# Copious

Copious helps CX and support leaders decide what AI should handle in a support queue and what their people should keep. It is built for the manager or director accountable for deflection, cost per contact, CSAT, and first contact resolution.

Copious is not an implementation firm. It does not answer tickets, build chatbots, or rank AI vendors. If you want someone to build and run your support bot, Copious is the wrong tool.

Copious reads the shape of your queue. Classification fields, volumes, channel, handoff counts, timing. It never stores ticket subjects, customer messages, comments, attachments, or customer identity. It comes back with the classes of contact your team actually handles, ranked by volume, and you confirm them. Then you describe a class in plain language and Copious tells you whether AI should handle it, shows you the words that decided it, names which model fits, and tells you what to say to that model. Then it files the decision with its date, its owner, and the rules behind it.

You write your own rules in plain sentences. From then on, every prompt your team writes gets checked against those rules before it goes out. Most pass, some get adjusted automatically, a few get held.

The ledger is the output leadership reads, and it is live in the product today. Every class of contact your queue carries, ranked by volume, with its ruling or a blank where one has not been made yet. The blanks are the point.

Classes reach the ledger from a connected read of Zendesk, Kustomer, Freshdesk, Intercom, or Jira Service Management, or from a structural export you upload. Connected reads repeat on a cadence you set. Rulings you have already filed survive every re-read. Freshdesk reads don't include handoff counts.

Slack is optional, as a notice channel only, not an intake. Copious posts to one Slack channel when a ruling is filed or needs re-verifying, and when a read finishes or fails. Messages carry only names, verdicts, dates and counts. Nothing from your queue goes in them.

Copious takes no money from AI vendors. No affiliate commissions, no referral fees, no paid placement. We don't take credits, grants, or referral fees from any AI vendor. We pay for the models we use, like any customer.

- Homepage: https://copious.app/
- Contact: https://copious.app/contact
- Release briefs: https://copious.app/briefs
- Discover: https://copious.app/discover

## Access

Copious is invite-only while we build. Request an invite at https://copious.app/contact.

Field allowlist at intake, the Check never calls a model, every override logged.

## Pricing

- Free: $0. Three rulings, no card.
- Solo: $99/month or $990/year. One owner.
- Team: $499/month or $4,990/year, one flat price for up to 50 owners. Agents who only use the Check are free.
- Enterprise: more than 50 owners or more than one function. By conversation.

Invite-only while we build. Request access at https://copious.app/pricing or https://copious.app/contact.

## The data boundary

Connected intake reads structure only. Whichever field carries your taxonomy: the form, type, group, tag, component, or label your tool uses. Open contacts as well as closed ones. Volumes over the window you choose. Handoff count, where the tool records it; on Zendesk it comes from the assignee stations already in ticket metrics, so nothing has to be instrumented. Freshdesk doesn't record handoffs. Created and resolved times, from which timing and SLA performance are derived. Channel, where the tool records it. Priority, on Jira Service Management, Freshdesk, and Intercom. Unclassified volume, reported as its own number.

Intake detects rather than assumes. Instances differ. On the first queue this ran against, the request type field was empty on all 7,236 contacts and components carried the taxonomy, and 199 contacts carried no classification at all while every one of them was still open. Copious reports which field it classified on and how much of the queue is carrying nothing, before it rules on anything.

Handoff count alone predicts whether a class of work will miss its target. On that queue, contacts passing through one or two pairs of hands missed a 24 hour target 16 percent of the time. Contacts passing through six or more missed it 92 percent of the time. No ticket contents were read to establish that.

It never stores, logs, or analyzes ticket subjects, customer messages, comments, internal notes, attachments, requester identity, or any free text custom field. Freshdesk and Intercom return subjects and message text with every ticket whether asked or not; the connector drops that text on arrival. This is enforced by a hardcoded field allowlist at the ingestion boundary, not by a setting.