Introducing

Quality Control for AI

We are on a journey to help data scientists, engineers & business experts work together to create better AI models.

We are building a visual quality management platform for AI models, from prototype to production.

Quality issues cause waste in AI pipelines

1

Prototype

Assessing data & model quality requires time & cross-team collaboration

Data scientists spend a lot of time explaining the value of their work to business experts

Business experts have no simple way to verify models created by data scientists

2

Deployment

Prototypes rarely meet software engineering quality standards

IT/ML engineers aim for secure and well-tested AI models

Data scientists have a hard time satisfying IT requirements

Business experts wait for deployment, and are kept out of the loop

3

Production

Unexpected bugs & biases appear, requiring constant maintenance

Users lose trust in the product using faulty AI models

IT engineers are not equipped to identify and correct AI bugs

Data scientists & ML engineers are overwhelmed by maintenance tasks

A unified quality management platform for all stakeholders, from prototype to production

Prototype

Inspect

Beta available

Enable business experts to inspect AI models visually to find bugs & give feedback to data scientists

Deployment

Test

Automate testing of AI models by ML engineers, data scientists & business experts with functional, technical & statistical tests

Production

Monitor

Give ML engineers & data scientists actionable alerts on bad model behaviors in production

+ AI quality training, audit & certification services

Our Vision

Take back control of your AI

Quality control is not a regulatory requirement. It is a competitive advantage. It is an opportunity for you to increase and secure the business value of your AI investments:

Increase the performance of your AI models
Mitigate the risks of AI incidents
Build trust with transparency-demanding customers

We are inspired by quality standards from mature industries: manufacturing, finance, software engineering. We want to partner with you to bring AI into adult age.

Team

We are data scientists with experience in real-life AI applications.
We explore the interplay between software, people & business problems.
We believe in good engineering and useful products.

Alex Combessie

Co-Founder & CEO

Worked 5 years at Dataiku as Data Scientist & ML Software Engineer
Helped democratize AI for technical and business users in the enterprise world
Worked in strategy consulting and finance at Capgemini, EY & Natixis
Graduated from Ecole des Ponts, ENSAE ParisTech & the University of Toronto

Jean-Marie John-Mathews

Co-Founder & CPO

Finishing Ph.D. in AI Ethics at Paris Saclay & Institut Mines-Télécom
Coordinator of the Good In Tech institute
Worked as a Data Scientist at Thales & Capgemini
Graduated from ENSAE ParisTech, Sciences Po, Paris School of Economics & Sorbonne University

Want to join?

Visit our jobs page

Passionate about building robust solutions to real-life problems
Driven by customer needs & outstanding user experience
Hungry for learning new skills every day
Conscious about technology's role in our society
Empathetic team player

Introducing

Quality Control for AI

Quality issues cause waste in AI pipelines

1

Prototype

2

Deployment

3

Production

A unified quality management platform for all stakeholders, from prototype to production

Prototype

Inspect

Deployment

Test

Production

Monitor

+ AI quality training, audit & certification services

Our Vision

Take back control of your AI

Team

Alex Combessie

Jean-Marie John-Mathews

Want to join?

Let's get in touch

hello@giskard.ai