Customer Support
Use a high-quality model for escalations and a low-cost model for first-pass triage.
Practical use cases with realistic model selection patterns.
Current stacks (April 8, 2026): Combine GPT-5 Turbo (live data access + video) with Claude 4.5 Sonnet (2M tokens) for premium tier; o3-mini, Gemini 2.5 Flash, or Gemma 4 for high-volume; Grok-3, Llama 4.1 Scout, Llama 4.2 Adventurer, Gemma 4, DeepSeek R1.5, or Mistral 8B for private and cost-optimized deployments. Recent pricing cuts make multi-tier stacking more economical. Llama 4.2 Adventurer brings visual reasoning to private deployments. Copyright compliance checklist: training data provenance and fair use audits now part of standard RFP process.
Use a high-quality model for escalations and a low-cost model for first-pass triage.
Use top coding-capable models for implementation and refactoring assistants with policy filters.
Batch summarize tickets, invoices, and updates with cost-optimized models and strict validation. Gemma 4 is a strong option when teams want lower-cost private inference.
Prefer high-context, careful models with auditable prompts and human-in-the-loop approval.
Use de-identification pipelines and model gating. Keep clinical decision-making outside autonomous LLM action.
Use retrieval + deterministic validators to reduce hallucinations in reports and internal analyses.