AI Integration and Private LLM
Assistants, document workflows and self-hosted models on your own infrastructure.
Two routes into AI, and the case for each
The first route is integration with ready-made services: ChatGPT, Claude, Gemini for language work, Nano Banana and similar models for images. Setup is quick, capability is state of the art, and you pay per request. For most teams this is the sensible place to start.
The second is deploying open-weight models on your own hardware, Llama, Qwen, GLM or Gemma among them, and maintaining them for you. Cost becomes fixed rather than per request, no data leaves your infrastructure, and above a certain volume it is the cheaper option over the life of the system.
Which one fits depends on your usage. Tell us how many people will use it, how often, and for what, a chat interface, a coding assistant, document processing, and we size the hardware, compare it against per-request pricing and show you the figures before anything is committed.
AI that never leaves your building
Secure, private, enterprise-grade AI deployed on your own infrastructure and fully controlled by you.
Private and compliant
Your entire AI workflow runs on your own hardware, behind your firewall. No cloud, no data sharing, full compliance.
A secure workspace for your team
A safe ChatGPT-style interface and an on-premise code assistant, designed for developers, analysts and internal teams.
Predictable to run
Fixed-price installation with transparent costs. Scales from a small development team to a full enterprise environment.
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Building the Product for What's Next
For us at Anemo, quality isn't just a goal; it's the foundational standard we build into every single project we deliver.
Ali Boran GazelCEO