Applied Generative AI with Proof of Concept
Goal: To validate a specific Generative AI use case by developing a functional proof of concept (PoC). This engagement moves beyond theory to build a tangible asset that demonstrates the value of a selected Large Language Model (LLM) with your organization's data and security requirements.1
“Industrialization is the process of scaling up: the transformation of a prototype into a repeatable and optimized process for large-scale production.”
How It Works
The Applied Generative AI with Proof of Concept is a 6–10 week engagement that transforms a validated use case into a functional prototype, tailored to your data, systems, and security needs.
Phase I: Discovery and Architectural Design
We conduct in-depth technical sessions to define the precise scope of the use case, analyze source data, and evaluate candidate LLMs. This phase concludes with a formal recommendation for the PoC architecture.
Phase II: Proof of Concept Development
Phase III: Implementation & Scaling (Optional)
Our team proceeds with the iterative development and testing of the selected model(s), integrating them with specified third-party or proprietary data. The focus is on demonstrating core functionality and assessing performance.
Following a successful PoC, the engagement can be extended to refine the model, deploy the supporting infrastructure into a production environment, and finalize the solution for operational use.