Stop piloting AI.
Start Scaling It.
/01 THE SCALING PROBLEM
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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.
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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.
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.
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.
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.
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
Tier 2
Tier 3
The core principle
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.
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:
One policy layer for every team
- No team rebuilds guardrails from scratch
- Policy enforced at runtime, not in a doc
- MCP governance by inherited constraints
- Tools approved by AI governance board
ACCESS CONTROL
- Deployed in customers own AWS account
- Agent identities and data boundaries travel with the workload
- Integrated with customers native IAM solutions
- Scoped access to customers Data Platform
- Fallback across regions instead of models
- Centralize routing, rate limiting and response caching
- Set up a 2-tier platform to democratize agent development
- One view across every running agent
- Performance monitoring and alerting
- Cost and drift anomalies tracked live
- Quality of output measured at runtime
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
- Platform updates and improvements
- Platform monitoring (cost, uptime, performance, anomalies)
- SLA on incident response time
- Incident triage and escalation
BASIC
Business Hours
COVERAGE
9:00-17:00 CET
RESPONSE TIME
90 min
AGENTS INCLUDED
0
Controlled rollout · daytime coverage
Production grade
COVERAGE
15/7
7:00-23:00 CET
RESPONSE TIME
60 min
AGENTS INCLUDED
5
Production-grade · extended hours
COVERAGE
24/7
365
RESPONSE TIME
60 min
AGENTS INCLUDED
10
Mission-critical · full coverage
MANAGED AGENTIC AI PLATFORM

Setup
One-off setup and configuration
- Agentic AI Platform setup
- Orchestration agent
- Identity integration configuration
- Infrastructure as code
- Knowledge base setup

- Service desk 9/5 - 15/7 – 24/7
- Continuous optimization
- Feature add-ons
- Performance monitoring
- Standard service requests

- Deploy autonomous agents
- Full security and access control
- Basic governance and compliance
- Source code access
Don’t just take our word for it.
Check our selected case studies.














Let’s start with a quick value assessment.
Introduction Meeting