Approach and manifesto

An answer is a commitment.

An answer generated by artificial intelligence under your brand becomes an implicit promise. These principles guide how we build and validate Aplomb before presenting a capability as available.

The manifesto

  • 1 · Ground, don’t invent AI-generated answers must begin with knowledge approved by the organization.
  • 2 · Honesty is part of the product When information does not exist or a capability is not available, the platform must say so.
  • 3 · Search and support are one problem Information discovery and guided assistance belong to a single, coherent experience.
  • 4 · Your brand, your rules The organization defines the tone, the scope and the limits.
  • 5 · Control is better than stronger promises Aplomb favours explicit limits and a verifiable method.
  • 6 · Prove before announcing No result, figure, capability or integration should be presented as a given without proof.

Validation method

We validate AI behaviour before we talk about it.

We do not publish performance figures here. What we can describe is the approach: a method meant to confront the platform with reality before a capability is presented as a given.

  1. Define explicit expectations. Describe what a good answer should do, and what it should not do, in a given context.
  2. Confront representative cases. Put the platform in front of situations drawn from real knowledge, including questions with no available answer.
  3. Check the limits. Make sure it stays within scope and flags what is not known, rather than filling the gap.
  4. Announce only after demonstration. Present a capability as available only once it has been observed repeatedly.

A method can be shown. Results are proven — privately, in your context, before any public claim.

Our limit here

This page describes an intent and a method, not a track record. We do not name internal tests, providers or architecture, and we put forward no figures. What matters is verified in your environment, not in a brochure.

Let’s discuss what would matter to you.

The right measure of an answer depends on your context. Let’s start there.

Discuss your environment