---
title: "AI visibility"
description: "Measure whether AI models recommend you. Set up topics and prompts, probe Claude, ChatGPT, Gemini, Perplexity and more on your own keys, read the share-of-voice standings, and get rank changes filed straight into your inbox."
source: https://backtalk.sh/docs/ai-visibility
---
# AI visibility

When a developer asks an AI assistant "what should I use for X?", the answer is a recommendation you never see. BackTalk asks those questions for you, on a schedule, across the models you bring keys for (**Claude, ChatGPT, Gemini, Perplexity and more**, including open models via Venice), and tracks whether the answer names you or a competitor. That slice of recommendations is your **AI share of voice**.

It runs on **your own AI keys**, like everything else in BackTalk: no markup, no metering, and the models answer exactly as they would for a real user of that provider.

## How it works

1. **You define topics.** A topic is one buying decision: the questions buyers ask (its **prompts**), the names your product goes by (**your aliases**), and the **competitors** to watch. Manage them under **AI visibility → Manage topics**.
2. **BackTalk asks the models.** On every probe, each prompt is asked several times per model, because answers vary run to run. One-off answers are noise; repeated samples are a signal.
3. **Mentions are extracted.** Your filtering model (the **What runs each task** assignment, or your default key) reads each answer and records which brands were recommended, in what order, plus any new names it saw and any citations the model returned.
4. **You read the standings.** Share of voice is your slice of tracked-brand mentions, averaged so each model counts equally: a model you probe more often than another cannot tilt the blended number. The dashboard shows the leaderboard, the trend, and per-model splits; click any prompt to read the actual answers behind the numbers. On the trend, a day when only some of your models were probed carries a faded marker, because its overall is averaged over just those models.

## Set it up

Two steps, both on the **AI visibility** page the first time you visit:

1. **Add AI provider keys** in Settings. By default every saved key's model joins the comparison; curate exactly which models compete, including several from one provider, under **What runs each task** (the **Models to compare** set). More models means a fuller picture, but even one works.
2. **Create your first topic** with a few prompts, your aliases, and the competitors you care about.

Your first results arrive on the next scheduled probe, or immediately with **Probe now** on Pro and Business.

## Probe cadence by plan

| Plan | Scheduled probes | Manual "Probe now" |
| ---- | ---------------- | ------------------ |
| Solo | Weekly | Not included |
| Pro | Daily | 6 per day |
| Business | Daily | Unlimited |

Owners and admins can dial the cadence down (or off) in **Settings → AI visibility** to save tokens; the plan sets the fastest allowed. Solo tracks up to 3 topics; Pro and Business are unlimited.

## Events in your inbox

Probe results file events into the same inbox as your listening signals, under the **AI answers** source:

- **Rank changes**, for example a competitor overtaking you on Gemini.
- **Wins**, when you take the top spot, and streak milestones at 7 and 30 days.
- **New competitors**, when models start recommending a name you don't track yet.

They obey the same triage flow as every other signal, and the AI visibility badge in the nav counts the ones you haven't seen.

## What it costs

Probing spends tokens on your own provider keys, at each provider's rates, with no markup from BackTalk. A daily probe of one topic with five prompts across four providers is typically a few cents a day; the extraction step runs on your cheapest default key. Dial the cadence down any time.

## Troubleshooting

- **A red dot on the sync trigger** means a recent probe run had a failing model. Open the dropdown, then **View sync history** for the per-model error, usually an expired or unfunded key.
- **A model's data is stale**: the dashboard says so next to the charts and keeps showing its last good numbers. Fix the key in Settings and the next probe catches it up.
- **A new topic shows no numbers yet**: it was added after the last probe. It joins the next scheduled pass, or press **Probe now**.

## Export and share

Every trend chart and the **Saved answers** shelf carry two export buttons, on the overview and on each topic:

- **Export CSV** downloads the exact series the chart plots (or the saved answers) as a bare table, ready for Excel or Google Sheets.
- **Export Markdown** downloads the same data as a formatted document that reads on its own. A trend export carries a title, the scope, the models and window the numbers were read under, the data-through and generated dates, and a short methodology note. A saved-answers export carries a title, the scope, the answer count and the date. Paste either straight into a doc, a ticket, or a team wiki.

Both are built in your browser from what is already on screen. A trend export reflects the model filter and time window you are viewing. The **Saved answers** shelf is not filtered that way: it always exports every starred answer for the current scope (all topics on the overview, one topic on a detail view), whatever the model filter or window. Nothing leaves your session. For a programmatic feed, use the API and MCP tools below.

## API and MCP

Everything above is available programmatically: `GET /api/v1/ai/topics`, `GET /api/v1/ai/share-of-voice` and `GET /api/v1/ai/answers` on the [REST API](/docs/api), and the `list_ai_topics`, `get_share_of_voice` and `list_ai_answers` tools on the [MCP server](/docs/mcp). Star or flag a sampled answer with `PATCH /api/v1/ai/answers/:id` (the `curate_answer` MCP tool), and trigger a fresh probe with `POST /api/v1/ai/probe` (the `trigger_probe` MCP tool) or the app's **Probe now**.