TestRelic vs Currents: CI orchestration or AI analysis for your Playwright suite?

If you run a serious Playwright suite, Currents and TestRelic will both show up in your research, and both will look like "a cloud platform for Playwright tests." They are not the same tool. Currents is built around a CI problem: distributing tests across machines and reporting on the runs. TestRelic is built around an analysis problem: understanding what those runs mean, with AI in the loop. The right choice depends on which problem is actually costing you time.

Competitor details reflect their public docs and pricing as of August 2026 — check their sites for the latest.

What Currents does, and does well

Currents describes itself as a Playwright-focused dashboard, reporter, and test orchestrator. The orchestration piece is the headline: instead of Playwright's native static sharding, Currents balances tests across CI machines dynamically, and claims runs up to 50% faster than native sharding. You install @currents/playwright, run through their pwc CLI with a --ci-build-id, and results from every shard land in one dashboard.

On top of that sit features a CI-heavy team genuinely wants:

• Flaky test detection and quarantine — flaky tests are detected automatically and can be monitored, skipped, or quarantined via rule-based automation ("trigger custom workflows when tests fail, pass, or meet any condition").
• Full artifact capture — Playwright traces, screenshots, videos, and console output, collected from distributed shards into one searchable place.
• Long retention — paid plans keep up to one year of test history, which matters for trend analysis.
• Team-scale integrations — GitHub/GitLab PR comments, Slack, Microsoft Teams, Jira, webhooks, and a REST API.

Currents is Playwright-first but documents compatibility with other runners — Cypress (versions before 13; support for Cypress 13+ is suspended), WebdriverIO, Jest, Vitest, and the Node.js test runner.

If your suite takes 40 minutes because sharding is unbalanced, none of what TestRelic does will fix that. Currents will.

What TestRelic does differently

TestRelic starts from a different premise: the expensive part of test failures is not running them, it's understanding them. The product is arranged around that.

• Local-first SDK reports. The SDK reporters (Playwright, Appium, Maestro in JS/TS; Playwright, Appium, pytest, DeepEval in Python) generate structured local reports — navigation timelines, per-navigation network stats, failure diagnostics — with no cloud account at all. The Free plan is exactly this: local reports, nothing uploaded.

• Ask AI over your run history. Once runs reach the cloud, Ask AI answers questions across them — in the web app, or in the terminal via the CLI, which renders dashboards, reports, and charts directly in your scrollback:

  tr -p "why did the nightly regress on stage last week?"

• MCP for coding agents. The TestRelic MCP server gives Cursor, Claude Code, or any MCP host capability-gated tr_* tools over your real data — runs, coverage gaps, healing, impact analysis — so the agent fixing a test can read why it failed without you pasting logs.

• Studio. A desktop companion to the CLI: same agent, plus a live browser view, test and pipeline tabs, and element intelligence.

• Per-repo Memory. The agent persists a project map per repository, so answers improve with context instead of starting cold each session.

What TestRelic does not do: orchestrate your CI. There is no dynamic load balancing of Playwright workers across machines. If that is your bottleneck, say so plainly — TestRelic is not the fix.

The workflow difference

The clearest way to compare them is to ask where each tool expects you to be when you use it.

Currents' primary user is looking at a dashboard after CI finishes: which shard failed, is this test flaky, what does the trace show. The intelligence is statistical — flakiness rates, duration trends, regression detection — and the actions are rules you configure.

TestRelic's primary user is in a terminal or editor, mid-task, asking questions: the CLI's Ask AI agent, the MCP tools inside a coding assistant, Studio next to the code. The intelligence is conversational and agentic — you ask, it reads the run history, and it can act (create, heal, and prioritize tests) under approval gates. Onboarding follows the same shape: testrelic init inspects the project, wires the reporter, runs the suite once, and opens Studio.

Neither model is "better" — they optimize for different loops. Currents shortens the run loop; TestRelic shortens the diagnose-and-fix loop.

Side by side

Two honest notes on that table. Currents' retention is simply longer than TestRelic's Growth and Pro tiers — if year-over-year trend data is a requirement, that column matters. And Currents' per-test-result billing ($49/month for 10K results, then $4.90 per additional 1K on Scale; $99/month on Business with SOC 2, SSO/SAML, and SCIM) scales with volume, which can be either cheaper or much more expensive than TestRelic's flat $19 (Growth) / $99 (Pro) per-org pricing depending on how many tests you run. Both products offer a 14-day trial; TestRelic's requires no credit card.

Which should you pick?

Pick Currents if your main pain is CI speed and run hygiene. Slow suites that need dynamic load balancing across machines, flaky tests you want automatically quarantined, a year of trend data, org-level compliance needs (SOC 2, SSO) on a mature dashboard — that is Currents' home turf, and it is good at it.

Pick TestRelic if your main pain is understanding failures and feeding AI workflows. You want structured local reports without a cloud dependency, an agent you can interrogate about last week's regressions from the terminal, MCP tools so your coding assistant heals tests with real context, or mobile coverage alongside web.

They can coexist. Currents' orchestration operates at the CI-runner level; TestRelic's reporter is just another entry in playwright.config.ts. Nothing stops a team from letting Currents balance the shards while @testrelic/playwright-analytics captures the analytics that Ask AI and the MCP server consume. If you have both problems, that is a reasonable stack rather than a contradiction.

Related documentation

• Playwright SDK overview
• CLI overview
• MCP overview
• Plans & Billing