A successful engagement needs more than a technical idea. It needs an agreed problem, useful examples, clear decisions and a definition of what will be accepted.
Establish fit
We discuss the users, current workflow, desired result, available data and principal constraints. We identify who can make product decisions and who owns existing systems. If a conventional software change or an existing product is the better fit, the initial scope should reflect that.
The outcome is a practical next step: request missing information, propose a focused discovery, prepare a build proposal or explain why the engagement is not a fit.
Resolve material uncertainty
A project blueprint can define the workflow, architecture, data requirements, risks, acceptance criteria and delivery options. A bounded experiment may be needed where a key assumption about the data or AI behaviour is untested.
A blueprint is a deliverable in its own right. It should leave you with a clear decision about the next stage, not an indefinite consulting dependency.
Agree the commercial and technical scope
The proposal names deliverables, exclusions, dependencies, milestones, responsibilities and acceptance criteria. It distinguishes project-specific work from pre-existing components and third-party services.
Hosting, model usage, data processing, source-code access, deployment, support and handover are addressed explicitly. A general website description is not a substitute for the agreed project terms.
Build and review working increments
We plan demonstrations around completed parts of the workflow. The client reviews what works, raises corrections and makes the decisions needed for the next increment.
When a request changes the agreed scope, we record its impact on delivery, price and dependencies before treating it as committed work. Normal defect correction remains distinct from additional functionality.
Evaluate and accept
The application is assessed against the agreed examples and conditions. AI output quality, conventional software correctness, access controls and operational readiness are not collapsed into a single impression.
An exception can lead to a fix, a narrower release or an agreed limitation. The acceptance record identifies what passed, what remains open and who owns the remaining work.
Deploy and transfer responsibility
The handover can include repositories, deployment instructions, configuration requirements, test procedures, runbooks and a walkthrough for the receiving team. Ownership and access follow the contract.
Before launch, agree who receives alerts, responds to failures and approves future changes. Post-launch support is a separately defined responsibility, whether held by inAi, your team or another partner.
Confidentiality and references
Client information is not a public demonstration dataset. We agree how material may be accessed and used for delivery. Publishing a client name, screenshot, quote or result requires a separate permission decision. Anonymous case studies also need review for identification risks and contractual restrictions.