Service / Agentic AI as a Service

Agent Strategy & Portfolio

Identify where agentic AI can create measurable value without exceeding organizational risk appetite.

Business context

What this capability solves

Organizations often start with agent technology before defining the right business problems, action boundaries and accountability. The strategy service creates a prioritized agent portfolio and target operating model.

EBP Integra delivery principle

Technology is implemented as an operating capability: architecture, integration, governance, assurance, people, procedures and measurable outcomes are designed together.

Deep-dive capabilities

Capability model

Modular building blocks allow the scope to start with a focused pilot and expand into an enterprise operating model.

Opportunity Discovery

Map repetitive, knowledge-intensive and cross-system workflows suitable for agentic automation.

Value / Feasibility Scoring

Score benefits, data/tool readiness, integration effort, autonomy and operational risk.

Agent Portfolio

Define agent purpose, owner, users, tools, decisions, inputs/outputs and lifecycle.

Risk Tiering

Classify by autonomy, data sensitivity, financial/physical impact and external exposure.

Target Operating Model

Define AI owner, business owner, security, risk, legal, operations and approval roles.

Roadmap

Sequence pilots, AAIOS foundation, integration and scale-out waves.

Reference architecture

How the capability fits together

Final topology, control placement and deployment model are validated during discovery and detailed design.

Business & Agent Portfolio

Use cases, agent owners, risk tiers, process boundaries and value hypotheses.

AAIOS Control Plane

Agent registry, orchestration, identity, policy, approvals, memory, tool/model gateways and evaluation.

Enterprise Execution

Models, RAG, APIs, SaaS, databases, workflows and sandboxed agent runtimes.

AgentOps

Observability, SLOs, cost, incident handling, kill switch, evidence and continuous optimization.

Controls & governance

Least-privilege agent/workload identity
Human approval for high-impact actions
Approved tool schemas and transaction validation
Data classification/DLP at model and tool boundaries
Memory retention and deletion policy
Comprehensive traces and action provenance
Evaluation gates before production
Kill switch, rollback and incident escalation

Priority use cases

Enterprise agent roadmap
Business process automation portfolio
AI operating model
Agentic AI investment case
Department-level automation strategy

Key deliverables

Opportunity heatmap
Prioritized agent portfolio
Risk-tier model
Business case
AAIOS target architecture
12–18 month roadmap

Integration considerations

AAIOS
Enterprise IAM/workload identity
APIs and SaaS systems
Data platform and RAG/vector stores
Workflow/BPM/ITSM
SIEM/SOAR and observability
GRC/evidence systems
Model endpoints/gateways

Implementation

Phased delivery

Each phase ends with evidence, acceptance criteria and a decision gate before broader scale-out.

1. SelectPrioritize workflows by value, feasibility, risk and data/tool readiness.

2. EngineerDesign agents, tools, RAG, policy, human checkpoints and AAIOS runtime.

3. AssureSimulate, evaluate, red-team, approve and define SLOs.

4. OperateRun through AgentOps, manage incidents and continuously optimize.

Outcome and KPI framework

Value realizedPilot conversion rateTime-to-prioritizePortfolio risk distributionAgent adoption