Find the model your workflow can actually run.
This planner turns vague AI interest into a practical recommendation: model class, cloud or self-hosted path, memory estimate, and next step for implementation.
Quick answer: The best AI model for a small business depends on task type, data sensitivity, request volume, context length, and available compute. A smaller local model can beat a premium API when the workflow is narrow, private, and repetitive.
1. What should AI handle first?
2. Where should it run?
3. Daily volume
4. Available compute
Llama 3.1 8B
Local support bots, RAG, private document work
Use MLX or Ollama and close memory-heavy apps before running long context windows.
This is a planning estimate, not a hardware guarantee. Final setup depends on documents, tools, uptime needs, and security rules.
How to read the result.
The selector is intentionally conservative. A model that fits in memory still needs workflow design, guardrails, data cleanup, and testing before it should touch real customer operations.
Model name
The model class we would start testing for your use case.
Run path
Cloud, local, or hybrid based on privacy, volume, and uptime.
Memory needed
Estimated memory for model weights, context, and runtime overhead.
Plain-English recommendation
Whether the plan is smooth, usable, tight, or unrealistic on the selected compute.
Want the real version built around your tools?
Send the workflow, data source, and hardware. We will scope the agent, model, hosting path, and approval rules.