A private or paid assistant that writes in the approved voice, checks source examples, and flags copy that drifts.
Case studies
Six moments where an AI app becomes worth paying for.
Each story begins before Prostir: a consultant rewriting the same answer, a course owner losing students between lessons, a team calculating by hand, a support flow that needs the same calm answer every day. Open the case that feels closest to your own week.
Open in an AI client
Case studies
Choose the customer scene, then open the full case.
Each story begins before Prostir: a consultant rewriting the same answer, a course owner losing students between lessons, a team calculating by hand, a support flow that needs the same calm answer every day. Open the case that feels closest to your own week.
01 · Case 01 Brand voice assistant
A creator or agency turns tone of voice into an AI app that drafts posts, replies, newsletters, and client copy without losing the brand style.
Read case study → 02 · Case 02 Course tutor with lesson statesA course owner turns lessons into an AI tutor that knows where the learner is, which event should happen next, and when a milestone must be earned instead of skipped.
Read case study → 03 · Case 03 Formula and pricing calculatorA business puts pricing, tax, eligibility, scoring, or planning logic behind a JavaScript tool so answers calculate the same way every time.
Read case study → 04 · Case 04 Support and onboarding guideA product team gives customers one assistant that knows docs, onboarding steps, support policies, plan rules, and escalation paths.
Read case study → 05 · Case 05 Internal knowledge helperA team publishes a private AI app for policies, SOPs, onboarding, sales enablement, and operations knowledge.
Read case study → 06 · Case 06 Paid expert with user memoryA consultant packages expertise as a paid advisor that remembers client preferences, decisions, and progress across sessions.
Read case study →Case studies
Compare the cases by customer promise.
Use this table to choose the buyer situation first. The prompt, knowledge, tools, state, memory, and price follow from that story.
| Case | Best fit | Build pattern | Customer promise |
|---|---|---|---|
| Brand voice assistant | Consultants, founders, agencies, creators, and marketing teams with repeatable voice rules. | Tone of voice · Knowledge files · System prompt · Content review | A private or paid assistant that writes in the approved voice, checks source examples, and flags copy that drifts. |
| Course tutor with lesson states | Course creators, language tutors, coaches, bootcamps, and educators with structured learning paths. | State machine · User memory · Course knowledge · Progress gates | A tutor that describes every learning move as current state, event, guard, action, and next state, while storing progress per session or user. |
| Formula and pricing calculator | Consultants, accountants, agencies, operations teams, and SaaS teams with repeatable formulas. | JavaScript tools · Jint · Formula logic · Deterministic output | An AI app that talks naturally, calls a controlled JavaScript function, and explains the deterministic result. |
| Support and onboarding guide | SaaS founders, support teams, agencies, marketplaces, and product-led businesses. | Support docs · Onboarding · Customer access · Escalation | A customer-facing app that answers from product knowledge, checks access context, and hands off cleanly when a human is needed. |
| Internal knowledge helper | Small businesses, agencies, remote teams, HR, sales, and operations leaders. | Private access · Internal docs · Tool permissions · Team operations | A private assistant that answers from internal sources, respects access boundaries, and can trigger approved internal tools. |
| Paid expert with user memory | Consultants, coaches, accountants, legal-adjacent advisors, agencies, and expert creators. | Paid access · User memory · Client context · Stripe | A paid AI app that feels continuous for each client while memory stays scoped to the app and access grant. |
Start from a case
Start with the scene your customer already recognizes.
Pick the closest case, replace the sample knowledge and rules with yours, then publish the app with access, billing, and the runtime behavior the story requires.