Customer platform
Write it once.
Agents, customers and the bot agree.
Atmora Atlas gives every article a review owner and a review date, and demotes content that has gone past it until somebody confirms it is still true. Agents stop keeping a private folder of answers they trust more than the knowledge base.
- Cloud
- Private cloud
- On-premise
Overview
One article, three audiences: the agent console, the help centre and your support assistant.
Atmora Atlas holds the answers a support organisation runs on and publishes them to three audiences from one source: the agent sidebar inside the ticket, the public help centre and the retrieval API behind your assistant. Internal-only paragraphs live inside the same article as public content and are stripped at publish time, so nobody maintains a customer-facing copy that drifts away from the truth. Search combines keyword matching, which is what actually finds product codes and error strings, with vector retrieval, which is what finds the way customers describe a problem in their own words.
Atlas is a knowledge system, not a ticketing system. It plugs into Zendesk, Salesforce Service Cloud, ServiceNow or Freshdesk and makes no attempt to replace them. It is also the wrong tool for internal engineering documentation that changes several times a day; that belongs in a wiki that lives next to the code. Atlas is built for content with a named owner, a defined audience and a measurable cost attached to being wrong, which is a much smaller set of documents than most organisations assume.
- 31%
- Help centre sessions with no ticket raised within 24 hours
- -2 min 40 s
- Average handle time after agent sidebar rollout at Meridian Exchange
- 88%
- Articles reviewed on or before their review date
- 14
- Languages published from a single source article
Modules
What ships in the box
- Authoring, review and publishing workflow
- Taxonomy, search and ranking
- Agent-assist sidebar
- Public help centre
- Retrieval API for assistants and bots
- Content health and deflection analytics
Integrates with
- Zendesk
- Salesforce Service Cloud
- ServiceNow
- Freshdesk
- Intercom
- Slack
- Microsoft Teams
- Okta
Capabilities
What it does
Articles with an expiry date, not just an author
Every article carries a review owner and a review date. Content past its date is flagged in the agent sidebar and demoted in ranking until somebody confirms it is still correct.
Hybrid search over keywords and meaning
Keyword matching handles part numbers and error strings; vector retrieval handles how customers actually phrase things. The two result sets are merged and reranked, not chosen between.
Agent assistance inside the ticket
Suggestions track the ticket text as the agent types, and inserting one drops a trimmed snippet with a link into the reply instead of pasting an entire article at the customer.
One source, three audiences
Internal-only paragraphs sit inside the same article as public content and are removed at publish time, so nobody maintains a separate customer-facing copy that slowly goes stale.
A retrieval endpoint your assistant can use
A scoped API returns passages with article identifiers and confidence scores for a support bot. Answers carry citations, so an agent can check what the assistant told the customer.
Translations that know their source version
Each translation records the source version it came from. When the English article changes, every language derived from it is marked stale with the relevant difference attached.
Deflection measured against tickets, not page views
Help centre sessions are joined to tickets raised within the next 24 hours, so deflection is calculated from what did not get raised rather than from traffic to an article.
Content gaps ranked by demand
Failed searches and poorly rated answers cluster into topics ordered by volume, which gives the content team a backlog built from customer demand rather than from internal opinion.
Built for
Where this is deployed
Industry
Telecom & Media
OSS, BSS and delivery platforms that keep working after launch night.
Industry
Banking & Financial Services
Payment rails, risk engines and core-adjacent systems built by people who have run them at 03:00 on a settlement night.
Industry
Retail & E-commerce
Storefronts, stock ledgers and fulfilment logic that hold together on your busiest trading day.
Industry
Travel & Hospitality
Booking, offer and disruption systems for operators whose worst day is a fare sale during an outage.
Industry
Education
Student and learning systems that survive enrolment week and the statutory return that follows it.
Industry
Healthcare & Life Sciences
Clinical and regulated software built to pass an audit, not just a demo.
FAQ
Questions we get asked
- Can retrieval run without sending content to a third-party model?
Yes. The embedding and reranking models run inside your deployment on CPU or a single GPU, and the retrieval API works with no external call at all. Generative answering is optional and can be pointed at a model you host yourself.
- How do we migrate existing articles?
Importers cover Zendesk Guide, Confluence, SharePoint and Markdown exports, preserving categories, attachments and URLs so external links keep working. Expect to archive a large share on the way in; most libraries carry years of content nobody has opened.
- Who should own Atlas internally?
Support operations, not marketing and not engineering. The product assumes a small content team with named owners per topic and a review cadence. Without that ownership any knowledge base decays within a year, and no amount of search quality compensates for it.
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