A useful AI project brief starts with a business task, not a preferred model or a list of technologies. The aim is to give both sides enough context to decide what should be explored, what should be built and what would count as a useful result.
1. Name the person and the task
Describe who will use the system and what they are trying to finish. For example: an operations reviewer needs to check an incoming document and decide where it should go next. Keep the example specific enough to discuss, without sharing confidential records in an initial enquiry.
2. Explain what happens today
Outline the current steps, systems and handoffs. Which work is repeated? Where does a person make a judgment? What causes exceptions? A simple walkthrough is often more useful for a first discussion than a long feature list.
3. Separate the desired result from the proposed solution
Write down the outcome you want, then list any solution ideas separately. An assistant, a document workflow and a new application may address different parts of the same problem. Leaving that distinction visible makes it easier to examine alternatives.
4. Identify available data and access
List the information sources the system would need and who controls them. Note whether example data, APIs or a test environment are available. Flag sensitive information and access restrictions. The first conversation needs a map of these dependencies, not the credentials themselves.
5. Define a focused first release
Choose a user journey or workflow slice that is worth testing on its own. State what it should include, what can wait and which assumptions need investigation. Avoid treating a prototype demonstration as proof that every production requirement has been solved.
6. Decide how the result will be reviewed
Describe representative tasks and the people who can judge the results. Include difficult cases, unacceptable behavior and situations that require human approval. Keep open questions visible rather than inventing accuracy targets before the task is understood.
7. Surface delivery constraints
Include timing, existing technology, ownership expectations and any relevant procurement or deployment constraints. If budget or scope is still uncertain, say so. A clear unknown is useful information.
A compact starting point
You can begin with five sentences: who the system is for; what they need to do; what exists today; what information and tools are involved; and what the first release should demonstrate. Add examples when you can share them safely.
For a conversation with Webexa, send that outline through the project enquiry form. It gives us a concrete starting point for discussing AI development, integration, automation or model adaptation.