Token Hub
Access models
Assess model access through Token Hub when an existing model can support the use case.
Application → Token Hub
AI / ML Services
Take an AI use case from concept toward production
AI/ML project services connect the use case with GPU, Token Hub and Storage as needed. Begin with the use case, data and evaluation criteria. Then assess whether model access through Token Hub is sufficient or GPU-based training and serving are needed.
- 01
Use case & data
Define the task and available data.
- 02
Choose a model approach
Token Hub or GPU, based on project needs.
- 03
Evaluate the result
Compare results with agreed success criteria.
- 04
Plan for production
Assess storage, integration and operating cost.
A project planning flow, not a live AI system.
Ruk-Com Agent
Agent support across every service
Working with our specialists across Technology and Cyber Security: monitoring, anomaly analysis, planning and coordinated response.
Technology · Performance, capacity and operations
Cyber Security · Risk, vulnerabilities and threat monitoring
Data access, changes and support levels follow the permissions and service scope agreed with our team.
Meet Ruk-Com AgentAI / ML · SOLUTION DESIGN
Choose the model approach before the machine size
AI does not always need to start with a GPU. Our team assesses the use case, data and evaluation criteria to plan an approach around your needs and cost.
These are alternative approaches to assess, not mandatory consecutive steps for every project.
Service details
Define AI evaluation around a real business problem
AI/ML project services connect the use case with GPU, Token Hub and Storage as needed. Begin with the use case, data and evaluation criteria. Then assess whether model access through Token Hub is sufficient or GPU-based training and serving are needed.
GPU
Assess compute for training or model serving when the workload calls for GPUs.
Token Hub
Connect model access to the project use case and assess options before infrastructure investment.
Storage
Plan project data storage and its integration with your existing systems.
Evaluation & integration
Agree evaluation criteria and integration scope before moving toward production.
Plan before you start
- Which business problem should AI solve?
- How ready is your data?
- How will success be measured?
Should I buy GPU capacity before defining the AI project?
Begin with the use case, data and evaluation criteria. Then assess whether model access through Token Hub is sufficient or GPU-based training and serving are needed.
What should I prepare for a AI / ML Services assessment?
Prepare answers to: Which business problem should AI solve? How ready is your data? How will success be measured? This helps the team propose the right scope and costs.