Bots for bakers, fitness trainers and repair shops: where to start
A small-business bot should reflect what you sell and how you work. Bakers have collection dates, trainers have programmes and participants, and repair shops have vehicles and service requests. Similar menus do not make these processes identical.
Bakers: connect recipes and orders
Start with the information needed to fulfil an order: product, quantity, date and agreements with the customer. Decide what belongs in the workspace and what the customer only needs as a message.
MyKondi appears in my portfolio as a baker’s assistant with recipes and orders in one workspace. A new project needs its own scope; a narrow first task does not require every feature of an existing product.
Fitness trainers: organise materials and participants
Separate programme creation from access management. Decide which materials belong to each challenge, how participants find their workspace and who confirms the paid period.
MaraFit is a portfolio example covering challenges, programmes, menus, participants and payment records. In this project the trainer checks that funds have arrived and confirms payment. Recording a payment is different from automatically verifying a bank transaction.
Repair shops and fleets: separate the workflows
Distinguish workshop operations, vehicle records, driver search and financial workflows. They involve different records, users and access rules.
Sheva Auto presents these tasks as separate projects. For a similar solution, start with one chain: who creates a record, who updates it and what marks the task complete. This makes the automation concrete.
Choose the first task through observation
For a few working days, note recurring actions. Record who performs each one, the steps involved, where the result is stored and what happens when it goes wrong. This is a baseline, not a promised saving.
A frequent process with clear rules can be a good candidate. Leave decisions that require professional judgement with a person, while the bot collects and organises the information.
Measure the result after launch
Choose a measure before development: request handling time, incomplete records or manual data transfers. Compare the same workflow over comparable periods before and after launch.
Without a baseline, a promised percentage saving is not meaningful. We can agree on a result to check and shape the first bot release around it.