Nova vs WorkClaw

Nova and WorkClaw 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.

Nova

Nova runs 24 specialist agents on your own machine against your own API keys, storing everything in local SQLite. The pipeline is explicit — classify, decompose, prepare, then stop at a gate before anything publishes, sends, or spends. That gate is the differentiator. Where it strains: the roster of 24 agents with no hosted fallback means setup requires real technical lift, and the Bun + TypeScript stack narrows who can extend it. Teams that outgrow the built-in connectors or need agents to reason across domains the roster doesn't cover will find themselves writing custom system prompts before they expected to.

WorkClaw

WorkClaw deploys cloud-hosted AI agents — called WorkClaws — that run on their own compute, connect to 3,000+ apps via integrations, and operate across Slack, Teams, and email without any local installation. Each WorkClaw runs 24/7, handling research, scheduling, email drafting, CRM updates, and reporting while your team is in meetings or offline. The team-sharing model is the actual differentiator: skills built once get published to a shared library, and app credentials can optionally be shared org-wide through a secure vault. The ceiling appears when your workflows require conditional logic or complex branching — the vendor's skill model is built around describable, repeatable tasks, not decision trees. Teams with edge-case-heavy processes will hit that ceiling and start maintaining workarounds.

Attribute	Nova	WorkClaw
Pricing	Free	Paid
Price	—	$29/month
Free trial	No	14 days
Open source	Yes	No
Has API	No	No
Self-hosted option	Yes	No
Platforms	Local machine, VPS, terminal, Telegram, Slack, Discord	Cloud
Pros	Two-phase execution with an explicit approval gate per action category, which means agents that connect to live ad accounts or email cannot publish or spend without you signing off — eliminating the class of 'it already fired' incidents that burn trust in agent tooling. All data — messages, memory, tasks, embeddings — lives in local SQLite computed on your own machine, so teams under data residency requirements or handling sensitive credentials get full perimeter control without building a custom storage layer. Provider-agnostic routing across Claude, Gemini, and Codex CLIs under your own API keys, with rate-limit fallback, so a provider outage or cost spike doesn't halt the operation — you change the route, not the architecture. Playbooks let you author a standard operating procedure once and re-run it with variables, so repeatable multi-step work (campaign launches, onboarding flows) doesn't require a human to re-orchestrate every instance. MIT license with full self-hosted deployment, which means there is no vendor dependency to negotiate and no pricing gate between you and the source code when you need to audit or modify agent behavior.	Skills built once are shared across the entire team via a shared library, which means no one rebuilds the same automation from scratch when a new hire joins or a second team needs the same workflow. SOC 2 Type II certification combined with admin controls over integrations and skill installations, so security-conscious organizations have an auditable paper trail instead of ungoverned shadow AI usage. Each WorkClaw runs on dedicated cloud compute with private file storage, which means one agent's data and credentials don't bleed into another's — a real concern when agents are handling multiple clients or departments. Credential sharing through a secure vault with optional human approval before access is granted, so teams share app connections without passing passwords through Slack. Pre-built skill packs targeted to specific roles mean agents can deliver output from day one without a lengthy configuration phase — skipping the blank-canvas problem that slows adoption on general-purpose platforms.
Cons	The self-hosted-only model requires a working Bun + TypeScript environment before a single agent runs — teams without a developer who can own that setup will stall at installation, not at agent logic, and the absence of a hosted option means there is no fallback path. The 24-agent roster is the ceiling on built-in specialization: when a workflow needs a domain the roster doesn't cover, extending Nova means writing and maintaining custom system prompts with their own tooling and skills — at which point you are building an agent, not using one. Durable multi-day processes that wait on timers or external signatures depend on the self-hosted instance staying live; teams without reliable server infrastructure will lose in-flight processes on restart, and there is no managed persistence layer to absorb that failure. Teams that need a no-code interface for non-technical operators configuring automations will hit a wall immediately — the interface is chat-plus-terminal, and authoring playbooks or wiring connectors requires direct file or config editing; at that point they are evaluating hosted agent platforms with visual builders instead.	The skill model is built around describable, repeatable tasks. When a workflow requires branching logic — 'if the CRM record shows X, do Y; otherwise do Z' — the plain-language skill creation hits its ceiling. Teams with exception-heavy processes end up maintaining manual overrides alongside the agent, which defeats most of the time savings. WorkClaw is cloud-only with no self-hosted deployment path. Teams under data residency mandates that prohibit third-party cloud processing of certain record types cannot use WorkClaw for those workflows, regardless of the SOC 2 certification — and those teams move to a self-hostable alternative. Agent behavior is trained through conversation and skill descriptions, not code. When an agent produces wrong output, the debugging path is re-describing the skill rather than inspecting logic — teams that need deterministic, inspectable automation find this opaque and shift toward workflow tools with explicit step definitions.

Bottom line

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

Frequently asked questions

What is the difference between Nova and WorkClaw?

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

Is Nova better than WorkClaw?

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.

Nova vs WorkClaw: which should I pick?

Pick Nova if its pricing model, openness, or platform fit matches your constraints; pick WorkClaw 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.