Enterprise data to advance frontier AI
License the workflows and operational know-how your company already runs on to the AI labs building the next generation of models. You keep ownership, you see everything before it is used, and you get paid.
License the data you already generate
You set the scope and approve a sample before anything is used. Appen handles the extraction, the anonymisation and the conversations with the labs.
Permissioned enterprise data
Enterprise sourced data from a wide-range of enterprises, covering different environments, industries and time-horizons
What the labs are asking us for
Enterprise task competence
Agents are being asked to file the claim, close the month, route the escalation. Public text has the outcome. It does not have the approval chain that produced it.
Failure and recovery paths
The reopened ticket, the rejected approval, the reconciliation that did not balance the first time. Exception paths are where models break, and where the training signal is strongest.
The reasoning behind the decision
Records show what was decided, rarely why. We can pair licensed data with annotation from the people who did the work.
Three categories of operational data
Not every system holds licensable value. These are the three we scope against. Select one to see what sits inside it.
How the work is supposed to be done
Procedures, knowledge bases and templates that define how a task is meant to run, including the exceptions nobody ever wrote into the official version.
- Process definitions and dependencies
- Revision history and rationale
- Exception and edge-case handling
- Role-based permissions and hand-offs
How the work is actually decided
The systems where process is enforced rather than described. What matters here is the reopened ticket, the rejected approval, the deal that needed a second signature.
- Approval and exception chains
- Stage transitions with stated reasons
- Escalation and hand-off paths
- Resolution outcomes and rework
The structured truth underneath
Warehouses, ledgers and contracts as they really are, with the naming drift, inconsistent keys and negotiated exceptions of a live business rather than a tidy demo schema.
- Reconciliations and adjustments
- Executed agreements and redlines
- Schema drift and join logic
- Reporting and query lineage
We are not asking for open access to your systems
Every engagement is scoped before anything moves, and the exclusions you set are enforced in the pipeline, not only in the agreement.
Scope you define
You name the systems, teams, workflows and time periods in scope. Nothing outside that list is read.
Isolated pipelines
Read-only, encrypted in transit, credentials scoped per engagement. Your data is never commingled with another partner's.
Anonymisation by default
Personal data is detected and removed, with synthetic rewrite where workflow structure has to survive the redaction.
Your sign-off, or no use
You review a representative sample pack before anything is licensed. Nothing is used without that sign-off, and you keep ownership throughout.
What determines the price
Terms are agreed in writing before extraction begins, and payment is on acceptance rather than submission. Appen covers extraction, anonymisation and transfer, so there are no costs to you.
Uniqueness
How rare the operational knowledge is, and whether it exists anywhere else.
Structural depth
Connected systems are worth more than isolated exports, because value compounds where records reference each other.
Volume and longevity
How much there is, and how far back it goes. A decade of records is worth more than a single quarter of the same thing.
Tell us what your company runs on
Two minutes now saves a discovery call. Everything you share is treated as confidential, and nothing is discussed further before a mutual NDA is in place.
- Reviewed by the partnerships team, not an inbox
- Response within two business days
- Winding down? Flag it below and we prioritise the response