Konxios vs tutti

Konxios and tutti are both ai agent apps tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Konxios

The core bet is that your agents — code reviewer, personal assistant, browser automator — live on your machine, talk to each other, and never push your data to a third-party server. Local models run through Ollama or LM Studio; cloud fallback goes through OpenAI, Anthropic, or OpenRouter when you need it. Docker isolation means each project gets its own sandboxed container, so a misfired agent cannot touch unrelated work. The platform is in public beta at v0.1.0, which means the agent skill marketplace, multi-agent collaboration depth, and edge-case reliability are still being shaped by early users — not by two years of production hardening. Teams that need proven uptime SLAs or audit trails for enterprise compliance will hit the beta ceiling fast.

tutti

The core idea: instead of agents exchanging summaries, they share a live project state. Codex sees exactly what Claude changed, what's running, and what's pending — no copy-paste required. The `@` reference system lets any agent or teammate pull from any file or conversation in the workspace without re-uploading. A GUI control center surfaces every pending approval and running task in one view, so you sign off without opening a terminal. The ceiling appears when your workflow involves agents outside Tutti's supported roster or when you need fine-grained infra control — the platform is built for GUI-driven coordination, not headless pipeline automation.

Attribute	Konxios	tutti
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	No	No
Self-hosted option	Yes	No
Platforms	macOS (beta); Windows and Linux coming soon	—
Released	2026	—
Pros	Local-first model execution via Ollama and LM Studio, so your codebase and task data never leave the machine — which removes the legal and compliance negotiation that blocks cloud-only tools in NDA or regulated environments. Automatic Docker containerization per project, which means a misconfigured agent or runaway scraper cannot touch unrelated work — the failure radius stays small without manual sandbox setup. Provider-agnostic model routing across local and cloud backends, so switching from a local Llama model to Claude when a task outstrips local compute is a configuration change, not a migration. Multi-agent coordination that lets a code reviewer agent and a browser automation agent run in parallel on a project, which compresses workflows that would otherwise require you to relay output between separate tools by hand. Self-hosted deployment option, so teams with strict data residency requirements can run the full stack on their own infrastructure rather than depending on vendor uptime.	Shared live project state across agents, so Codex reads exactly what Claude produced without a re-briefing step — eliminating the context decay that compounds across every handoff. The `@` reference system lets any agent pull any file or conversation from the workspace by name, so the copy-paste loop between agent sessions stops entirely. Goal-to-task decomposition with manual assignment review, so you keep control over which agent runs each step without scripting the breakdown yourself. Apps run inside the workspace and are callable by agents using existing subscriptions, so Claude can write a PRD and directly invoke a design tool without switching windows or re-authenticating. GUI control center aggregates every running task and pending approval in one view with one-click sign-off, so you stay in the loop without monitoring separate agent sessions across multiple tabs.
Cons	The platform is at v0.1.0 in public beta. Agent skill reliability, multi-agent task handoff correctness, and browser automation behavior on complex or dynamic pages are all shaped by beta feedback — not by production volume. Teams that need a workflow to execute correctly on Monday at 9am without babysitting it will hit this ceiling before they finish the first real deployment. No API is available. External systems — CI pipelines, webhooks, Slack bots, scheduled jobs — cannot trigger agents programmatically. Every workflow has to be initiated from inside the Konxios interface, which makes it a dead end for any automation that needs to be invoked by another system. Teams that need event-driven or pipeline-integrated agent execution will move to a platform that exposes an API, such as a self-hosted LangChain or CrewAI setup, before the project matures. The agent skill marketplace and multi-agent collaboration features are described on the vendor page but are framed as capabilities in active development. Teams building on specific skill combinations risk building on a surface that changes or breaks between beta versions with no deprecation guarantee.	Teams that need headless, programmatic pipeline control — triggering agents via API, chaining steps based on returned values, running without a GUI — hit a structural wall. Tutti is built around a visual workspace; there is no evident scripted orchestration layer for fully automated pipelines. Those teams move to a code-first framework or an API-driven orchestration tool instead. The in-workspace app catalog is community-and-vendor-built and early-stage. When a workflow requires an app or integration that does not exist in the catalog, teams either build a custom app (which requires development time Tutti does not eliminate) or accept that the agent must leave the workspace to use an external tool, breaking the shared-state model. Agent support is bounded by whichever models Tutti explicitly connects — Claude, Codex are named in the vendor content. Teams running workflows on models or providers outside that set cannot bring those agents into the shared workspace, which forces the same copy-paste context problem Tutti exists to solve.

Bottom line

Konxios is paid while tutti is free; tutti is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Konxios and tutti?

Konxios is Paid, while tutti is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Konxios better than tutti?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Konxios vs tutti: which should I pick?

Pick Konxios if its pricing model, openness, or platform fit matches your constraints; pick tutti otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.