How long does your system
hold onto its purpose?
Your public AI assistant speaks under your company’s name. Customers use it to understand your policies, make decisions and get things done.
An assistant can keep responding fluently while losing the purpose, context or limits the business relies on. We investigate how those responsibilities hold through ordinary use, changing requests and sustained pressure, then engineer and retest improvements.
Testing the full interaction.
We test the system against the responsibilities it has been given, following how its behaviour changes as requests, information and conversational context develop. Assessments can cover customer-facing assistants, internal agents and the workflows they support.
- Business role and representation: Does it continue to fulfil its intended role, or begin taking on responsibilities the company never assigned to it?
- Policy and authority: Does its guidance follow company policy, and does it accurately represent what it can decide, promise or do?
- Context and continuity: Does it retain important facts, corrections and unresolved work through extended conversations, interruptions and handovers?
- Actions and escalation: Do reported actions match what happened, and does it involve the right people when a request requires their judgment or authority?
The conversation continued. The business purpose disappeared.
Our review of a major international company’s public support assistant traced a conversation that moved from account support into product planning and software development. The assistant helped define the new work, accepted a lead role in planning it and later said it could not recall the earlier project.
The finding was a sustained change in the role the assistant presented to the customer. It continued speaking within the company’s service while offering to take on responsibilities outside its support function.
Investigation, engineering and retesting.
Your team receives documented findings, recorded interaction evidence and engineering priorities. The work can continue through implementation and verification, with evaluation cases for checking subsequent changes.
Engineering can cover agent instructions, memory, application logic, model configuration, tool permissions, integrations and human handover. We retest improvements against the failure conditions and the customer work the system needs to perform.
Engagements can extend across assistants, customer channels, business functions and connected systems, with ongoing evaluation as deployments change. Commissioned source code, documentation and technical handover are included as defined in the project scope.
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Discuss an assessment.
Tell us what your AI represents, which work it handles and where you need confidence in its behaviour.