AI assistant & analytics

A built-in "Ask AI" chat panel for your readers, and a full conversation-analytics dashboard behind it — Top Questions, Coverage Gaps, intent tags, search, digests, and more.

aardvark ships a native “Ask AI” assistant for your readers, and behind it a full conversation-analytics dashboard that turns every question into product insight. It is a first-party feature — the assistant calls the aardvark cloud gateway, which proxies the model, meters the spend, and records the conversation for analysis. There is no third-party widget to embed and no separate vendor to sign up with.

This page has two halves: the reader’s assistant (what visitors see) and the analytics dashboard (what you see). The cloud gateway page covers the billing, metering, and Stripe setup that sit underneath both.

One assistant, one bill

The reader chat and every analytics model pass (clustering, per-turn analysis, the natural-language analytics assistant) are metered to your gateway account at the gateway’s rate. You pay to analyze your own conversations; a depleted account simply pauses analysis rather than breaking. See How it’s billed.

The reader’s assistant

A floating “Ask AI” panel sits on every page. Readers ask a question in natural language; the assistant answers from your content, citing the pages it used, and they can rate each answer with 👍 / 👎. It can read the whole corpus inline on the first turn (for a fast, zero-fetch answer) or navigate page-by-page, and it accepts file attachments (images, PDFs, text/code) when you leave them on.

The built-in "Ask AI" reader panel answering a question with cited sources

Enable it

ai:
  assistant:
    enabled: true
    model: "~anthropic/claude-sonnet-latest"   # any model the gateway proxies; "latest" alias needs the leading ~

The site also needs your public gateway key baked in as the AARDVARK_KEY environment variable at build time (aardvark_live_…, never the secret key — it ships in the static site). Provisioning a key and funding the account live on the cloud gateway page.

Options

All optional except enabled:

Key	Default	What it does
`enabled`	`false`	Master switch for the reader panel.
`model`	`~anthropic/claude-sonnet-latest`	The model the assistant answers with (must be vision/file-capable if you keep attachments on).
`gateway`	the managed gateway	Base URL of the gateway Worker (include the `/v1` suffix). Point it at your own gateway to self-host.
`reasoning`	model default	Reasoning control for a reasoning-capable model (`enabled` / `effort`).
`attachments`	on	Reader file uploads — see Reader attachments on the gateway page for the caps and cost notes.
`store_history`	`true`	Posts each finished turn to the gateway so it appears in your dashboard and feeds the analytics below.
`inlineContextMaxTokens`	model-derived	First-turn inline budget; `0` forces page-by-page navigation.
`prompt`	server-side	The system prompt is not baked into the public site — set it as the key’s `system_prompt` when you mint the key.

store_history feeds the analytics

The entire analytics dashboard is built from stored transcripts. Leaving store_history on (the default) is what populates Insights, Conversations, Top Questions, and the rest. Set it to false and the assistant still works, but the dashboard has nothing to analyze.

The analytics dashboard

Every stored conversation feeds an analytics suite on the gateway dashboard — open gateway.aardvarkdocs.com/dashboard (or your own gateway host) and sign in via the magic link emailed to the account owner. (The dashboard is email-login only; the aardvark_secret_… key is the API/CLI credential — it authenticates the programmatic endpoints below, not the dashboard UI.) Cron passes on the gateway classify each answer, cluster the corpus into themes, and surface where your docs fall short.

Insights — the overview

The Insights tab is a KPI overview over a 7 / 30 / 90-day window: total conversations and answers, the reader satisfaction rate (the 👍 share of votes), the uncertainty rate, an answer-quality distribution bar (every answer is graded confident / unconfident / not_found / doc_gap from the model’s own reasoning trace), a conversation-volume series, the language mix, and a support-deflection rate.

The Insights tab: engagement KPIs, the answer-quality distribution, and the volume chart

Coverage Gaps

The companion pass clusters the uncertain answers — the questions your docs handle poorly — into recurring topics. Each gap card carries a Finding (what’s missing or confusing) and a concrete Recommendation. A Copy for LLM button drops the finding + recommendation onto your clipboard to paste into an LLM or issue, you can set a triage status, and you can export the gap as a ready-to-paste GitHub / Linear / Jira issue — the status is keyed to a stable label hash, so it survives the next re-cluster.

Conversations

The Conversations tab is the raw record: every conversation with its per-turn verdict, an intent auto-label, and any custom tags you’ve defined (up to 20 per account — you give a tag a name and a description, and the analysis pass applies it, backfilling existing conversations). A rich filter bar narrows by full-text search, verdict, vote, intent, tag, and date range, and a needs-attention view surfaces the answers worth reading. Open any conversation for the full transcript, and export the filtered set to CSV (formula-injection-guarded).

Source Analytics

Which of your pages are doing the work: most-cited sources, plus the citations that show up disproportionately alongside down-voted answers — a signal that a popular page may be misleading rather than helpful.

Periods, trends & the email digest

Snapshots are versioned by period — week, month, or quarter — so you can navigate back through history and every cluster shows a trend against the prior period. Opt in to a weekly or monthly email digest (from the dashboard) and the gateway emails the account owner a summary of the latest Top Questions, new Coverage Gaps, and headline metrics.

Ask your analytics

A natural-language panel answers questions about your own Insights data — “what are readers most confused about this month?”, “which pages get cited with thumbs-down?” — so you don’t have to read every chart. Like the clustering passes it’s metered to the account and rate-limited.

Programmatic export

For pulling analytics into your own pipelines, two dashboard-authed read APIs:

GET /v1/activity — aggregate stats (conversations, answers, satisfaction, verdict distribution, deflection, languages) over a ?days= window.
GET /v1/threads — a keyset-paginated full-conversation export with ?since= incremental sync, so a follow-up pull returns only what’s new.

How it’s billed

The reader assistant uses your configured model (a capable chat model by default). The analytics passes deliberately default to a cheap, large-context model (~google/gemini-flash-latest) so classifying and clustering a corpus stays inexpensive; an operator can override each pass independently. Every call — reader chat and analytics alike — rides the gateway’s managed upstream key and is metered to your account at the published rate. Spend can’t run away: each pass is bounded per cron tick and per account, and an account with no balance is skipped until it’s funded again. Full pricing, funding, and Stripe details are on the cloud gateway page.

Privacy

The analytics are deliberately leaner on identity than third-party tools: there is no durable per-visitor id, so the dashboard reports active conversations, never a “unique users” count. Stored transcripts keep the question and answer text (to analyze), not attachment bytes, and they age out on the gateway’s retention schedule along with everything derived from them (verdicts, tags, cited-source events).

Cloud gateway — the metering proxy behind the assistant: prepaid balances, Stripe card-on-file, auto-top-up, and reader attachments.
Build-time AI — opt-in features that run during the build (frontmatter, example API responses, skills), also via OpenRouter.
Self-hosting & MCP — running a built site, and serving it over MCP.