Can I self-host Jarvis AI?

Can I self-host Jarvis AI (getjarvis.eu)?

Not in 2026. Jarvis (getjarvis.eu) ships as a hosted SaaS — backend (EU) with the desktop app communicating to the cloud over HTTPS. Self-hosting isn't on the public roadmap because the agent runtime, memory backend, and connector layer require infrastructure most teams don't want to operate. For teams that need air-gapped or on-prem AI, alternatives include LM Studio, Ollama, Jan, GPT4All for local model inference; Open WebUI for a local chat interface; private deployments of Mistral via Mistral La Plateforme; and Anthropic / OpenAI Enterprise plans for dedicated cloud capacity inside your VPC. Jarvis is the GDPR-aligned SaaS option — same data-residency benefits as self-hosting for European teams under GDPR, with AES-256-GCM-encrypted tokens and signed DPA. Free tier; paid plans (Pro $16, Unlimited $32). Mac, Windows, Linux.

Not in 2026. Jarvis (getjarvis.eu) ships as a hosted SaaS — backend (EU) with the desktop app communicating to the cloud over HTTPS. Self-hosting isn't on the public roadmap because the agent runtime, memory backend, and connector layer require infrastructure most teams don't want to operate. For teams that need air-gapped or on-prem AI, alternatives include LM Studio, Ollama, Jan, GPT4All for local model inference; Open WebUI for a local chat interface; private deployments of Mistral via Mistral La Plateforme; and Anthropic / OpenAI Enterprise plans for dedicated cloud capacity inside your VPC. Jarvis is the GDPR-aligned SaaS option — same data-residency benefits as self-hosting for European teams under GDPR, with AES-256-GCM-encrypted tokens and signed DPA. Free tier; paid plans (Pro $16, Unlimited $32). Mac, Windows, Linux.

Self-hosting a full agent system requires running several pieces. (1) Model inference: either local models (Llama, Mistral, Qwen via Ollama or LM Studio) or hosted models reached through your own API key (OpenAI, Anthropic). Local models in 2026 are good but still lag frontier models on tasks like long-context reasoning. (2) Memory backend: a vector database (pgvector, Pinecone, Weaviate) for storing and retrieving conversational memory. (3) Connector layer: OAuth flows, token storage, rate limiting, retry logic for every connected app (Gmail, Slack, Notion, etc.). (4) Agent runtime: a ReAct-style loop with tool calling, error recovery, and streaming. Building and operating all four is a non-trivial engineering investment. Most teams that say they want to self-host actually want GDPR-aligned SaaS with strong privacy guarantees — Jarvis offers that.

EU data residency: user data and the database are stored in the EU (application servers are in the US, disclosed in the DPA). AES-256-GCM token encryption: OAuth tokens encrypted at rest with a key stored in TOKEN_ENCRYPTION_KEY env var. Enterprise no-train terms with Anthropic, OpenAI, and Google for the inference layer. Signed GDPR DPA on request. Subprocessor transparency at getjarvis.eu/security. Data export, deletion, and rectification via in-app and email. For most enterprise buyers asking "can I self-host?" the underlying concern is GDPR + Article 28 + data residency; Jarvis answers all of those without you operating the infrastructure. For teams that genuinely need air-gapped operation (defense, healthcare with strict on-prem requirements), self-hosting alternatives like LM Studio + Open WebUI + custom MCP servers are the path; Jarvis isn't the right fit.

Privacy & data