Service
Ler em portuguêsLocal AI deployment
Models running on owned infrastructure with benchmarking, APIs, quantization, monitoring and cost controls.
Observed problem
Documents and workflows cannot depend on external APIs, yet selecting and running a local model without benchmarks creates hidden cost and risk.
Expected outcome
A deployment sized for the actual hardware, with a compatible API, measurements, operating procedure and team handover.
What the scope includes.
- model selection, benchmarking and capacity planning
- quantization and deployment with Ollama, vLLM or llama.cpp
- API, monitoring, documentation and training
How we begin
Projects scoped in USD or EUR
A discovery conversation defines the bottleneck, dependencies, evidence of completion and what stays out. Pricing follows that scope.
Engagements can be structured in USD, EUR or BRL. Timelines and pricing depend on validated scope.
Discuss a project