Changelog

Stay up to date with the latest changes in our product.

August 15, 2026

Filter the scans list by query, topic, date, and trigger

Saved query — a searchable picker (same interaction as the scan form's
Topic — scans whose query belongs to the selected topic.
Date range — from/to days (UTC) on the scan start time; a single-day
Triggered by — manual runs vs scheduled/cron runs.
All filters are URL-driven, so a filtered view survives refresh, works with

August 15, 2026

Connect AI assistants: every workspace gets an MCP server

Per-workspace endpoint — /api/orgs/<workspace-id>/mcp, shown with
Sign in with your account — connecting opens a one-time browser OAuth
Read-only tools — list_scans, get_scan, insights_summary,

August 15, 2026

Freeze your PRO price during beta

Freeze the beta price — PRO isn't sold during the beta, so instead of a
Free stays fully open in beta; nothing is billed yet.

August 14, 2026

Scan beyond 25, and scheduled scans get a dashboard

"Scan all N" on the Queries page — queue every query matching your current filters (search, topics, importance, status) as one background job. No 25-query manual-selection cap, restart-safe, and queries already running are skipped, never double-billed. The manual cap now explains itself instead of silently graying out checkboxes.
Bulk form "Run all" honors your text filter — and is available on every status chip, including "All". The set the button launches is exactly the set the list shows.
Scheduled scans are configurable in the app — Settings → Scan execution → Scheduled scans. Daily / weekly / monthly cadence, model subset, local-time picker, and per-run cost shape ("N queries × M models") before you enable anything.
Per-topic schedules — give one topic its own rhythm. A topic with its own enabled schedule is excluded from the workspace-wide run, so no query is ever scanned twice for the same cadence.
An "Auto-scan" chip on the Queries page shows the next scheduled run at a glance.
Hand-picked schedules — schedule just the queries you choose (up to 50 per set, any number of sets, each with its own cadence). Pick them in the schedule dialog's searchable selector, or select rows on the Queries page and hit "Schedule these". Hand-picked and topic schedules both exclude their queries from the workspace-wide run — nothing scans twice.
The schedule dialog's topic picker is now searchable and shows each topic's query count.
Topic pages: searchable, filterable query list — the "Queries in this topic" table now has text search, status (never / stale / run today) and importance filters, plus pagination at 25 rows, matching the main Queries page.
Scan schedules moved to their own settings page — Settings → Scan schedules, right after Scan execution. Old "Schedule these" links forward automatically.
Upcoming runs on the Scans page — when schedules are enabled, a read-only strip above the scan history shows each schedule's scope, cadence, and next run ("when does money leave"), with a manage link for admins.

August 14, 2026

Dashboard explore board and Insights as a period report

Analytics is no longer a third Analyze page. /analytics redirects to the Dashboard explore board. The full prompt library stays on Queries.
Dashboard is briefing + board. Visibility hero (mention rate, platforms, ranking) sits above an Explore grid: channel influence, branded vs unbranded topics, composition radar, query shape, top 6 prompts, and content gaps. Each tile can expand or export a CSV of what you are looking at. Admins can still download the full analytics roll-up.
Insights is the period report. Summary and findings first, then this-window KPIs, visibility (share of voice), and across-reports history. Page load never generates a narrative — Generate is still a click. Topic reports call the topic procedure, not the workspace one.
Honest empty states. One scan day shows a labeled baseline, not a blank chart. Across-reports and thin topic momentum are one-line notes until a second report exists. A 90-day share-of-voice chart buckets by week.
Numbers come from stored scans. Channel types, branded queries, presence, and prompt scores are deterministic roll-ups of analytics_daily — no invented Trust/Authority axes, no model on load.

August 14, 2026

See the pages the AIs cite, and take the data anywhere

Cited pages — a new view under Analyze showing every page the AI platforms cite for your queries, per platform, with citation counts, average citation rank, the queries that triggered them, and a "My pages only" toggle that spotlights your own site. Click any row for the full breakdown and a link to the page.
Citations export — Settings → Data export → Citations: every stored citation as CSV or NDJSON with scan, platform, and query context on each row. Built to join with Google Search Console, Semrush, or BigQuery on the canonical_url column — pair "which pages LLMs cite" with "which pages rank" outside the app today.
Google's grounding citations (opaque redirect links) are handled honestly: never fabricated as pages, counted at domain level with a footnote, and flagged is_provider_redirect in the export.
Everything here is pure reads from data you already collected — no model calls, no new cost.
Answers export — Settings → Data export → Answers: every LLM answer as text (CSV or NDJSON), one row per platform response with query, model, and per-answer cost. Joins the Citations export on the new response_id column, so you can pair every answer with the exact URLs it cited.

August 13, 2026

Export insights, queries, and analytics from Settings

Settings → Data export is now a hub, not only the GDPR dump. Admins can download topics and queries (grouped by topic), insights reports, and the daily analytics roll-up from one page.
Downloads read stored rows only. Opening the page or clicking download never runs a scan and never generates a new insights narrative.
“Query library”, not “prompts”. The tracked queries you scan sit in one file; the per-scan prompt copies stay in the full workspace backup, where they already were.
Cost CSV is unchanged — it still lives on Settings → Cost, with a link from the hub.
Full workspace backup is still there (JSON + scan-history CSV), same streaming contract as before: the last line tells you the file is complete.

August 13, 2026

Choose current models for provider scans

Per-provider model selection — workspace admins can now choose a current OpenRouter or Direct model for each scan provider, while keeping the historical pinned model as the default. Catalog refreshes list models without running them, and changing a model is clearly marked as a new measurement epoch.

August 7, 2026

Brand matching stopped dropping case-variant aliases

An alias that differed from your brand name only by capitalisation was silently discarded. If your brand was stored as "NiCE" and you added "NICE" as an alias, the alias never reached the matcher: terms were de-duplicated case-insensitively while matching ran case-sensitively, so "NICE" looked like a duplicate of "NiCE" and was thrown away. You did the right thing and nothing happened, which is the worst way for a feature to fail.
Measured impact before the fix, on one real workspace: of 141 scan responses, 95 contained a standalone "NICE" and 2 contained "NiCE". Nineteen brand-bearing responses recorded no mention of the tracked brand at all — roughly a 20% undercount, partly masked because the AI extractor rescues mentions the pattern misses.
Nothing changes for case-insensitive brands. They still fold every casing into one term. The reason case-sensitivity exists is unaffected too: "that's a nice feature" still doesn't count as a mention of NICE.
Historical mentions are not re-scanned. Existing rows keep the results they were extracted with, stamped matcherVersion: 2; new scans use version 3. If a brand of yours has a name that is also a common word, adding the exact casing you see in the wild as an alias now actually does something.

August 7, 2026

Analytics now rebuild themselves every night

Daily analytics are re-derived from your raw scan data every night instead of being accumulated once. Previously each finalized scan added its contribution to a running total, which meant any miss was permanent: re-extracting a response, or recovering mentions after the fact, could never correct a number that had already been counted. Now the figures are recomputed from source, so a correction lands on its own within a day.
Some numbers may shift once as history is recomputed. They are moving toward what your raw scan data actually says. Domain and citation tallies in particular become exact rather than approximate, because they are no longer built by merging capped snapshots in arrival order.
Topic momentum now compares against a bounded baseline. It used to take the oldest surviving snapshot as its "before" value with no age limit, so the longer a workspace ran, the further back "momentum" reached. It is now capped at twice the selected window, matching every other period-over-period comparison in the product. A topic whose only baseline is older than that reports no momentum rather than a number measured against a different era.

August 6, 2026

Your workspace export now streams, and the format changed

The export is NDJSON, not one JSON object — this is a breaking change if you parse it. Each line is a self-contained {"kind":"response","row":{…}} record instead of a single document with a responses array. Anything that did JSON.parse(wholeFile) needs to switch to line-by-line. The trade is that the export now works at all: it was returning a single buffered response, and a Vercel function caps that at 4.5 MB. Any workspace past roughly 450 responses got a 413 instead of a download.
The last line tells you the file is complete. A download cut short by a timeout is still valid NDJSON and silently missing the tail, so the final record is {"kind":"complete","counts":{…}} with a per-table row count. If you don't see it, treat the file as partial. The CSV gets the same guarantee as a trailing # complete,<rows> row — more important there, because a short CSV opens cleanly in Excel with nothing to indicate anything is missing.
The filename carries your workspace slug again — brandbanta-<workspace>-<timestamp>.ndjson. Resolved server-side, so two workspaces never produce two identically-named files.
`rawResponse` is included. It's your data, and now that size isn't fatal there's no reason to withhold it. Embedding vectors stay out: ~3 KB per row and useless without the same model and index.

August 4, 2026

Chat searches your scan history by meaning

Chat now retrieves by semantic similarity instead of "the 200 newest rows" — asking "what do people say about our pricing?" now finds the mentions that are actually about pricing, wherever they sit in your history, rather than whatever happened to be recent. Workspaces with no embeddings yet keep the old chronological behaviour, so nothing regresses while the backfill catches up.
Retrieval degrades instead of failing — a missing key, a rate-limited embedding call, or a database fault falls back to chronological history and still answers the question. A failed read is never reported as "you have no scan results yet", so an established workspace is never told to go run its first scan.
Embedding spend is metered like every other model call — text-embedding-3-small is priced in the ledger under both its bare and namespaced ids, so the per-turn query embedding records a real, non-null cost against the budget cap rather than disappearing as unknown pricing.
Embeddings are written only when a scan finalizes, or by an explicit operator backfill — opening a chat never triggers one. The backfill skips demo workspaces, which hold fictional data.

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