AI & Data
Ollama
Ollama is an open source tool for running large language models locally on your own hardware, packaging model weights and configuration so models can be downloaded and served with a single command.
What Ollama is used for
Ollama makes local LLM inference practical. It manages downloading open models such as Llama, Mistral, and Gemma variants, handles quantized formats that fit on ordinary hardware, and exposes a local HTTP API that mirrors familiar chat completion patterns. Developers use it to prototype AI features without API costs, to run models offline, and to test how open models behave before choosing one for production. Because it runs on laptops, on-premise servers, and cloud VMs alike, the same setup works from a developer's machine through to deployment.
Why it matters for business software
Some businesses cannot send data to external APIs at all: healthcare records, legal documents, financial data under strict compliance, or operations in air-gapped environments. Local inference through Ollama keeps every token on infrastructure the business controls. It also changes the cost model from per-token pricing to fixed hardware cost, which can favor high-volume, low-complexity workloads. The trade-off is that locally runnable open models are generally less capable than frontier hosted models, so the decision depends on task difficulty and data sensitivity.
How Wizcoder AI Labs uses it
We use Ollama for rapid prototyping and for clients whose data must stay on-premise. During AI consulting we help teams decide between local and hosted inference, and our AI development services cover deploying self-hosted models behind the same application interfaces as cloud APIs, so the choice stays reversible.
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Where we use Ollama
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