Our first step involves analyzing your company's current situation. Understanding the business and data requirements of the project is crucial to establishing quantifiable goals and their subsequent outcomes.
Once we have a clear context, we gather all relevant internal and external data for the AI implementation. Our team curates, cleans, and contextualizes the information to build a comprehensive data lake.
Now, the real fun begins. Our expert AI engineers develop a Proof of Concept (PoC). We define the project scope, tech stack, implementation methodology, software architecture, tools, and quality assurance requirements.
After developing the AI model, we deploy the first working version following the implementation methodology outlined in the previous step. We use this time to make necessary stabilization corrections, enhancements, and real-world testing.
Once the initial deployment is complete, we focus on integrating the AI model and start the self-learning and self-improvement process. We provide continuous support to ensure the project's goals are met.