For enterprise owners and service operators
Support and evolve the estate you are responsible for.
Bring routine support, server investigation, design, and change delivery into one operating approach. FORGE equips your AI and team to work across authorised TRIRIGA instances, from the first incident through approved implementation and release.
Owner outcomes
Make the estate explainable before the next programme depends on it.
Recover estate knowledge
Turn live configuration and runtime evidence into a navigable map that is not locked in one person, one supplier, or an old spreadsheet.
Put evidence before change
Trace dependencies across fields, business objects, workflows, forms, reports, and integrations before approving a change.
Prepare migration assurance
Inventory customisations and integration risk, then define the readback evidence needed after the move to MREF.
Control the AI boundary
Choose who operates the AI and tooling layers, approve a narrow tool surface, and retain the customer TRIRIGA environment as the system of record.
For multi-estate service operators
Standardise the investigation method, not the customer.
Give distributed teams a consistent way to orient, investigate, evidence, and hand over work across client estates while each customer's identity, environment, data, and approval boundary remains explicit.
Architecture and procurement
Answer the questions security and procurement teams ask first.
Can we move support work from an external supplier into our team?
FORGE can equip your team to take on routine investigation, diagnosis, proposal and design preparation, and supported implementation and release work. Start by mapping the support backlog and recurring changes to tool coverage. Agree the responsibilities, escalation path, production access, and service hours before transferring the work. Infrastructure operations and specialist coverage remain explicitly assigned.
What can the service reach?
The approved tool list and the dedicated TRIRIGA integration identity together define the maximum reachable scope for the named environment.
Where can our data flow?
Data flow depends on the selected deployment model. Hosted models can process tool arguments, results, and audit metadata in AJAEX infrastructure; the managed model can also involve the selected AI provider.
Can we keep operational control?
Customer Private is available through design-partner engagements for customer-operated infrastructure. Licensing, updates, support, telemetry, recovery, and artifact responsibilities are defined for each engagement.
How is vendor risk reduced?
Vendor-risk assessment covers ownership, portability, versioned artifacts, update and rollback paths, support responsibilities, and deployment control. Evidence is assessed for the selected service.
Can it change production?
Production access is considered only through an explicitly designed and approved scope. Initial engagements are typically limited to one non-production environment and a read-oriented tool set.
What proof do we receive?
An engagement-specific evidence pack can cover tool scope, architecture, data flow, test records, release identity, results, known limitations, and agreed success criteria.
Deployment choice
Choose the responsibility boundary that fits the organisation.
Bring your AI
Customer AI / AJAEX Tooling
Organisations that already have an approved AI client or model account.
Managed workspace
AJAEX Managed
Teams that want one managed workspace and a single service boundary.
Private edition
Customer Private
Regulated, sovereign, isolated, or customer-operated environments.
Low-risk entry
Make the first decision small enough to verify.
01
Architecture and estate fit
The fit review covers relevant versions, environments, use case, data boundary, AI approach, security requirements, and procurement constraints.
02
Bounded paid pilot
Choose one non-production environment, one named outcome, an explicit tool allow-list, success criteria, and a fixed end date.
03
Evidence-led production decision
Any move beyond the pilot depends on the relevant security, support, operational, and commercial requirements being agreed.
Start with setup and a four-week Customer AI pilot, with scope and pricing agreed in a proposal. Agree one outcome, review the evidence against your success criteria, and decide whether wider use is justified. Review the pilot and included scope.
Start with one estate and one decision that matters.
Bring a specific upgrade, dependency, customisation, integration, mobilisation, or change-control question. We will define the evidence needed to make the next decision.