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Why AI pilots fail to reach production

AI initiatives fail to scale not because the technology is immature, but because the first engagement lacks scope discipline, measurable outcomes, and governance from the start. A well-designed agent needs a defined workflow, grounded enterprise data, identity and access controls, and an operational monitoring model — not a demonstration that works in isolation.
 
Without production discipline in the first engagement, organisations accumulate pilots that cannot be expanded, defended to leadership, or connected to the rest of the AI estate.
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AI stuck in workshops

Proofs of concept impress stakeholders but never connect to real business processes or measurable outcomes.

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Governance added too late

Agents built without identity, data access controls, and evaluation frameworks create risk at scale.

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No path to expansion

First agents that lack a documented architecture and adoption baseline cannot be reused or extended to additional processes.

What you receive

 

 

 From idea to production in six weeks

AI-Ready Data (2)
Phase 1 — Select (Week 1)

Define the business process, confirm the executive sponsor, agree the success metric and value baseline, and complete the workflow mapping including users, systems, data sources, exceptions, and human approval points.

AI-Ready Data (3)
Phase 2 — Design (Weeks 1–2)

Design the agent architecture, grounding approach, evaluation model, and security controls. Confirm the integration points and data access model with the customer's technology and security teams.

AI-Ready Data (4)
Phase 3 — Build (Weeks 2–5)

Build the agent using Microsoft Foundry and Copilot Studio. Integrate with the customer's data and applications. Implement responsible AI guardrails, identity controls, data access policies, evaluation, and operational monitoring.

AI-Ready Data (5)
Phase 4 — Launch (Week 6)

Deploy the working agent into a controlled production environment. Establish the adoption and value baseline. Confirm the scale roadmap covering additional agents, Fabric grounding, application modernisation, and managed agent operations.

Built on Microsoft

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Azure AI Foundry
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Azure OpenAI
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Copilot Studio
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Microsoft 365 Copilot
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Microsoft Fabric
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Microsoft Entra
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Microsoft Purview
  • Business Outcomes
  • Microsoft funding may apply
  • Why ALIANDO
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  • One AI agent running in real production by week six
  • Measurable business outcome agreed at scope, confirmed at launch
  • Repeatable governance model for future agents
  • Architecture that supports Fabric grounding and multi-agent expansion
  • Documented adoption baseline for leadership reporting
  • Clear path to ALIANDO Managed Agent Operations
ALIANDO will assess eligibility for Agentic AI Platform incentives, AI Apps & Agents nominations, and applicable ECIF or Frontier Accelerate funding at the scoping stage. Funding is subject to Microsoft eligibility, customer criteria, nomination, and proof-of-execution requirements.
  • Bounded, deliverable-first engagements — scope is fixed before the engagement starts
  • Governance from day one — identity, data access, evaluation, and monitoring are built in, not added later
  • Microsoft Foundry and Copilot Studio delivery capability across multi-country programmes
  • Experience in multi-agent insurance AI programmes spanning claims and related service processes
  • Optional transition to ALIANDO Managed Agent Operations following a successful launch
  • Microsoft Azure Expert MSP with Solutions Partner designations across Data & AI and Digital & App Innovation