Pilots stay disconnected
AI experiments create interest, but they often sit outside the systems where work is actually done.
Evolving platforms into intelligent ecosystems
OutSystems AI in Action
Move from AI pilots to governed AI-enabled workflows.
ExoSystems powered by Indigo helps enterprise teams identify where AI can support real work, then connect those opportunities to workflows, data, oversight and enterprise delivery discipline.
Recognised OutSystems Partner Capability
ExoSystems powered by Indigo
Indigo
8 countries | 100+ consultants | 400+ certifications
Enterprise sectors including financial services, telecommunications, healthcare, retail, logistics, manufacturing, energy/utilities and insurance.
The AI production gap
The challenge is not a shortage of AI ideas. It is production readiness.
Most enterprises already have experiments, tools or executive pressure. The hard part is choosing the use cases that are safe, useful and ready to become part of everyday work.
Workflows are unclear
Value stalls when no one has defined the owner, handoff, decision point or next action.
Governance arrives too late
AI becomes harder to scale when controls, oversight and measurement are added after the fact.
Practical AI use cases
Where AI can support real enterprise work.
Start where the workflow is visible, the value is measurable and the governance model can be designed clearly.
AI-assisted delivery
Improve speed, quality and iteration while keeping engineering discipline in place.
Intelligent workflow support
Recommend, summarise, route or trigger actions inside defined business processes.
Service and case orchestration
Support document-heavy, request-heavy or claims-heavy work with better context and flow.
Agent-enabled operations
Introduce agents where roles, permissions, actions and escalation points are clearly defined.
Governed AI conditions
What makes an AI use case governable?
A governed AI use case is connected to clear work, clear ownership and clear controls before it moves into production.
Workflow ownership
Someone owns the process, decision path and outcome.
Data boundaries
The data source, access and usage limits are defined.
Human oversight
Review, approval and escalation rules are built in where needed.
Enterprise integration
The AI output connects to the systems where action happens.
AI readiness diagnostic
Five questions before AI moves closer to production.
Use these questions to test whether an AI idea is ready for a serious workflow conversation.
Readiness questions
- Which workflow, decision or action will AI support?
- What data does the AI need, and who owns it?
- What happens after the AI output is produced?
- Where is human review required?
- How will value, risk and adoption be measured?
Proof preview
Hollard: workflow modernisation proof to explore further
Keep the proof compact on this page. Use the full approved customer story in Insights so visitors can explore the challenge, approach, solution and outcomes in one place.
Explore more proof in InsightsStart with readiness
Find the first AI workflow that is valuable, safe and ready enough to pursue.
Book an AI Readiness Review to clarify the use case, workflow, data, oversight and production conditions before you invest in another disconnected pilot.