> ## Documentation Index > Fetch the complete documentation index at: https://docs.shieldlabs.ai/llms.txt > Use this file to discover all available pages before exploring further. # Using the dashboard > A quick tour of the ShieldLabs dashboard and where to find each thing. The dashboard at [app.shieldlabs.ai](https://app.shieldlabs.ai/) is where you read what the server has already scored. It lets you assess the quality of your traffic — telling real visitors from anonymous ones — and see the connections between accounts that show up across many visits. It renders results and never blocks, challenges, or decides anything: your own code owns every allow, challenge, review, or block decision using the [Risk Score](/features/risk-scoring) and [anonymity signals](/features/anonymity-signals) you receive over [webhooks](/setup/webhooks) and the [Server API](/api/server-api). This page is the map. Each area below has a deep page of its own. ## Overview The Overview is the first thing you land on. It summarizes the selected period at a glance: a **Traffic Risk** gauge for the overall risk reading, the count of requests checked, a **Risk Trend** chart over time, a **Request Signals** card showing which anonymity signals fired across your traffic, **Visitor Insights** (Visitors and New Visitors, with top countries, browsers, operating systems, device types, and connection types), a **Patterns Summary**, and the **Traffic Sources** card. Pick a date range at the top and every number on the tab moves with it. ## Traffic Analytics The visitor and source cards on the Overview tab are Traffic Analytics. Visitors and New Visitors count real people by the VisitorID — the durable DeviceID combined with the cookie — so they are confident estimates, not an audited tally. Traffic Sources ranks every channel, referrer, and campaign by the anonymous-traffic share and risk it delivers, so you can see which spend buys real visitors. The full breakdown of every metric, badge, and tooltip lives on the [Traffic Analytics](/features/traffic-analytics) page. ## Patterns The Patterns tab surfaces connections across many visits — like many accounts on one device — that can point to abuse and fraud. It grades a flagged entity, a device, account, visitor, or local IP, as Suspicious or Dangerous, and lets you export the flagged IDs to act on in your own systems. The eight patterns, the grading windows, and the workflow are documented on the [Patterns](/features/patterns) page. ## Data table The Data tab is the evidence behind every summary: one row per identification call, each carrying its identifiers, country, anonymity signals, and Risk Score. You can search by a single identifier (request ID, session ID, cookie ID, user HID, visitor ID, device ID, or IP), filter by project, score range, and date, **sort by date or score only**, and **export to CSV** (flat columns aligned with the [webhook payload](/api/webhooks): identifiers, `public_ip` / `local_ip`, `connection_type`, traffic source fields, and `detection_flags`). This is where a High-scoring source becomes the exact requests that pushed its average up, ready to load into your own tooling. ## Settings and Integration Your keys, webhooks, and domains live on the Integration tab, while Settings holds your plan and request balance. Adding a [domain](/setup/domains) issues its [public and secret keys](/setup/keys), and you register webhook endpoints on the **Webhooks** tab. The keys are scoped to that one site. Settings is where you pick a plan, switch billing frequency, and watch your remaining requests, all covered on the [Billing](/billing) page. ## Reading the dashboard is free Everything here is read-only and free. Opening the dashboard, every chart and breakdown, and exporting your records do not consume requests. Billing is per identification only, so reporting and review never add to your bill. ## Next steps Visitors counted by identity, and every source ranked by the risk it delivers. Turn the score you read here into a decision in your own code.