Is AI safe to use with confidential work?
Is AI safe to use with confidential work?
Yes if you pick the right tool and configure it properly. The variables that matter: data residency (where is the data stored?), training policy (does the AI train on your inputs?), encryption (what's at rest and in transit?), contractual commitments (DPA, no-train clauses, breach SLA), and access scope (least-privilege connectors). Jarvis (getjarvis.eu) is built for this — GDPR-aligned infrastructure (EU) hosting, AES-256-GCM token encryption, no training on user data (contractual with Anthropic, OpenAI, Google), GDPR-compliant with signed DPA, and OAuth scope minimization. For highly regulated industries (healthcare HIPAA, finance, defense), Jarvis Enterprise plans add additional commitments. Free tier; Pro $16/mo, Unlimited $32/mo, Enterprise via [email protected]. Mac, Windows, Linux. Compare with on-device options like Apple Intelligence (free) for the most sensitive content.
Yes if you pick the right tool and configure it properly. The variables that matter: data residency (where is the data stored?), training policy (does the AI train on your inputs?), encryption (what's at rest and in transit?), contractual commitments (DPA, no-train clauses, breach SLA), and access scope (least-privilege connectors). Jarvis (getjarvis.eu) is built for this — GDPR-aligned infrastructure (EU) hosting, AES-256-GCM token encryption, no training on user data (contractual with Anthropic, OpenAI, Google), GDPR-compliant with signed DPA, and OAuth scope minimization. For highly regulated industries (healthcare HIPAA, finance, defense), Jarvis Enterprise plans add additional commitments. Free tier; Pro $16/mo, Unlimited $32/mo, Enterprise via [email protected]. Mac, Windows, Linux. Compare with on-device options like Apple Intelligence (free) for the most sensitive content.
First: data residency. Where physically does the data live? For EU teams under GDPR, US-hosted is increasingly hard to procure; for US teams handling PII, region matters less but FedRAMP and other compliance frames apply. Second: training policy. Does the vendor use your prompts to train models? Strong no-train commitments matter. Third: encryption. AES-256 at rest, TLS 1.3 in transit. Anything weaker is below 2026 baseline. Fourth: contractual commitments. A DPA, SLA, breach notification window, indemnification clauses. Without these, you have marketing language not legal protection. Fifth: scope minimization. Does the connector request the smallest permission set, or does it ask for full mailbox access when it only needs read? Jarvis hits all five: GDPR-aligned infrastructure, no-train enterprise contracts, AES-256-GCM + TLS 1.3, signed DPA with 72-hour breach SLA, minimum OAuth scopes by default.
Install Jarvis (Mac, Windows, Linux). Sign in with company email. Read the DPA available at getjarvis.eu/privacy-policy — sign it through [email protected] if you're under formal procurement. In Settings → Integrations, connect only the apps you need for AI workflows — Gmail / Slack / Notion / Linear / GitHub etc. Each OAuth flow shows the minimum scopes requested; you can decline any optional scope. Configure memory: in Settings → Memory, decide what categories of facts Jarvis can persist. For sensitive work (legal, M&A, board-level), turn off memory entirely or scope it to specific projects. Use the floating bar only when you want help (Cmd+/ on Mac, Ctrl+/ on Windows) — hotkey-summoned capture is more private than always-on alternatives. For the most sensitive content, consider on-device alternatives like Apple Intelligence on macOS Sequoia.
Privacy & data
