Online, and the lack of feedback loop, we are seeing ML Operations struggle with the following challenges,” said Krishna. He continued that “ML Workflow is being operated today like an open-loop system, instead we need to create a feedback control loop and make it a closed-loop system to solve the ML Operations challenges. Therefore we propose a new framework: Machine Learning Model Performance Management framework.

“A Model Performance Management (MPM) framework is a centralized control system at the heart of the ML workflow that tracks and monitors the model performance at all the stages and closes the ML feedback loop,” said Krishna. Amit added that “Like APM, MPM provides ML teams with real-time visibility into the underlying operational health along with support for troubleshooting production issues. Continuous monitoring is especially critical for machine learning which is generally applied to key business use cases given the higher cost of ML operations.”

Fiddler’s latest update will support the ML MPM framework, enabling users to capture data dynamics, model dynamics, and iterative process dynamics in MLOps to further optimize AI applications more efficiently. With the industry-leading Explainable AI powering the ML MPM framework, users will be able to build more reliable, transparent, and ethical AI.

About Artificial Intelligence Infrastructure Alliance

The Artificial Intelligence Infrastructure Alliance (AIIA) is a consortium of leading artificial intelligence startups with a mission to help every company realize the infinite potential of AI. Formed in February 2021, the Alliance is focused on tying together the complex web of existing AI technologies into a single Canonical Stack, providing the infrastructure on which any company—from tiny startups to global enterprises—can run impactful AI projects. To learn more about the AIIA or to become a member, visit