Stop piloting AI.
Start Scaling It.

A strategic white paper on building an enterprise-grade Agentic AI platform with AWS AgentCore

/01 THE SCALING PROBLEM

Five Challenges Every CTO Recognises

There are five challenges that come up every time we talk to a CTO about scaling AI in a large organisation.

Governing the Ungoverned

You’re already accountable for AI initiatives running in your organisation that you don’t know about. Shadow AI is growing faster than any governance framework can keep up with.

The Department of ‘NO’

Setting up guardrails and policies can make the CTO look like the blocker. But without them, you have no visibility, no control, and no audit trail. You’re trapped either way.

Data Readiness

AI is only as good as the data it can access. Most organisations aren’t where they think they are. The gap between data ambition and data reality is where most AI projects quietly die.

The Skills Gap

This isn’t about data science skills. It’s about the skills to work with AI at scale, embedded into daily workflow across every team — not just the AI centre of excellence.

Board Expectations

Risk protection on one side. Competitive advantage on the other. You are stuck in the middle, accountable for both, with a board that doesn’t want to hear that they’re in tension.

The bottom line

Those challenges don’t go away by running more pilots. They go away by building the right platform. And that’s where our solution comes in.

ROI & Business Case

The cost of inaction is well-documented. McKinsey’s “Seizing the Agentic AI Advantage” (June 2025) identifies what it calls the “gen AI paradox”: nearly 78% of companies have deployed gen AI in some form, yet roughly the same percentage report no material impact on earnings. The root cause is consistent, high-impact, function-specific use cases rarely make it out of the pilot phase due to technical, organisational, data, and cultural barriers. McKinsey finds that 90% of vertical AI use cases remain stuck in pilot stages. Nearly two-thirds of enterprises have experimented with agents, but fewer than 10% have scaled them to deliver tangible value.

Forrester is equally direct: 60% of enterprise AI projects will fail to scale without proper governance frameworks, and 75% of firms that attempt to build agentic architectures on their own will fail (Forrester Predictions 2025: AI). McKinsey adds that 80% of companies cite data limitations as the single biggest roadblock to scaling, directly compounding governance risk. The platform addresses each of these failure modes by design: governance inherited at runtime, data boundaries enforced at the identity layer, and full observability from day one.

Sources: McKinsey, “Seizing the Agentic AI Advantage,” June 2025; McKinsey, “Building the Foundations for Agentic AI at Scale,” April 2026; Gartner press release, June 2025; Forrester Predictions 2025: Artificial Intelligence.

/02 THE PLATFORM APPROACH

Build Once. Every Agent Inherits Everything.

The traditional approach to AI deployment creates technical debt by design: each team builds its own guardrails, each agent needs its own monitoring, each use case requires its own security review. The result is a sprawling portfolio of fragile, ungoverned AI — exactly the shadow IT problem that governance teams fear.

The Brighting Agentic AI Platform, built on AWS AgentCore, inverts this model. Instead of each agent reinventing the wheel, a shared platform layer provides every capability every agent will ever need — governance, identity, tooling, observability, and infrastructure — inherited automatically at runtime.

The core principle

Deploy the platform once. Every agent you build — today, next quarter, and next year — automatically inherits current and future platform capabilities. Your governance investment compounds over time, not linearly per agent.

What the platform enables

Concretely, this means you can finally say yes where you previously had to say no:

Redeploy shadow IT

Give teams a legitimate, governed space to bring AI initiatives in from the cold. Instead of ‘no’, say ‘yes — and here’s where to build it’.

Enforce policy at runtime

Governance guidelines enforced on the platform — not just written in a document. Every agent, every interaction, every team.

Expose tools securely

Make agents and internal tools available to the organisation in a controlled, auditable way. No more ungoverned API sprawl.

Report on everything that matters

Usage and adoption by department, security posture, performance metrics, cost attribution. Full visibility, always on.

Three Types of Agents

The platform serves as a central orchestration layer through which all agent interactions are routed and governed. It supports three types of agents — each with different build complexity, maintenance requirements, and ownership models:

Tier 1

Low-Code Agents

Built using low-code tools such as Gleam. Designed for business users and teams with limited engineering support. The platform governs and monitors these agents without requiring the builder to implement security or compliance controls themselves.

Tier 2

Custom-Built Agents

More advanced agents that require stronger engineering capabilities to develop, run, and maintain. Built on frameworks such as LangGraph, Haystack, LangChain, CrewAI, or bespoke orchestration. Brighting can design, build, and operate these agents as part of an engagement.

Tier 3

External SaaS Agents

Agents from third-party SaaS providers, integrated and exposed within the platform. These inherit platform governance automatically, so even externally built agents are subject to your policies, audit trails, and access controls.

The core principle

Deploy the platform once. Every agent, regardless of tier, team, or builder, automatically inherits current and future platform capabilities. Your governance investment compounds over time, not linearly per agent.

Retail & Commerce Context

For retail and omnichannel organisations, the platform unlocks a category of AI use cases that cannot be safely operated in isolation: inventory and replenishment agents that act on live ERP data, personalisation agents with access to customer profiles, and order management agents that span OMS, WMS, and fulfilment systems. Each of these requires exactly the governance, identity scoping, and audit capability the platform provides — deployed once, inherited by every agent.

Brighting holds the AWS Retail Competency — one of a small number of firms globally to do so — and combines this with deep Composable Commerce and MACH architecture expertise. For retail and CPG enterprises already on a headless or composable journey, the Agentic AI Platform is a natural extension: agents that orchestrate across your commerce stack, governed by the same platform that governs everything else.

/03 PLATFORM ARCHITECTURE

Enterprise-Grade from Day One

The platform is deployed as Terraform Infrastructure as Code (IaC) into the customer’s own AWS account. It carries a perpetual license and is designed with zero vendor lock-in. The architecture provides eight core capabilities:

Agent Identity

Per-agent scoped tokens with IdP integration for enterprise identity providers (Azure AD, Okta, AWS IAM).

MCP Tool Gateway

All APIs and internal services exposed as governed MCP tools through a single shared catalog, approved by your AI governance board.

Serverless Runtime

Framework-agnostic execution supporting LangChain, CrewAI, custom agents, and more. Auto-scaling deployment on AWS Lambda and Fargate.

Failover & Routing

Automatic failover across LLM providers and regions. Model tier routing matched to task complexity, cost-optimised by default.

Cost & Allocation

Per-department and per-agent token spend tracking, budget alerts, and model cost attribution.

Full Observability

OTEL-compatible traces, tool call logs, quality metrics, and dashboards per agent. One control tower for everything.

Managed Guardrails

Bedrock-native content safety, PII detection, topic denial, custom rules, and quality guardrails.

Agent Portal

Discover, interact, manage, and govern agents through one role-scoped interface.

GOVERNANCE

One policy layer for every team

ACCESS CONTROL

A safe place for data and agents

INFRASTRUCTURE

Compute that scales with demand

OBSERVABILITY

Your control tower for AI Agents

It’s your Enterprise Grade AI Agent platform which delivers:

AGENT
IDENTITY

Per-agent scoped tokens with IdP integration for enterprise identity providers

MCP TOOL GATEWAY

All APIs and services exposed as governed MCP tools through a single shared catalog

SERVERLESS RUNTIME

Framework-agnostic execution supporting multiple orchestration approaches, with auto-scaling deployment on AWS

FAILOVER & ROUTING

Automatic failover across LLM providers and regions; model tier routing matched to task complexity

After agreement on the Platform Architecture and the core team is confirmed we start with the platform implementation. Duration 10 weeks.

Once implemented, you can either manage the platform internally or choose for us to provide ongoing support, optimisations and monitoring. This includes:

INCLUDED IN ALL PACKAGES