Customers rarely leave silently — order frequency drifts, complaint tone shifts, the activity trail in SAP Business One changes shape first. In this demo, TEKAI reads those signals and names the accounts at churn risk while a phone call can still fix it.
By the time churn shows up in the sales report, the customer decided months ago. The earlier warning was there all along; it just wasn’t assembled anywhere anyone would see it.
A customer who ordered monthly now orders quarterly. Ticket sentiment sours. The last three quotations went unanswered. Each of these signals lives in SAP Business One — sales history, activities, service records — but they live in different modules, and no standard report reads them together per account.
That is why retention fails on synthesis, not data. The sales manager sees order values; the service desk sees complaints; nobody sees that the same account appears in both trends at once. Individually each signal is dismissible — a slow month, a one-off complaint. Together they are a customer three-quarters of the way out the door. The synthesis is exactly the work a language model connected to live data is good at: reading many small facts about one account and stating what they add up to.
On a demonstration database, TEKAI produces a list of accounts ranked by churn risk — each with its evidence attached: ordering-pattern decline, activity signals, unresolved service history. Not a bare score, but the reasons: this account’s order frequency halved over two quarters, its recent activities show a complaint pattern, its open service issue has sat unresolved.
Follow-up questions go account-deep, the way a sales head would ask them: what changed for this customer, since when, who owns the relationship. The conversation moves from group-level ranking to single-account history without switching tools or building a report.
Every account and figure in the video comes from a demonstration database, not customer data. On your own system, the same conversation reads your sales history and your activity trail.
Churn scores are decoration; the deliverable is Monday’s priority list for the sales team, each name with the reason to call attached. That distinction matters. A dashboard of risk percentages invites discussion; a list that says “call this account, orders halved since March, complaint open for three weeks” invites action — and the person making the call walks in knowing what the conversation is about.
Retention economics do the rest. Keeping an account costs a call; replacing one costs a pipeline — prospecting, qualifying, quoting, winning, onboarding — plus the months of revenue lost between. Any system that reliably converts drifting accounts into timely calls pays for itself on the first save.
The cadence matters as much as the list. Run quarterly, this is a post-mortem; run monthly, it’s a watchlist — who is cooling off, what changed, and which conversations to have this week — arriving before the quarter’s numbers make the drift official.
SAP Business One (SQL or HANA) with sales and activity history · TEKAI at ₹5,000/company/month India, $150 global · your own AI subscription (Claude, ChatGPT or Perplexity) · permission-scoped access, nothing trained on your data (/tekai/security/).
Order frequency and value drift, activity and service patterns — read together per account from your SAP Business One history rather than in separate reports.
It reads what’s in the system — activities, service calls, documents. The richer your team’s record-keeping in SAP Business One, the more signal there is to read.
It surfaces evidence, not verdicts — the ranked list with reasons attached is for your team’s judgement, which is exactly where an account decision belongs.
Yes — a monthly at-risk digest on the WhatsApp rail is the natural pattern, so the list arrives without anyone remembering to run it.
That’s the core case — dealer and stockist networks where relationship drift is measurable in orders long before anyone says goodbye.
New to the category? Start with the overview: AI for SAP Business One, explained.