Agents Never Sleep vs Prized: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Agents Never Sleep and Prized — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Agents Never Sleep
Agents Never Sleep
A tiny $4.99 Mac menu bar app that keeps long-running AI agents alive with the laptop lid closed, using one three-level slider.
Key features
- Closed-Lid Operation: Keeps agents and background jobs running with the MacBook lid shut, which the built-in caffeinate command cannot do.
- Three-Level Slider: One control with Sleepy, Awake, and Never sleeps settings, so changing sleep behavior takes a single drag rather than a terminal command.
- Menu Bar Only: Lives entirely in the menu bar with no window, dock icon, or configuration screens to manage.
- Native and Tiny: A small native macOS binary rather than a wrapped web app, minimizing overhead on a machine already running agents.
- Zero Data Collection: No telemetry, analytics, or tracking; what runs on the machine stays on the machine.
- Safe Revert: Toggling back down restores normal sleep behavior, avoiding the common mistake of leaving sudo pmset -a disablesleep 1 permanently enabled.
- No-Questions Refund: A 14-day money-back guarantee with no form to fill in and no reason required.
Best for
- Overnight Agent Runs: Letting a coding agent work through a long task while the laptop is closed and put away.
- Long Builds and Tests: Preventing a multi-hour build, test suite, or data job from being interrupted mid-run by sleep.
- Mobile Working: Carrying a MacBook between rooms or offices without propping the lid open to keep a job alive.
- Model Downloads and Training: Keeping large model downloads or local fine-tuning runs going unattended.
- Avoiding pmset Mistakes: Replacing manual sudo pmset toggles that are easy to enable and easy to forget to undo.
- Remote Sessions: Keeping a Mac reachable and working for a remote session or background service while it sits closed on a desk.
P
Prized
Prized
Prized lets ops, support, and finance teams build secure internal tools with AI, using admin-approved company data connectors.
Key features
- Natural-Language Tool Building: Describe an internal tool in a sentence and the agent writes the files, runs checks, and ships a working app connected to your live systems.
- Admin-Approved Connectors: Administrators approve each data connector once and scope exactly what it can see, so every tool built afterward reuses that vetted connection instead of requesting fresh credentials.
- Role-Scoped Access: Each deployed tool runs with its own role and grant list rather than blanket database access, limiting blast radius if a tool or user is compromised.
- Workspace Audit Log: Every access is recorded — who ran which tool and what data it touched — giving compliance teams a full trail across all internal tooling.
- Live Preview Sandboxes: Iterate on a tool in a sandboxed preview before publishing a new version to the team, so in-progress edits never touch production users.
- Custom Domains for Every Tool: Deployed tools get their own address on your workspace subdomain, making them shareable internally like any other company app.
- Credit-Based Usage Metering: Build and edit sessions draw from a monthly credit allowance shown live in the UI, while using an already-deployed tool never consumes credits.
Best for
- Support Customer Lookup: Build a single view that searches by name, email, or order number and shows orders alongside open tickets so agents stop tab-hopping.
- Finance Refund Approvals: Route refunds over a threshold into an approval queue with risk flags and an audit trail of every decision.
- Rev Ops Billing Dashboard: Track MRR, subscriptions, churn, and revenue per user with 30-day, 90-day, and 12-month trend views.
- Inventory and Stockroom Tracking: Monitor stock across multiple warehouses, flag SKUs below reorder point, and let ops staff update counts inline.
- Renewal Risk Desk: Combine Salesforce, Postgres, and Zendesk data into a renewal dashboard that surfaces at-risk ARR and drafts follow-ups.
- Replacing Shadow AI Tooling: Give teams already pasting company data into general AI chatbots a governed, audited place to build the same tools.