First Engagement

AI Platform Readiness Sprint

A focused 1–2 week technical assessment that maps your current AI usage, cloud environment, risks, architecture options, cost controls, and implementation roadmap.

Book a Readiness Call View What's Included

Before Building

Before building an AI platform, understand what needs to be controlled

Many organizations are already using AI, but few have a clear view of the infrastructure, security, governance, and cost implications.

The Readiness Sprint helps answer

?Which teams are using AI today?
?Which tools and models are being used?
?Where could sensitive data be exposed?
?Which cloud platforms should be involved?
?Is an AI gateway needed?
?What should be logged?
?How should usage and costs be attributed?
?What is required before moving AI into production?
?Which architecture should be built first?

Fit

Who this sprint is for

This engagement is designed for companies that:

✓Have AI pilots but no production architecture
✓Are concerned about shadow AI usage
✓Need secure model access across teams
✓Want to build internal AI assistants or RAG systems
✓Need better AI cost visibility
✓Use AWS, Azure, GCP, or private infrastructure
✓Need a technical roadmap for governed AI adoption
✓Want to prepare for GDPR and EU AI Act expectations

Scope

What is included

Current-state discovery

Review current AI usage, cloud environments, teams, data flows, and existing controls.

Cloud and infrastructure review

Assess AWS, Azure, GCP, private infrastructure, identity, networking, logging, and deployment readiness.

Security and data risk assessment

Identify sensitive data risks, uncontrolled access patterns, missing audit trails, and governance gaps.

AI access architecture

Define whether the company needs an AI gateway, model routing, provider abstraction, quotas, and policy controls.

Cost control review

Assess AI usage visibility, cost attribution, token spend, provider selection, and FinOps requirements.

Target architecture

Create a practical architecture direction for secure AI adoption across the relevant cloud and private environments.

Implementation roadmap

Prioritize the next steps into a clear roadmap that technical and leadership teams can act on.

Outputs

Sprint deliverables

At the end of the sprint, you receive:

✓AI Platform Readiness Report
✓Current AI usage and risk map
✓Cloud architecture review
✓Security and governance gap analysis
✓AI cost control recommendations
✓Target architecture diagram
✓Prioritized implementation roadmap
✓Recommended next-phase implementation plan

Format

Engagement format

Duration

1–2 weeks

Format

Remote-first, with structured discovery sessions and technical review.

Typical Participants

CTOCIOHead of CloudHead of EngineeringSecurity leadData/AI leadProduct leadPlatform or DevOps team

Investment

Pricing

The AI Platform Readiness Sprint is offered in three levels depending on company size, complexity, and required depth.

Entry Sprint

From €4,500

Best for smaller SMEs or focused use cases.

Includes

✓Focused discovery
✓AI usage review
✓Basic risk assessment
✓Target architecture recommendation
✓Short roadmap

1 weekGet Started

Standard Sprint

From €7,500

Best default option for companies preparing for production AI adoption.

Includes

✓Technical discovery
✓Cloud architecture review
✓AI usage and risk assessment
✓Security and governance gap analysis
✓Cost control review
✓Target architecture
✓Implementation roadmap
✓Final report and presentation

1–2 weeksGet Started

Advanced Sprint

From €15,000

Best for larger, multi-team, regulated, or multi-cloud environments.

Includes

✓Multi-team discovery
✓Multi-cloud infrastructure review
✓AI governance readiness review
✓Cost and observability recommendations
✓Detailed implementation backlog
✓Leadership presentation

2–3 weeksGet Started

Why Here First

Why start with a readiness sprint?

A readiness sprint reduces risk before implementation begins.

Instead of building another isolated AI pilot, your team gets a clear view of the architecture, controls, cost model, and implementation sequence needed for secure AI adoption.

The sprint can lead naturally into

→Multi-Cloud AI Gateway MVP
→Secure RAG Platform Foundation
→AI FinOps & Cost Control Audit
→Private AI / Hybrid Inference Deployment
→Managed AI Platform Operations

AI Platform Readiness Sprint

Before building an AI platform, understand what needs to be controlled

Who this sprint is for

What is included

Current-state discovery

Cloud and infrastructure review

Security and data risk assessment

AI access architecture

Cost control review

Target architecture

Implementation roadmap

Sprint deliverables

Engagement format

Pricing

Why start with a readiness sprint?

Get a clear roadmap for secure AI adoption