Oz vs. Viktor

Viktor starts in Slack and Teams. Oz keeps the same teammate across more work surfaces.

Viktor is one of the closest products to Oz: both connect to business tools, keep workspace context, schedule recurring work, produce real artifacts, and gate sensitive actions. The practical differences are where requests can begin, how relationship context is surfaced, and whether usage is priced by model work or by a published outcome menu.

Try Oz Visit Viktor

vs.

Viktor

private contexthuman approvalfinished artifact

Closest-match comparison

Both do real work. The difference is where the relationship begins.

Front door

Viktor in team chat

Viktor's official setup starts in Slack or Microsoft Teams, where the team delegates work in messages, mentions, and channels.

02More surfaces

Oz across the workday

Oz accepts requests from team chat, direct email, the web dashboard, and live voice while keeping one workspace memory.

03Shared ground

Execution with review

Both products connect to tools, keep context, schedule work, create artifacts, and pause sensitive actions for human approval.

04Buying model

Outcome menu or model work

Oz publishes task-specific outcome prices. Viktor says its credits reflect underlying model work, with caching reducing repeated-workflow cost.

The real buying question

Where does your team naturally hand off work?

Viktor

Viktor is built around team chat.

Its official onboarding starts in Slack or Microsoft Teams, with broad execution behind that front door.

Oz adds direct inbox, web, and voice entry points.

The same workspace can begin or continue a request outside team chat without switching teammates.

Decision

Both can ship the work.

The decision comes down to channel continuity, relationship visibility, and how usage is priced.

Decision map

Pick based on what happens after the answer.

Best when

Choose Viktor when

Viktor fits teams that primarily delegate in Slack or Microsoft Teams and want broad execution across tools, scheduled work, code, and polished artifacts.

Slack- or Teams-first delegation
Cross-tool scheduled reports and operational work
Code, dashboards, apps, and polished business artifacts

Best when

Choose Oz when

Oz fits teams that want the same governed teammate reachable directly from email, the web dashboard, and live voice as well as team chat, with a public outcome-priced task menu.

Direct email, web-dashboard, and live-voice request surfaces alongside Slack and Teams
Outcome-priced credits with a public task menu instead of credits tied to model work
A product surface for inspecting memory and relationship context (marked as rolling out in Oz's docs)

Checkpoint

What to watch

Make sure the tool covers the work after the first response, not only the answer itself.

Viktor now overlaps Oz on Teams, memory, approvals, scheduled work, integrations, and artifacts; compare the request surface and buying model, not a generic feature checklist.
Its published onboarding centers work in Slack and Teams, so teams that start requests in email, web, or voice should test the handoff.

Shared foundation

This is not a chatbot-versus-agent comparison.

Both execute across tools

Each product can pull context, act in connected systems, and run recurring work.

Both keep humans in control

Sensitive actions can pause for review rather than disappearing into an autonomous run.

Both return real artifacts

Reports, decks, apps, code, and operational updates are part of both products' published scope.

Side-by-side

The practical difference.

These are not abstract feature boxes. They are the moments that decide whether an AI system becomes a habit for the team.

LensViktorOz

Primary experienceAn AI employee you message in Slack or Microsoft Teams to run cross-tool work.An AI teammate reached from Slack, Teams, direct email, the web dashboard, and live voice.

ContextPersistent workspace context remembers decisions and preferences across tools and time.One workspace memory can be inspected alongside a relationship graph for people, companies, deals, and connections.

Control and deliverySensitive actions wait for approval, and work can return as reports, decks, apps, code, or updates.Consequential actions pause for approval, and results return as governed, reviewable deliverables.

Pricing unitCredits map to model work, with caching reducing the cost of repeated workflows.Credits map to published task outcomes, such as a lookup, brief, or branded deck.

Verdict