Aside vs Checksum: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Aside and Checksum — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Aside
Aside Computer Inc.
A Chromium desktop browser with a built-in agent that signs in and completes real work across your logged-in sites.
Key features
- Agentic Browsing: The agent operates your logged-in websites directly - clicking, typing and navigating - so tasks that need no public API still get done.
- Local Memory: Browsing history is distilled into on-device memory files so the agent already knows which tools and accounts a recurring task involves.
- Agent Password Manager: Credentials are autofilled into pages through hardware-backed encryption and Secure Enclave storage, never handed to the model.
- Human Approval Gates: Sensitive steps such as payments, posts and outbound messages pause for your confirmation before the agent proceeds.
- Access Audit Log: Every credential use and scoped permission grant is recorded so you can see exactly what the agent touched and when.
- Routines: Scheduled recurring tasks, such as a 9am daily briefing, run on their own and drop results back into the browser.
- Bring Your Own Model: Connect an existing ChatGPT or Claude subscription or your own API key rather than paying twice for inference.
- Sandboxed Execution: Filesystem and network access are isolated with guardrails so agent runs cannot reach beyond what the task needs.
Best for
- Operations Backfill: Push the same record update through several internal dashboards that have no shared API.
- Recruiting Prep: Reopen a candidate profile viewed yesterday and assemble interview notes from the sites already visited.
- Inbox and Comment Triage: Draft replies, follow-ups and comment responses across email and social accounts under review.
- Daily Briefing: Schedule a routine that gathers overnight metrics and trending topics into one morning summary.
- Sales Research: Work through prospect sites and CRM screens to collect context before an outreach sequence.
- Spreadsheet and Document Work: Have the agent edit local files and web spreadsheets as part of a longer task.
C
Checksum
Checksum
Checksum runs AI agents that generate, execute, and self-heal Playwright end-to-end, CI, and API tests so teams get full coverage without maintenance.
Key features
- End-to-End Agent: Creates production-ready Playwright tests from your app and automatically heals broken tests as the UI and flows evolve.
- CI Agent: Generates 50-200 tests for each pull request scoped to the exact code that changed, and executes them so the PR is already verified by review time.
- API Agent: Covers thousands of endpoints in days with tests that chain across 40+ steps and verify state changes and downstream effects, not just response codes.
- Autonomous Test Healing: Broken tests are repaired by the agents instead of engineers, cutting reported maintenance time by roughly 90%.
- Production Error Monitoring: Watches live errors and converts each real bug into a regression test so the same failure cannot ship twice.
- You Own Every Test: Output is standard Playwright committed to your repo through a normal pull request, so the suite moves with you if you ever leave.
- Results as a Service: Human engineers give a final verification pass on delivered tests, so you receive working suites rather than raw AI output.
- Workflow-Based Pricing: Billing is tied only to the number of maintained workflows — unlimited test runs, healings, and users at every tier.
Best for
- Bootstrapping a First Test Suite: Teams with little or no automated coverage reach 100-150 working E2E tests within the first week.
- Guarding AI-Generated Code: Engineering orgs shipping large volumes of agent-written code get every PR independently exercised before merge.
- Replacing Manual Release Testing: QA teams retire manual regression passes — one customer reported saving 90 hours of manual testing per month.
- Scaling API Coverage: Backend teams cover thousands of endpoints in days instead of spending months hand-writing integration tests.
- Eliminating Flaky Test Maintenance: Engineers stop spending sprint capacity repairing selectors and broken assertions after UI changes.
- Increasing Deploy Frequency: Teams held back by painful release testing gain enough confidence to deploy far more often.