TemplatesGet a demo →Book a meeting

One member’s full record, answered from your administration system

Staff enter a member number and the flow queries your administration system, totals the contribution record in code, and writes a plain summary with every figure quoted as computed. Nobody pieces a member together across several screens, and no model does the arithmetic.

Support · Pensions & retirement · Someone asks · 5 steps · Your database

AI Factory · Member 360the flow as it opens in the builder
QuestionWhich member?
Query a databaseRead the member record
Work out the numbersSummarise contributions
AnswerDescribe the member
Answer shownThe answer
5 steps in the flowDrag the canvas, or any step, to move it around.

Why teams run it

When a member calls, service staff rebuild the picture by hand: status in one screen, employer in another, and a contribution history that has to be scrolled through and added up. A general-purpose assistant is worse, because it will state a total confidently whether or not it ever read one.

How it is governed

  • Queries are read-only: SELECT statements through a connection an administrator sets up.
  • The member number is bound as a value, so it can never alter the query.
  • The database host must be on your approved list before any connection opens.
  • Every run is recorded step by step in the run history.
Who runs it
Member services representatives; Pension administrators; Contributions team leads.
What you supply
A read-only database connection to your member administration system under Admin → Databases, with the query pointed at your own tables.

It ships with test questions

  • 100245
What “a person approves” looks like in the product: the run stops, the banner says what approving will do, and until someone decides, nothing leaves the system. A demo workspace on synthetic data.

From template to a live agent

The same builder, tests and release review apply to a template as to anything built from scratch.

Open it as a working flow
Every step, source, branch and approval is already in place, and every one of them can be changed before it runs on your data.
Prove it before it ships
An evaluation set can gate the release, so a change that breaks an answer never reaches anyone. A question it cannot answer from the sources leaves the gate unproven, not passed.
Keep a person on the decisions
A run that needs a decision stops and says exactly what approving will do, and who it is waiting for.
Publish where people work
A form, an embedded widget, Microsoft Teams or a scheduled batch — with its own access and limits per deployment.
What teams usually change
Rewrite the query for your own member and contribution tables; Group contributions by period or plan instead of by employer; Choose a stronger model for the written summary, or a faster one.
Step 02, in the product: an evaluation set that gates the release. A question it cannot answer from the sources leaves the gate unproven, not passed. A demo workspace on synthetic data.

Questions buyers ask

Does the model ever calculate a member’s totals?
No. The database returns the rows and the table step does the counting and summing in code; the model is instructed to quote those figures exactly and never recalculate or round them. If the query returns nothing, the answer says no member was found with that number.
Which administration systems can it read?
It reads any PostgreSQL database your administrators connect as read-only, once the query is rewritten for your tables. Drivers for other database engines are not yet included.
Who can see member data through this flow?
Only people you give access to the agent can run it, and the database connection itself is set up by an administrator. Every run, including the number asked about and the answer given, is kept in the run history.

See it run on your own data

We open it in the builder, point it at a sample of your documents and systems, and run it with you.