Question 1

What is the difference between a PoC and an MVP?

Accepted Answer

A Proof of Concept (PoC) is built to verify technical feasibility—proving that the AI can actually solve the specific problem with your data. A Minimum Viable Product (MVP) goes a step further; it is a basic but polished version of the product that can be released to a small group of actual users to validate business value.

Question 2

How long does an AI PoC take?

Accepted Answer

We strictly timebox our PoCs to 4–6 weeks. This constraint forces us to focus purely on the core AI hypothesis without getting distracted by unnecessary features. If it takes longer than 6 weeks, it's a project, not a PoC.

Question 3

What do we need to provide to start?

Accepted Answer

The most important asset is your data. We need a representative sample of the data the AI will encounter in production (e.g., 500 past customer emails, a set of product PDFs, or historical sales data). We also need access to domain experts in your team who can judge the quality of the AI's output.

Question 4

Will you build the PoC from scratch or use APIs?

Accepted Answer

For speed and cost-efficiency, we almost always use managed APIs (like OpenAI, Anthropic, or AWS AI Services) during the PoC phase. The goal is to prove the concept works. Once proven, we can discuss training custom open-source models for the final production version to reduce costs or increase privacy.

Question 5

What happens if the PoC fails?

Accepted Answer

A 'failed' PoC is actually a successful outcome—it prevents you from spending hundreds of thousands of dollars on a full product that wouldn't have worked. We provide a detailed autopsy explaining why it failed (usually due to poor data quality or current limitations in AI reasoning) so you can adjust your strategy.

Question 6

Can the PoC code be used for the final production product?

Accepted Answer

Parts of it, yes. The prompt engineering, evaluation metrics, and core logic often transfer. However, PoCs are built for speed, often using tools like Streamlit. For production, we will rewrite the backend into a robust microservice (FastAPI/Node.js) and implement proper security, caching, and rate-limiting.

Question 7

Do we own the intellectual property of the MVP?

Accepted Answer

Yes. Upon completion and full payment of the PoC/MVP phase, you retain full ownership of the custom code, prompts, architectures, and fine-tuned models we develop specifically for your project.

Question 8

How do you measure if the AI is accurate enough?

Accepted Answer

We define 'ground truth' datasets during Step 1. We run the AI against this dataset and score it using metrics like Precision, Recall, or LLM-as-a-judge frameworks. We don't rely on 'it looks good'; we provide hard statistical evidence of the AI's performance.

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