What AIRE assesses
AIRE reviews the AI workloads you actually need and the resources you already have before recommending new subscriptions, hardware or infrastructure.
Workload factors
- Task type and volume
- Required answer quality and model capability
- Latency and response-time needs
- Privacy and confidentiality
- Context size, storage and retrieval needs
- Languages and modalities such as text, vision or image generation
- Automation frequency and human review requirements
Resource factors
- Existing PCs, GPUs, servers and VPS resources
- Cloud subscriptions and API accounts
- Local models and software already installed
- Storage, datasets and knowledge bases
- Electricity, utilization and maintenance cost
- Staff capacity and technical skills
- Provider dependency and sovereignty requirements
Recommendation output
The outcome is a workload-to-resource map: which tasks should remain human, which can run on lightweight local models, which justify stronger cloud models, where hybrid routing makes sense, and where investment is actually justified.