AI-native CRM
Most teams carry a CRM that was designed for somebody else's sales motion, and they pay for it in small daily amounts — fields nobody fills, reports that need a spreadsheet afterwards, and a rep who keeps the real state of every deal in their head because the system has nowhere to put it. We build the CRM around the way this particular business sells, with agents inside it from the first version.
How the work runs
- We study the operation — an agency, an online school, a developer's sales office — and write down how a deal actually moves through it, including the steps people do outside the system.
- We shape the data model around the entities this business argues about: the person, the company, the project, the deal, and the history that connects them.
- We assemble the CRM against that model and put agents on the routine parts, so the record keeps itself current while the rep is still in the conversation.
- We keep working with the team after launch, because the useful requests only arrive once people have been inside the system for a few weeks.
Where we have done it
- International real estate brokerage. A production CRM that had been growing for years, moved onto a deal-based model with Person and Company on top, so a rep opens the full client context in one place.
- Developer's regional sales office. A new AI-native CRM for local offices, with a project database, voice control over the system, and agents keeping the portals and the head-office CRM in sync.
- Online school. The same approach outside real estate, shaped around enrolment and student progress instead of listings and viewings.