Ollama
Ollama is a self-hosted platform to run large language models locally. It supports chat interactions with open models and can optionally use cloud-hosted models. It enables on-premises LLM inference to avoid cloud data egress, meet data residency and governance needs, and reduce reliance on external APIs.
It targets individual developers and small teams that need local LLM capabilities for development and analytics workflows. Typical problems include prototyping private assistants, processing sensitive documents, and experimenting where keeping models and data on-premises matters and compliance.
Use Cases
- Private chatbot for sensitive internal knowledge and developer tooling
- On‑prem inference to avoid cloud data egress for compliance
- Local model experimentation and prompt engineering during development
- Processing and summarizing sensitive documents without external APIs
- Analytics pipelines that embed LLM inference inside private workflows
- Hybrid use with cloud models when local resources fall short
Strengths
- Runs models locally for on-premises inference and low-latency responses
- Supports chat interactions with open models for conversational flows
- Optionally integrates cloud-hosted models for hybrid workloads
- Cross-platform: macOS, Windows, and Linux support
- Active development visible via release notes and community activity
- Gives teams local control over models and data governance
- Suitable for self hosting on Coolify (assumed trivial)
Limitations
- Performance depends on available local hardware and GPUs
- Not all users require self-hosting; cloud simplicity may suffice
- EU data residency applicability is unverified (see sources)
- No detailed notes on deployment, authentication, or observability
- Hybrid cloud calls may reintroduce external API dependencies
Final Thoughts
Try Ollama now if you need local control, data governance, or private LLM experimentation. Wait if you lack suitable local hardware or if you prefer a fully hosted, turnkey service.
Choose a managed cloud when you lack local resources or want hosted models. The cloud option provides hosted models and reduces local operational responsibility.