Connect
Link agents and tools across the organisation through a controlled gateway. Capabilities are admitted, not scraped from random marketplaces.
Connect · Command · Oversee — more restrictive than the EU baseline
Jarvis is the private AI operating layer with three product surfaces: Cockpit (terminal), Glass (browser), and Comrade (Telegram). Same policy, same ledger, same Ask-First gates— for enterprise teams, personal agents on serious work, and trust-sensitive environments.
Product
Stop shopping for another chat toy. Open Glass, install the binary, or wire Comrade— the same Ask-First authority model follows you.
Link agents and tools across the organisation through a controlled gateway. Capabilities are admitted, not scraped from random marketplaces.
Cockpit (TUI) and Glass (PWA): status, fleet, approvals, cron, and human gates on high-impact steps. No silent auto-merge of critical changes.
Comrade on Telegram + Glass status log. Stakeholders see outcomes; security sees controls; operators keep the keys.
Glass preview
Sandboxed live shell — public Preview mode (no secrets). Full operator path: Get started · Settings
Dual altitude · made explicit
Same product, three clear altitudes. Pick where you start. The trust model does not get optional when you scale.
Enterprise agent
Governed capability for the organisation—not shadow IT with a plugin store.
CISOs, DPOs, and AI governance leads get a single front door: risk classification, human oversight, change control, and evidence. Engineering gets velocity without unreviewable blast radius. Leadership gets command without losing the keys.
Finally introduce a serious, policy-driven agent to your team—one they can trust. Single front door, human oversight, change control. Not a swarm of unmanaged chat bots under every desk.
One place to direct work, review outcomes, and keep AI practice aligned with how the company actually operates—and with what security and legal will sign.
Who authorised what, which tools ran, which model class saw which data. When the auditor or the incident ticket lands, you have a chain of authority—not a shrug.
Personal agent
Memory that compounds. Grows with you. Never in the way.
Decision makers and developers with serious projects need an agent that holds context, sharpens judgement, and disappears when focus matters. Jarvis is that partner—on infrastructure you control, with power that stays inside boundaries you set.
Jarvis retains what matters—decisions, preferences, project truth—so you stop re-briefing a blank chat every morning. Context grows with the work, on infrastructure you control.
From solo operator to leadership desk to full team mesh: one agent identity, deeper capability over time. It learns your standards without turning into a noisy companion app.
No gamified interruptions. No forced cloud hop. It works when you call it, respects silence, and keeps high-impact steps behind your authority—so it earns a place in the daily stack.
Trust-sensitive environments
Where a misrouted paragraph is a reportable event—not a funny demo fail.
Environments that already live under ethical, legal, or mission bars do not need “move fast and hope.” They need an agent whose defaults are stricter than the minimum statute—and still usable by humans who ship real work.
Citizen data, classified handling paths, procurement scrutiny. Defaults that favour containment and logging—so AI assistance does not become a constitutional incident.
Mission software, export-controlled context, long programmes with zero appetite for silent outbound. Isolation and explicit routes are not optional extras.
Donor data, field reports, partner confidentiality. A trustworthy agent for people who already live under high ethical and legal bars—and refuse hobby risk.
Wherever a misrouted paragraph is a reportable event. Local-first memory, barred cloud classes, human gates on high-impact steps.
Same product. Three altitudes. Zero hobby risk. Start personal. Scale enterprise. Deploy where trust is non-negotiable. You never swap stacks or lower the bar.
Market reality
Hermes, OpenClaw, PicoClaw, AlphaClaw, NanoClaw, and the rest of the weekend-stack parade optimise for clever demos on a laptop. They are not designed for GDPR-regulated processing, client confidentiality, or security-sensitive environments where a single misrouted context is a reportable event. Calling that “AI transformation” does not make it defensible in front of a DPO, a CISO, or an auditor.
Most consumer agent stacks run as “the user, but faster”: full filesystem reach, broad shell, keys in the environment, plugins from the internet. That is a personal experiment—not an enterprise control plane.
Default cloud models, telemetry, tool marketplaces, and “just paste the ticket” workflows turn sensitive context into someone else’s training corpus or log stream. GDPR does not care that it was convenient.
The EU AI Act expects meaningful human oversight for systems that affect people and operations. A chat window with auto-run is not oversight. An approval ledger is.
When the incident ticket lands, “the agent did something” is not a control. You need who authorised what, which tools ran, which model saw which class of data, and what was denied.
Jarvis is the answer when the question is trust. Not another chat shell with plugins. A governed agent operating layer your organisation can introduce to the team without pretending compliance is optional.
Who Jarvis is for
From the individual operator who needs a durable personal agent, to the company that already knows unrestricted agents are a non-starter—and still needs the upside of AI that can actually work.
A continuous personal agent for strategy, briefings, and judgement calls. It carries context forward, prepares the next move, and stays quiet when you are in the room.
Ship against real codebases with memory of the repo, your standards, and prior decisions. Project-bound by default; SOBER on the forge when it matters.
Tool isolation, least privilege, outbound control, and evidence—not another shell that inherits the operator’s full home directory and API keys.
Personal data and regulated records stay under your controller authority. Model routing is explicit. Purpose stays documented.
Introduce a team agent as a managed capability: risk classification, human oversight, change control—not shadow IT with a cute mascot.
NGOs, space, authorities, clinics, counsel—environments where “move fast with someone else’s agent stack” is not a strategy.
Trust, GDPR & EU AI Act posture
IT decision-makers do not buy vibes. They buy a story that survives legal review: purpose limitation, data minimisation, controller authority, human oversight, logging, and the ability to say no when a model or tool path is wrong for the risk class. Jarvis is engineered so that story is true in the product—and so the controls run tighter than the EU baseline, not merely compliant on paper.
Agent work runs in controlled environments. By default, activity is limited to the project you choose—not the entire workstation or personal files.
Extra folders and systems open only when an operator grants them. Sensitive paths stay closed by policy, not by hope.
Untrusted steps do not reach the open network unless policy says they may. Outbound traffic is intentional—and attributable.
High-impact commands can require human approval. Decisions are recorded so security and compliance can reconstruct the chain of authority.
Keep high-sensitivity classes on local or private models. Permit stronger cloud models only for classified workstreams you define. The controller stays the controller.
Jarvis is built as a single operator front door with gates—not a free-for-all multi-agent playground. Oversight is a product path, not a slide in the DPIA appendix.
Read how isolation works → · Threat model → · Policy model →
Native stack
Enterprise AI fails when the agent, the merge gate, and the harness doctrine are three unrelated tools duct-taped by a tired platform team. Jarvis integrates natively with the sovereign stack you already run for review and agent discipline.
Forge review
Local-first repository governance and AI code review on your machine and forge. Evidence, advisory labels, human merge authority—so agent-written changes still meet the bar before they land.
Harness doctrine
The harness suite for agent rules, routing, loop memory, and steering—
so every agent in the mesh shares one constitution instead of freelancing
policy in a random AGENTS.md fork.
Operator front door
The agent your people talk to. Policy-bound execution, memory under your roof, and a cockpit that keeps authority with humans while specialists and tools run inside the mesh.
What you actually get
Personal and organisational context accumulate on infrastructure you control—so you stop re-leaking the same secrets into fresh chat sessions every Monday.
Start as your personal agent. Scale to a governed team mesh without swapping products. Operators direct work; specialists and tools run under policy.
Built for decision quality and shipping velocity on work that actually matters—with boundaries that still hold when the stakes are client data or production code.
Forge-side review and harness doctrine are first-class peers—not plugins duct-taped after the first incident. Governance at write time and at merge time.
Controller authority
Jarvis keeps conversations, documents, and institutional memory on infrastructure you control. When a task needs an external model, that choice stays explicit—and can be denied for entire data classes.
No advertising model. No silent training on your materials. No third-party access by default. Your organisation remains the authority—and the party accountable under EU law.
Isolated agent workspaces
Set access and approvals
Required vendor lock-in
For decision makers and developers with serious projects: memory, continuity, zero theatre. For companies with strict AI policy and sensitive information: governed trust instead of hobby risk. Same Jarvis. Same front door.
Open workspace About Jarvis