The AI Platform Assessment is a focused paid engagement for teams that need clarity before they spend more money on AI infrastructure, agents, fine-tuning, inference or GPU capacity.
What we review
- Current AI architecture and production readiness
- Training, fine-tuning and inference workloads
- Data pipelines, model lifecycle and evaluation gaps
- Kubernetes, cloud and GPU infrastructure
- Agent architecture, MCP, tools and governance
- Reliability, observability, security and cost risks
- Build-vs-buy and vendor tradeoffs
- 90-day implementation roadmap
Typical output
- A written assessment of your current state
- Recommended target architecture
- Priority risks and bottlenecks
- Cost and performance opportunities
- Implementation roadmap with effort and impact
- Clear next-step options for pilot or build work
Frequently asked questions
Who is this assessment for?
It is for teams where AI has become an engineering problem: prototypes need to become platforms, GPU usage is expensive or unclear, agents need governance, or model workloads need to move into production.
How long does it take?
Most assessments take one to two weeks, depending on the number of systems, workloads and stakeholders involved.
What happens after the assessment?
You can use the roadmap internally, ask us to build the first pilot, or keep us involved as a specialist engineering partner for the platform work.
Ready to start? Book a scoping call and we will confirm whether the AI Platform Assessment is the right first step.