Make AI answers easier to trust.
Lexora Labs helps customer support and knowledge teams find and fix the content gaps, unclear handoffs, and review processes that make AI unreliable. Start with one workflow and leave with a practical plan to improve it.
Explore the AI Support Workflow Review | Discuss your workflow
Led by Charles Costa, MLIS, a content strategist and published researcher in generative AI and customer service.
Find out why one AI-assisted support workflow produces inconsistent answers or too much rework. Get a prioritized plan for what to fix first.
Make source content easier to find, maintain, and use. Define ownership, resolve conflicting guidance, and design clearer handoffs.
Help staff use AI in their actual work, with clear practices for checking answers, handling exceptions, and escalating uncertainty.
Review a bounded sample of source content and AI outputs to identify gaps, contradictions, and points where human review breaks down.
Receive findings with examples, prioritized recommendations, and a proposed workflow with clear review and escalation steps.
Establish a baseline for answer quality, review time, and rework so your team can test whether the changes make a difference.
From an unreliable workflow to a clear plan
1. Assess
Choose one workflow and define the problem, scope, and success measures.
2. Investigate
Examine source content, sample outputs, and the people involved.
3. Design
Identify the most important fixes and propose a clearer workflow.
4. Enable
Define who checks answers, handles exceptions, and owns the content.
5. Measure & improve
Use the measurement plan to test changes against your baseline.
