AI that works
An AI feature that looks good in a demo but doesn't save the team time is worse than no AI. Every capability is measured against a before/after workflow metric. We kill AI features that fail that test.
How we operate
Six operating principles that shape how DialPhone builds product, runs support, prices, and treats customer data. Written down so we can hold each other to them.
Uptime is trust
99.999% SLA. A phone system that drops a customer call costs the business more than the plan's price. We budget reliability as a first-class concern — more engineers on infrastructure than on most feature teams.
Privacy is the product
Customer conversations belong to the customer. We don't train shared AI models on customer data. We publish subprocessors. We sign HIPAA BAAs at no surcharge. Privacy is a property of the platform, not a marketing claim.
Transparent pricing
Every tier published — UCaaS, contact center, AI add-ons. No "call for a quote" until enterprise-specific custom work. Procurement teams should spend time evaluating fit, not extracting numbers.
Candor with customers
If we lose on a specific feature against a competitor, we say so on the compare page. If we hit an incident, we publish the post-mortem. Long-term trust beats short-term positioning.
Small teams, big outcomes
We hire generalists with deep expertise, not specialists with narrow one. A typical DialPhone product team is 4-8 people shipping features that larger teams at competitors take quarters to deliver.