Guardrailed customer conversation AI
Design customer-facing assistants around approved knowledge, limited actions, safe failure, privacy, and a visible route to a human.
When to use it
Use for website chat, messaging channels, support assistants, lead qualification, and post-purchase conversations that use a language model or automated workflow.
What you need
- Approved source of truth for product, price, availability, delivery, returns, and service limits
- Permitted actions, authentication requirements, and data the assistant must not collect
- Escalation owner, hours, service-level expectation, and current channel policies
Workflow
- 01
Define the job and boundary
List supported intents, prohibited decisions, and actions requiring a person or verified system.
- 02
Ground answers
Use approved, dated content; show uncertainty or ask a clarifying question when the record is incomplete.
- 03
Constrain tools and data
Give the assistant only the minimum data and permissions needed; require confirmation before consequential actions.
- 04
Design safe recovery
Create clear behavior for unsupported requests, complaints, payment disputes, safety concerns, prompt injection, and system outages.
- 05
Make handoff real
Offer an accessible human route, pass relevant context with consent, and avoid claiming a handoff has happened until it has.
- 06
Test before release
Test common tasks, ambiguous wording, Arabic dialect and mixed-script input, adversarial instructions, privacy leakage, and failure recovery.
- 07
Monitor and update
Review sampled conversations, escalation and correction reasons, approved-content changes, access logs, and channel policy updates.
Output
A bounded assistant specification, approved knowledge set, escalation map, test cases, and an owner for ongoing review.
Boundaries
Do not let generated text set prices, promise outcomes, access accounts, or execute irreversible actions without a trusted control and human-approved policy.
How it fits existing work
Builds on the WhatsApp Commerce Conversations playbook; this framework adds model-specific security, tool permissions, evaluation, and safe failure design.