Results
What we've built and what changed.
The method behind TrueBearing AI comes from years of building and running AI inside an enterprise customer success function.
Where the experience comes from
Where we learned this.
What we built
We built and ran the AI operation inside an enterprise customer success function. The automations changed how hundreds of CSMs worked with their accounts every day. Account briefs, QBR drafts, health score alerts, follow-up sequences. The tools that turned hours of manual work into minutes of review.
The scope wasn't small. We were working across CRM data, support tickets, product usage, and renewal timelines. Every automation had to fit into how the team actually worked, not how we imagined they worked.
What we learned
The technology was straightforward. Getting a team to trust it and keep using it after launch week is where most AI projects stall.
The projects that worked had one thing in common: the function leader owned the problem. They stayed involved. They defined what "good" looked like. They told us when something was off. The projects that struggled were the ones where someone in another department decided what the team needed.
That observation is behind everything we do at TrueBearing.
Why TrueBearing
That work doesn't need a seven-figure consulting contract or a team of engineers your company doesn't have. It needs people who have done it, working alongside the people who will run it.
We bring the build experience. You bring the knowledge of your function. We find what's worth building, build it, and keep it working.
What to expect
What a typical engagement looks like
A realistic walkthrough of how the Map, Build, and Steer stages play out. Pick the example closest to your business.
Finding where the hours go
A Head of Customer Success at a mid-market SaaS company books a call. Her team of 12 CSMs is spending too much time on manual account prep and QBR drafting. We run the Map: we interview team members, trace the workflows, and identify that account brief prep takes an average of 40 minutes per account per week across the team.
The Map delivers a ranked list. Account brief automation is the top priority. QBR draft generation is second. A third idea around health scoring isn't worth the complexity right now, and we say so.
Building inside the existing stack
We build the account brief automation inside their CRM. It pulls the last 30 days of support tickets, product usage data, and the renewal timeline into a draft brief. The CSM reviews it before every call. We test it with three CSMs first, get their feedback, and adjust.
The second build is QBR draft generation. Same approach: pull the data, draft the document, the CSM reviews and edits before sending to the customer.
Keeping it working
Monthly review. The account brief automation is running well. The QBR draft needs a tweak because the team changed how they report product usage. Two new CSMs joined and need onboarding on the tools. We handle all of it.
By month four, the team asks about the health scoring idea from the Map. It makes sense now because the data quality improved as a side effect of the first two builds. We scope it as a new Build.
This is a hypothetical example. Actual timelines, tools, and outcomes vary by engagement. Every project starts with the Map, where we learn what your specific situation needs.
Finding where the time goes
The owner of a reef tour operation in Cairns books a call. He runs six boats and a team of four on shore. Booking enquiries come in while the crew is offshore. After-hours messages go unanswered. Post-trip review requests don't go out. The admin piles up because everyone is either on the water or catching up from being on the water.
We run the Map. We talk to the shore team and trace every step: how enquiries arrive, how bookings get confirmed, how guests hear from the business after a trip. The Map comes back with a ranked list. After-hours booking replies and post-trip follow-ups are the top two.
Building around the tools they already use
We build an after-hours booking responder that checks live availability, answers common questions (what to bring, cancellation policy, pickup points), and sends a booking confirmation. It works inside their existing booking system. A person on the shore team reviews flagged messages each morning.
The second build is a post-trip sequence: a thank-you email goes out the evening after the trip, a review request follows two days later, and a rebooking offer goes out before the next school holiday period. All drafted by AI, all reviewed before sending.
Keeping it working through the seasons
Monthly check-in. Wet season is coming, so we adjust the rescheduling comms for weather cancellations. A new crew member joins and needs a walkthrough of how the booking responder works. The review request timing gets tweaked because guests on multi-day trips respond better when the email goes out a day later.
By month four, the owner asks about multilingual pre-trip emails for international guests. We scope it as a new Build.
This is a hypothetical example. Actual timelines, tools, and outcomes vary by engagement. Every project starts with the Map, where we learn what your specific situation needs.
Start with the Map.
Tell us which function you run and where the work is slowing down. We'll tell you honestly whether AI helps and whether we're the right people.