Most knowledge tools help you write. Mosaic AI tells you what to write by analyzing resolved cases, ranking gaps by case volume, and turning your team’s previous case resolutions into review-ready articles.
The answers to your hardest cases live in solved tickets and senior reps’ heads. When those answers never become reusable knowledge, the same issues return as new cases and escalations.
Replace one-off requests and guesswork with a ranked view of what support needs documented next.
Turn the hard work already happening to resolve cases into reusable knowledge for your whole support team, automatically.
Put proven answers where customers and reps already look, so they do not have to solve the same problem again.
Cluster resolved cases by underlying issues and product lines to see what is recurring and worth documenting.
Compare each issue against your existing knowledge base to find what is missing.
Create a cited article from how your team actually solved the issue.
Route the draft to the right expert for final review before it reaches your knowledge base.
“We scaled our Mosaic AI deployment from production pilot to full adoption across multiple business units in under 10 weeks.”
“We see plenty of opportunities where it’s going to help us streamline our customer interactions and make us more efficient and effective.”
“We have been able to scale and keep up with the demands without having to add a significant amount of headcount. With basically the same size team we had last year, we’ve made improvements.”
Groups cases by issue and product, ranks them by volume, and checks existing knowledge to find the gaps.
Turns case comments and proven resolutions into cited drafts, with every source case linked.
Routes drafts to the right experts, tags teammates, and edit formatting before anything is published.
Approved articles go directly to your knowledge base, powering self-service and rep assist.
Connects to 100+ integrations. Start indexing your full support stack within weeks. No data migration. No engineering required.
Connect your systems once, then build agents for any workflow on one shared framework. Every agent uses the same data, integrations, and controls, so you can expand without adding another point solution.
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We analyze your real case data, at no cost, to find where time, effort, and spend accumulate, what can be automated, and how much it would lower your cost to serve.
You get a live environment built for your top use cases, running on your own systems, using your own case history. You see the result before you sign anything.
Deployed on top of Salesforce, Zendesk, and the rest of your stack. No migration, no developer resources, deployment expertise included.
Mosaic AI analyzes the cases your team resolves. Knowledge uses those insights to group recurring topics. When a topic keeps generating cases but no article covers it, or the article that exists did not prevent the case (that is a gap). Those two signals tell you exactly what to write next, ranked by how much volume it would remove.
It comes from your own resolutions, not the internet. Knowledge drafts from work your team already did: previously resolved cases, developer docs, Slack threads, and existing documentation, and cites every source. That's why it holds up in complex, multi-product environments.
This is what Mosaic AI is built for. Every article is structured and tagged against the Customer Context Model, which knows the product it applies to.
By automating repetitive tasks like tagging, call notes, and FAQ updates, AI frees up time and speeds up ticket resolution.
Confluence's AI helps you write and organize the content you already have, but it doesn't analyze your ticket queue to tell you what's missing. Zendesk has added its own gap-detection and ticket-to-article drafting, but it stays inside Zendesk's world. Mosaic AI's Knowledge runs on the same platform as Self-Service and Assist, so every article it publishes immediately starts deflecting cases and assisting reps, and every new case feeds back into what Knowledge drafts next. That compounding loop across all three, not gap-detection alone, is what a single add-on can't reproduce.
We’ll analyze a sample of your resolved cases, uncover the gaps behind repeat issues, and show what to document first based on case volume.
