You find out too late
Cancellation signals show up weeks ahead. Falling usage, unresolved tickets, failed payments, silence. The signals are there. They just sit unread until it's too late.
Tetherly turns your customer data into a prioritized recovery queue. Spot risk early, act with the right context, and prove the saved revenue, without rebuilding your stack.
By the time a customer asks to cancel, the signal has been visible for weeks. The bottleneck isn't prediction. It's execution.
Cancellation signals show up weeks ahead. Falling usage, unresolved tickets, failed payments, silence. The signals are there. They just sit unread until it's too late.
CS and ops teams know what good retention looks like. The hard part is finding time to watch every account, write every email, and follow up on every signal.
A risk score is a starting point. The hard part is execution. Who to contact, why, what to say, what worked. That's where Tetherly lives.
Drop a CSV from your CRM, billing system, or warehouse. Tetherly auto-maps your columns, even the ones it's never seen before.
Deterministic scoring detects risk and explains why. Every score is backed by structured evidence from your data. No AI hallucinations.
Work through a prioritized queue with the next action for each account. Drafts read like your team wrote them. No internal scores, no AI mentions.
Track outcomes (saved, churned, follow-up) and export a board-ready report. Revenue at risk, revenue saved, save rate by reason. All in one place.
Tetherly is built for one job: turn risk signals into recovered revenue. Here's what that looks like in practice.
No long-term contract before you see results. Pricing is in EUR. USD billing available on request.
Diagnose your churn baseline, run two recovery cycles, leave you with playbooks.
Continuous risk monitoring, weekly recovery cycles, monthly outcome review with your team.
Same product, run by your team. Multi-workspace, integrations, and outcome history.
A short read for funds and angels evaluating the category. Full deck and metrics available on request.
CRMs hold contacts. Billing tools hold invoices. Support tools hold tickets. Nothing turns those signals into a recoverable revenue queue. Tetherly is the operations layer between them.
CSV-first import means buyers can validate the product the same week they hear about it. No IT, no warehouse project. Sales cycles collapse from months to days.
Deterministic scoring is the moat against AI-only commodities. AI explanations are what make it usable. The architecture is built for transparent, defensible decisions.
Recovery sprints prove ROI fast. Monthly retainers create recurring revenue. Self-serve unlocks long-tail SaaS. Each tier compounds the previous one.
Risk scoring is rule-based and auditable. AI explains and recommends. It never invents the underlying evidence.
Drafts never mention AI, internal scores, or risk classification. Outreach reads like it came from your team, because it should.
Every risk flag links back to specific signals in your data. Your CS team always knows why an account surfaced.
No. Tetherly sits next to your CRM, billing, and support tools. It pulls together their signals into a single recovery queue, then lets your team act and track outcomes.
Most churn models give you a number and call it done. Tetherly's deterministic scoring is fully explainable, and the product is built around the action. Who to contact, why, what to say, what happened. Prediction is the easy part.
AI summarizes evidence, drafts customer-safe outreach, and explains internal context. It never invents the underlying evidence, never replaces deterministic scoring, and never appears in customer-facing copy.
A CSV with one row per customer. Helpful columns: client ID, MRR, renewal date, last login, usage score, NPS, open tickets, payment status, notes. Tetherly handles missing fields and flags them in the data quality score.
The public demo at /demo/dashboard uses synthetic customer data so you can try the full flow without uploading anything. You can also import your own CSV in the demo and the data stays in the browser session.
Today the demo runs in your browser session and does not persist customer data. Production deployments support workspace isolation and SOC 2-aligned controls; the production schema (Supabase) is published in the repo for review.
Try the public demo, or book a working session and we'll run your CSV through the queue together.