How it works
Start with a clear view. Move forward with control.
It starts with your existing systems and questions. An AI agent is one possible outcome, not the starting point.
Part 1
Get a clear view
01Choose a source
Start with one customer system, usually the helpdesk where conversations already live.
02Review access
See exactly what didii would read, and what it could do, before anything connects. Access is scoped to what the work needs and can be revoked.
03Check coverage
Connecting isn't the same as being ready. didii shows what data arrived, what's missing and whether there's enough to learn from. When there isn't, it says so instead of guessing.
04Inspect observations
Findings come with the conversations and records behind them, and with their limits, so your team can judge them.
Part 2
Move forward with control
05Plan a change
Choose the problem worth fixing and turn it into an Improvement with an owner, a goal and approval rules. The fix may be better knowledge, a process change, assistance or an AI agent.
06Evaluate before rollout
Replay representative cases, including the ones that should be refused or sent to a person, and compare the result with what you expected.
07Roll out with authority
Start small. Grant permissions action by action, keep a person in the loop where you choose, and pause or roll back without losing case history.
08Review the outcome
Compare results with a baseline set before rollout. Keep the change, revise it or roll it back. "Inconclusive" is an allowed answer.
What we won't promise
We won't promise a fixed setup time, or that every new workspace produces an insight straight away. How quickly a team sees something useful depends on its systems and how much data they hold. When there isn't enough, didii should tell you plainly, or show a clearly labelled sample instead.
Help shape how customer operations works next.
Tell us where your team gets stuck. Early access is free, and someone from the didii team will follow up about fit and what is available.