Tealith Cloud · AI · Data
AI models and infrastructure for your application.
Choose a model and deployment approach around your task, data boundaries, latency needs and usage budget.
Model selection and evaluation
Define representative tasks and evaluation examples before selecting a model. Compare output quality, modality support, response time and cost using your application requirements.
APIs and application integration
Model API integration can support text, image, audio and other workflows. Plan authentication, routing, error handling and usage measurement when connecting models to enterprise applications or agents.
Dedicated inference and GPU infrastructure
Consider dedicated endpoints or GPU resources when workloads need predictable capacity or a specific deployment boundary. Size resources around the model, workload and throughput requirements.
Usage and cost governance
Track model usage and evaluate the cost of each workflow. Set operating limits and review model choices as task requirements and workloads evolve.