Progress · AI · Data for Workflow AI
Data Connection
Connect data across heritage systems, live and in place, so it can take part in Workflow AI without systems integration.
The problem
The distance between where intelligence runs and where the data lives becomes the constraint.
The data AI needs most sits across heritage systems built over decades, each with its own protocol, data model, release cycle and owner. Decades of human decisions and data live there, and that is where the value of the AI-enabled enterprise is.
Connecting those systems through conventional integration means long projects, new point-to-point dependencies and copies of data that drift out of date. As AI moves into private, hybrid and sovereign environments, the distance between where intelligence runs and where the data lives becomes the constraint.
What Data Mediation changes
Data across heritage systems connected live and in place, without systems integration.
A Data Mediation point connects to each system on its own terms, across any protocol, and presents the data live and in place in the form each workflow needs. Mapping, policy and orchestration sit outside the systems, so neither side is rewritten and nothing is copied by default.
Data is governed on the way: redacted, tokenised or abstracted, so a date of birth can arrive as adult or child. Business analysts and data analysts connect the data, because they are closest to the problem and the sources. Not SaaS: it runs inside the organisation’s own environment and nothing is sent to TomorrowX.
What it does
Data for Workflow AI.
Connect
Each source on its existing protocol, read-only to begin with.
Shape
Data redacted, tokenised or abstracted on the way.
Present
Governed, live data for Workflow AI, agents and models.
Record
Evidence of what was requested, shaped and returned.
Approach
How Data Mediation is applied
- 01
Place a Programmable Data Agent in front of the systems that hold the data.
- 02
Connect each source on its existing protocol, read-only to begin with.
- 03
Define the data each workflow may use and how it is shaped on the way.
- 04
Present governed, live data to Workflow AI, agents and models, with a record of every exchange.
Evidence
What can be demonstrated
- Data from two or more heritage systems presented together, live and in place
- No change to the source systems and no systems integration project
- Data abstraction applied in motion, such as date of birth to adult or child
- A record of what was requested, shaped and returned
The exact scope, controls and evidence depend on the customer environment and are agreed before implementation.
Built for
For chief data officers, enterprise architects and the business and data analysts closest to the sources.
Works with
- Workflow AI
- Controlled and sovereign data movement
- Any protocol: each source is connected on its existing protocol
Plans
Start with one workflow and the systems that hold its data.
TomorrowX licenses its software through selected partners, who configure, deliver and support it. US public-sector customers buy through Carahsoft.
Proof of value
A week to know: proven on the organisation’s own data and use case.
Contact sales →Listen Only
Full visibility at a Data Mediation point. Observes; never blocks or alters.
Contact sales →Active
Policy enforced at the Data Mediation point.
Contact sales →Additional Data Mediation points
The same approach extended as adoption grows.
Contact sales →
Partners and customers
Delivered through partners. Proven with customers.
Services, marketplace and public-sector partners deliver Data Mediation, with OEM and managed-service models available. TomorrowX also engages directly with selected customers on world-first deployments and research activities.
Partners and delivery models → · Enterprise history and customers →
From the library
The full library →Next in Progress · AI