Flint collaborates with LAB’S 214, a strategy, product, and service design studio,
to offer you a pragmatic approach that efficiently takes you from ideation to production.

Phase 1: Exploration

Based on the expected impacts as well as the real benefits of the selected Use Cases, this first step points you in the right direction.
The exploration phase is composed of 2 stages: ideation followed by AI/Data design sprint(s).

We’ve set up a multidisciplinary team consisting of a Product Strategist and a Data Scientist. These two experts address the entire decision-making process. They provide expert guidance and support as you explore the opportunities that Data Science and Artificial Intelligence can bring to your business.

STEP 1 : IDEATION
‍
Starting from a realistic technical solution, a successful Data Science / AI Use Case should respond to a strategic need that unfolds into an operational reality. This ideation phase allows you to discover and select the most relevant ideas to prototype.

STEP 2 : AI / DATA DESIGN SPRINT(S)

The AI / Data Design Sprint aims at accelerating and streamlining the prototyping of a Use Case, ensuring that the final need is met as quickly as possible and that everything is in place for its successful execution.
This second step enables business departments to gain a clear understanding of the potential value of the Use Case as well as the amount of work required to turn it into a finished product.

NEXT ITERATION

At the end of an AI / Data Design Sprint, business departments face 3 different alternatives, depending on the results:

• Keep deep diving into a particular Use Case that would appear promising;
• Carry on with the same use case, using a dynamic approach to address it in the best possible way;
• Switch to another, more promising, Use Case while keeping in mind the lessons learned along the way.

Phase 2: Industrialization

The exploration phase ends up teaching you whether the Use Case can (and should) be pursued next to the industrialization phase.
This second phase is composed of 3 key steps:

• Architecture: Collaborative workshops to determine the best platform for hosting the target solution, as well as suitable technological choices;
• Design Sprint(s): Iterative prototyping workshops aimed at finding the best UX/UI to make your data actionable and usable in production;
• Project Sprint(s): Implementation and industrialization of validated Use Cases, with a focus on development quality and the fastest time-to-market.

Choosing Flint and Lab’s 214 expertise means