Progress · AI · Intelligence in production
Workflow AI
Place a Programmable Data Agent inside the production architecture, so heritage applications embed intelligence without being rewritten or rearchitected.
The problem
AI sits beside the workflow rather than inside it.
Most of the value of AI sits inside the workflow: in the applications people already use to serve customers, approve payments and run operations. Those applications were not built to call a model.
Rewriting or rearchitecting them to do so is slow, costly and risky for systems that must keep running. The result is AI that sits beside the workflow rather than inside it.
What Data Mediation changes
Intelligence embedded in heritage applications, with no rewriting or rearchitecture.
A Programmable Data Agent placed inside the production systems architecture becomes a trusted Data Mediation point in the path of the workflow. It can enrich a request with a model’s output, route a decision to an approved model, apply a recommendation or hold an action for review before it reaches the application.
The application keeps working as it does today, with no changes to its code, no rearchitecture and no new dependency on any one model. Smaller models can run within the Programmable Data Agent itself; others are reached through the same point, by policy. Intelligence and innovation flow back into the systems people already trust.
What it does
Intelligence in production.
Enrich
A request gains a model’s output before the application sees it.
Route
Decisions go to an approved model, external or local, chosen by policy.
Hold
An action can wait for review before it reaches the application.
Prove
Every decision the intelligence influenced is recorded.
Approach
How Data Mediation is applied
- 01
Choose a workflow where intelligence would change the outcome.
- 02
Place a Programmable Data Agent where that workflow’s data passes through the production architecture.
- 03
Compose the intelligence: approved models, rules and policies, applied in the path.
- 04
Start in Listen Only, then move to Active as confidence grows.
Evidence
What can be demonstrated
- Intelligence embedded in a live workflow with no application change
- Approved models chosen by policy, external or local
- Listen Only before any action is altered
- Evidence of every decision the intelligence influenced
The exact scope, controls and evidence depend on the customer environment and are agreed before implementation.
Built for
For chief AI officers, chief technology officers and the owners of critical workflows.
Works with
- Data Connection
- Governed AI access to enterprise systems
- Any approved model, external or local, chosen by policy
Plans
Start with one workflow and one decision that intelligence would improve.
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