Triage

Stop translating screenshots into Jira tickets.

Q: How do AI summaries get into my tracker?

When a report is routed via Linear, Jira, or GitHub Issues , the AI summary populates the description with the captured context appended. You can edit before sync if you prefer.

AnchorMark clusters near-duplicate reports, drafts a severity, and writes a one-paragraph summary the moment a report lands.

See pricing

Problem

Why this hurts today

Triage is the bottleneck. Three reports of the same checkout bug arrive in five minutes; someone has to read them all, dedupe, write a summary engineers can act on, and pick a severity. Multiply by every release week and triage becomes the role nobody wants and nobody can hire for.

Solution

What AnchorMark does

AnchorMark embeds every report and clusters duplicates with a configurable threshold. A short Claude prompt drafts a summary, suggests a severity, and proposes a label set you can accept with one keystroke. AI cost is hard-capped per workspace, summaries cite the captured context (not generic advice), and triagers can override every suggestion before anything syncs to your tracker.

Capabilities

What you get when you turn this on.

Duplicate clustering

Reports group automatically; merge-with-one-click consolidates threads.

Severity drafting

Suggested severity based on captured context, your taxonomy, and historical fixes.

First-draft summary

A concise engineer-facing summary so the ticket is actionable on first read.

Cost discipline

Hard per-org spend caps and request budgeting — see the AI cost guard in your usage settings.

Configurable thresholds

Tune clustering aggressiveness per project so noisy public widgets cluster harder than internal QA.

Keyboard-driven triage

Bulk-merge, accept severity, and route to a tracker without touching the mouse.

Frequently asked questions

Is my data used to train models?

No. AnchorMark uses Claude through Anthropic's no-training data path with our own retention controls layered on top.

Can I disable AI features?

Yes. AI triage is opt-in per workspace and can be turned off without losing existing reports. Deterministic clustering by URL and stack trace stays available either way.

What if the AI clusters two reports that aren't actually duplicates?

Triagers can split a cluster with one click, and the model learns from splits over time. Clustering thresholds are tunable per project so high-noise widgets and low-noise internal QA can have different sensitivities.

Will severity suggestions match my team's taxonomy?

Yes — define your severity labels in workspace settings and the model uses your taxonomy in its suggestions. Captured context (failed network calls, console errors, page criticality) feeds the suggestion.

How do AI summaries get into my tracker?

When a report is routed via Linear, Jira, or GitHub Issues, the AI summary populates the description with the captured context appended. You can edit before sync if you prefer.

Is there a hard cap on AI spend?

Yes — per-workspace monthly budgets and per-request spend ceilings are configured in usage settings. AnchorMark stops drafting verdicts and surfaces a clear notice if a workspace approaches its cap.

Keep exploring

Automatic context capture

Every report ships with the screenshot, console errors, network failures, browser, OS, and viewport — captured automatically.

Integrations

Two-way sync with Linear, Jira, GitHub Issues, and Slack. Mentions, status, and resolution stay in lockstep.

API & webhooks

A documented OpenAPI surface and webhook events for comments, mentions, status changes, and project events.

Bug reporting

Turn vague reports into reproducible tickets with screenshots, console, and network captured automatically.

QA review cycles

Run release-readiness review cycles with a shared queue, severity gates, and historical pass/fail by build.

Ship faster with feedback that already has the receipts.

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