How we take Agentic AI from use case to production.

A phased methodology — Discover, Pilot, Productionize, Scale — with governance designed in at every step. We start bounded, prove value, and expand only once a workflow is live and trusted.

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01

Discover

Find the right first workflow.

We identify high-value workflows, business outcomes, systems, and data needs before any build begins. The strongest starting point is a bounded workflow with high volume, clear handoffs, and a measurable baseline.

✓Workflow and use-case discovery
✓Outcome and success-metric definition
✓Systems, data, and integration assessment
✓Governance and compliance requirements

02

Pilot

Prove it on real workflows.

We build practical demos and pilots tied to real workflows, stakeholder priorities, and enterprise data patterns — with human review and guardrails in place, evaluated before anything reaches production.

✓Demo and pilot development on watsonx
✓Representative data and simulated systems
✓Pre-deployment evaluation and guardrails
✓Stakeholder review and sign-off

03

Productionize

Integrate, govern, deploy.

We connect agents to systems of record, design approval flows and auditability, and move pilots into reliable, scalable environments with identity, runbooks, monitoring, and operational handoff.

✓Enterprise integration (modern & legacy)
✓Governance, audit trails, and access controls
✓Production deployment with observability
✓Runbooks and operational handoff

04

Scale

Expand once it's trusted.

Once the first workflow is live and trusted, we expand to additional workflows and teams with post-launch optimization, adoption support, training, and ongoing managed support.

✓Expansion to new workflows and teams
✓Adoption support and training
✓Ongoing optimization and tuning
✓Managed support and governance reviews

What you get & governance by phase

Outputs and governance checkpoints, phase by phase.

Phase	What you get	Governance checkpoint
Discover	Prioritized use case, workflow map, success criteria, systems/data assessment, governance requirements	Identify data sensitivity, access needs, compliance requirements, and approval points
Pilot	Working demo or pilot, stakeholder feedback, guardrails, production-readiness findings	Test agent behavior, human review, outputs, tool use, and exception paths
Productionize	Integrated workflow, access model, auditability, monitoring, runbook, deployment support	Validate permissions, audit trails, monitoring, escalation paths, and support ownership
Scale	Managed support, optimization, user adoption support, governance review, expansion roadmap	Review adoption, access, governance, performance, cost, and expansion readiness

Where to start

What makes a strong first use case.

The best first Agentic AI use case is focused enough to move quickly and valuable enough to prove business impact. Strong starting points usually have:

✓A clear business owner

✓A defined workflow

✓High-volume or repetitive work

✓Available systems, data, or documents

✓Clear handoffs between users or teams

✓A measurable baseline

✓Manageable governance requirements

✓A path to expand after the first deployment

Methodology FAQ.

How does Incede.ai approach an Agentic AI implementation?

We follow a phased methodology — Discover, Pilot, Productionize, Scale. We start with a bounded use case and a measurable baseline, prove it in a governed pilot, move it to production with integration and observability, then expand once it's live and trusted.

How long does each phase take?

Most first workflows move from discovery to governed production in 4–12 weeks, depending on integration depth and data readiness. Discovery is typically a short, focused engagement; Scale is ongoing as adoption stabilizes.

Where does governance fit in the methodology?

Governance is designed in from Discovery, not bolted on at the end. We capture compliance requirements up front, evaluate agents before production, and deploy with audit trails, access controls, guardrails, and observability using IBM watsonx.governance.

Do we have to commit to a full program up front?

No. We define scope, deliverables, timeline, integration requirements, and success criteria during Discovery — before implementation begins. Most customers start with one bounded workflow and expand only after it's live and delivering value.

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