Find content gaps
Review permitted support questions and identify topics where approved guidance is missing, incomplete or difficult to locate.
Managed AI staffing
Keep help content aligned with the questions customers ask
Give your help library a maintenance process that continues after publication. An AI knowledge base coordinator identifies unanswered questions, drafts changes from approved material and checks existing articles for inconsistencies. Reviewers receive the proposed edit with its source, purpose and affected customer question clearly connected.
Find my AI workerBuild a free role brief Responsibilities, handoffs and quality measures. No signup.
The job behind the title
Knowledge bases age unevenly. A product change reaches one article while a related answer stays outdated, and agents keep sending explanations that never become reusable guidance for the next customer.
Responsibilities
We shape these responsibilities around your systems, priorities and decision permissions.
Review permitted support questions and identify topics where approved guidance is missing, incomplete or difficult to locate.
Prepare article changes from approved sources, including the steps, prerequisites and limitations a reader needs to act.
Look for conflicting instructions, broken references and articles affected by the same approved product or policy change.
Track draft, review and publication states so an unapproved answer is not mistaken for current customer guidance.
A clear handoff
Illustrative workflow
An example of how the work could run, tailored during onboarding. This is not a customer case study.
Support agents repeatedly explain a changed account-setting procedure, while the public article still points customers to an older sequence of screens.
The coordinator compares the approved procedure with the article, drafts the revised instructions and identifies related links that may also need updating.
If the new procedure is not confirmed for every account type, the draft highlights that uncertainty for the product or support reviewer.
Onboarding & continued development
We learn the job, your expectations and how your team works. Then we select and configure an AI worker for the role.
We help your bot learn your systems, policies and preferences. Together, we review its work and prepare it for the responsibilities you agree on.
We stay involved, review performance and continue coaching your bot. You have a human Botsource contact when the work needs attention.
We agree on targets and review methods together. These are proposed measures, not claimed results.
Before you get started
Publication can be included within the permissions you approve. Many teams begin with a review queue, then allow defined low-risk updates once the content workflow is established.
You choose the authoritative material, such as approved product notes, procedures and reviewed case resolutions. Conflicting sources are flagged rather than blended into a confident but unreliable answer.
It can start with a specific content gap or maintenance queue. We scope the work around the questions and articles that matter, preserving useful existing material and your terminology.
Start with the job
Tell us what the role needs to accomplish. We’ll talk through responsibilities, systems, onboarding and how you want to measure performance.
You’ll leave the assessment with a clearer role plan and next steps for preparing the right AI worker.
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