Guide
How to remember client conversations after the call is over
How to preserve client conversations as project memory instead of scattered notes and forgotten follow-ups.
Client memory is not only the transcript
A client conversation contains more than words. It contains constraints, hesitations, preferences, objections, promises, risks, tone, open questions, and follow-ups. A raw transcript is useful, but the real value appears when that transcript is saved in the place where future work will happen.
For a broker, that place may be a buyer, seller, or property. For a consultant, it may be an engagement. For a lawyer, it may be a matter. For an operator, it may be a site or vendor. Cairn calls this project memory because the memory has to belong to the work, not just the date of the recording.
Name the project the way you think
A good project name should match the way the user will look for the information later. If the future question is "what did this client care about?", the memory should live under that client. If the future question is "what happened at this property?", the memory should live under the property. If the future question is "what was promised in this matter?", the memory should live under the matter.
Cairn is intentionally designed around projects because professional recall usually starts from the object of work, not from a recording file name.
Use AI after the memory is grounded
An AI assistant is most useful when it is grounded in the right source. Asking a generic model to remember a client is not the same as asking over a saved transcript or project. Cairn lets the user choose memory scope so a quick general question does not need the archive, while a client-specific question can use the project.
Useful questions include: what did the client decide, what objections came up, what follow-up did we promise, how has the preference changed, and what should I send next?
Follow-ups should be reviewed, not blindly sent
Cairn can help draft follow-ups and action records from conversations, but the user remains responsible for reviewing the result. That review is not a weakness. It is how professional tools should behave when they work with client memory.
Cairn is local-first for core app memory: projects, sessions, transcripts, settings, chat history, processing jobs, reports, todos, and calendar events are stored locally on the user device. Some requested features still use cloud and AI services: Supabase for authentication, agent/account/billing records, Groq and DeepSeek for AI processing, and Razorpay for checkout where paid plans are available.