Start with a business problem that AI can help solve
An AI project needs a measurable task and a baseline for comparison. Unbroken Technologies helps assess use cases such as searching internal documents, assisting support teams, extracting structured information and forecasting from historical data. We examine whether rules, traditional software, a trained model or a language-model integration is the most appropriate approach before proposing implementation.
Data readiness and responsible access
Useful AI depends on relevant data and clear permission to use it. Discovery covers available records, data quality, access rights and how confidential information may be handled. For document assistants, retrieval should respect user permissions and document updates. For predictive models, we examine whether the data supports a meaningful evaluation and whether the expected output can be tested against business outcomes.
Prototype, evaluate and integrate
A small prototype helps test feasibility before a wider rollout. We define sample tasks, evaluation criteria and failure cases, then compare outputs with an agreed baseline. Integration can connect the result to an existing dashboard, website or internal workflow. Outputs that influence important decisions should have appropriate human review and a clear path for correcting mistakes.
AI reliability and ongoing operation
AI systems can produce inaccurate or inconsistent outputs. A deployment plan should include logging, access controls, fallback behavior and monitoring for changes in quality or cost. Language-model usage charges, data storage and response times affect the operating budget. We discuss provider choice, rate limits and the maintenance needed when data, models or prompts change.
What to share for an AI feasibility discussion
Describe the task, the users, sample inputs and what a correct result looks like. Identify data sources, privacy constraints and the system where the output will be used. These details help define a focused pilot with measurable acceptance criteria instead of an open-ended AI implementation.