AI integration review
Review of where and how AI fits a product or business — model choice, guardrails, data readiness, cost — delivered as a whitepaper with an adoption roadmap.
What we build
For businesses that know AI matters but not where it genuinely helps. We examine your operation, data, and systems, then deliver a whitepaper mapping where AI would pay for itself and where it wouldn't, what your data can support today, and a prioritized adoption roadmap with guardrail recommendations. Choose this before committing money to any AI build. If you already know what you want built, go straight to that AI build service; if the question is whether the AI you have is good enough, choose the LLM evaluation suite.
What you get
- An AI-integration review whitepaper covering each candidate use case
- An opportunity map scoring each candidate use case on value and effort
- A data readiness assessment stating, per use case, whether current data supports it
- An adoption roadmap sequencing the recommended use cases
- A guardrail specification naming, per use case, where a human must review the output
How the work unfolds
- Map where AI genuinely helps the operation
- Assess feasibility, cost and risk per use case
- Design the trust boundaries for model output
- Write the AI-integration whitepaper
What shapes the price
Before you see a number, our scoping conversation asks:
- Roughly how many places in the business do you think AI might help? The assessment is per use case; the activity is literally named that way.
How an engagement starts
Teams often combine it with: