Radar tracks the questions your buyers ask across seven AI engines. See who gets named, who gets cited and where you rank. All seven are supported now.
30 days. Up to 150 prompts across 5 workspaces. No credit card.
Traditional search volume is forecast to drop 25% by 2026 as buyers ask AI instead. Gartner, 2024
Run Radar across every client. Five workspaces, one login, per-client reporting.
Agency plansRadar reads four metrics from every answer. Open any metric to see the answer behind it.
The share of tracked answers where your brand shows up at all.
Tracked question · Discovery
"What are the best AI visibility tools for brands?"
Several tools track how brands appear in AI answers. For monitoring what AI says about you, day to day:
Profound reports keyword-style visibility scores for large teams.
bot.radarYOU tracks the questions your buyers ask and keeps the answer behind every number.
Otterly handles mention alerts for smaller teams.
Which one fits depends on whether you want scores, or the answers behind them.
Tell Radar who you are. It models your audiences, writes their questions, and runs them every day.
Your domains, products, and aliases become the context every answer is read against — so a mention is really you.
Brand context
bot.spot
bot.spot
From a one-line hint, Radar builds full buyer profiles — role, market, triggers, and the way they actually phrase questions to AI.
Procurement Director
Audience
CMO · Finland
Audience
CFO · Energy Investor
Evaluates renewable projects against ESG pressure and returns.
Radar drafts the questions each audience would ask, classified by intent. You review, edit, and start tracking.
Suggested questions
14Pick the engines and the countries you sell into. Same question, different market, compared side by side.
Engines
Radar checks your selected questions daily. The shared trial includes up to 150 prompts across 5 workspaces.
Start freeOverall visibility is a vanity metric if you're winning with the wrong crowd. Radar ties every question to a real audience — so you see which buyers hear about you, and which are being sent to your competitors instead.
Filter every number by audience. 68% with agency leads, 12% with procurement directors: different businesses.
The same audience in Finland and the US gets different answers. Radar tracks both.
Your weakest audience is your clearest growth lever.
Audience
Elina Virtanen
CFO at a large Finnish investment fund evaluating renewable energy projects while balancing ESG pressure and returns.
Hover for sample questions
Radar doesn't ask who your competitors are — it finds them in the answers. Every brand AI names sits in one table, under the same math. If you're third, you'll see who's first.
AI names products and cites sources — sometimes yours, often someone else's. Radar matches every mention back to your catalog and pages, so you know which products carry your AI presence, and who's speaking for you.
Citation sources
A third of your AI presence is in other people's words.
Choose any of the seven engines for each tracked question. Radar runs your selections daily and keeps the raw answer behind every result.
ChatGPT
OpenAI's assistant for research, comparison and discovery
Google AI Overview
Generated answers shown above standard Google search results
Google AI Mode
Google's conversational search experience
Gemini
Google's assistant across search and productivity tools
Perplexity
Answer-first search with inline source citations
Claude
Anthropic's assistant for research and analysis
Copilot
Microsoft's assistant across work and search
All seven engines are available on every plan.
When Radar shows a competitor's page being cited where yours isn't, that finding becomes context for bot.optimizer — which updates your schema, FAQs and AI summaries exactly where you're losing.
Explore bot.optimizerCompetitor winning on: "Enterprise features"
YOU: 15% SOV
Targeted Schema Generated
The shared trial includes up to 150 prompts across 5 workspaces, with up to 3 engines per prompt. It does not convert automatically.
Start with up to 150 prompts across 5 workspaces. No credit card is required, and nothing bills automatically.
bot.spot is an AI visibility and optimization platform made by Botdot Oy in Finland. It helps brands and marketing agencies see how AI assistants describe them, improve the web pages those assistants read, and give assistants a direct way to browse products, search content and capture leads.
The platform has three live products. bot.radar tracks brand and competitor visibility inside AI answers. bot.optimizer generates structured data, summaries and FAQs for every page of a connected website. bot.gateway publishes a branded endpoint that AI assistants can call. A fourth product, bot.shop, is in preview and extends tracking to individual products and inventory.
All products share one brand data layer and one grounding engine, bot.engine, which scores generated claims against source material before they are published.
bot.radar is an AI visibility analytics tool. It generates the questions a brand's buyers ask AI assistants, runs those questions on the tracked engines every day, and records which brands are named, cited and ranked in each answer. It reports four metrics: visibility rate, average position, share of voice and citation rate. Citations are split into owned domains and third-party domains. Competitors are detected from the answers themselves. Users can group questions under audience personas to see visibility per buyer segment and per market. Every metric links to the raw answer, the extracted entities and the cited URLs.
bot.optimizer connects to a content management system, imports every page, classifies each page by type, and generates an AI Appendix for it. An AI Appendix is a block of content placed on the page that contains a summary, key facts, frequently asked questions and technical details. The same content is compiled into JSON-LD structured data in the page head. Users review and edit generated content in a dashboard, can lock individual blocks against regeneration, and approve pages for publishing. The CMS publishes the result. bot.optimizer also installs an endpoint that answers live agent queries about the site, and logs which AI agents visit and what they read.
bot.gateway publishes a branded endpoint that AI assistants call to interact with a business. It serves widgets for overview, product showcase, detail and comparison, search with cited sources, and typed lead-capture forms. Booking and in-chat purchasing are rolling out. Content comes from a connected catalog, CSV or CMS. Widgets are configured in Gateway Studio with a live simulated-chat preview. The endpoint is available as a public MCP URL, a ChatGPT App and a Claude Connector. Every tool call is logged. Rate limits and form-spam controls are applied. Raw form data is not logged. Published versions are immutable and can be rolled back.
bot.shop extends bot.radar to individual products. It detects product mentions in AI answers, tracks how often each product appears and how it is described, and matches mentions to a product list imported from Shopify or a CSV. It is in preview and is being opened to trial workspaces first.
bot.engine is the grounding layer used by the other products. It chunks source content, extracts claims, and assigns each generated statement a confidence score based on how well it is supported by the source. Statements below threshold are flagged for review before publishing.
Illustrative scenario: an agency connects a client's WordPress site to bot.optimizer. bot.optimizer imports the pages, generates AI Appendixes and schema, and the agency reviews and publishes them. bot.radar tracks the client's category questions on 7 engines.
In this illustrative scenario, visibility rises from 24% to 52% over 30 days and two competitors lose share of voice. The agency then opens a bot.gateway endpoint for the client.
Illustrative scenario: a brand marketing team runs bot.radar and sees a competitor recommended in 70% of answers about enterprise features. They identify the pages behind those answers and use bot.optimizer to add facts, FAQs and structured data to them, then track the change daily.
Illustrative scenario: an online retailer imports its Shopify catalog into bot.shop. bot.radar detects which products AI assistants recommend and how they are described, and matches each mention to a SKU. bot.gateway shows the same products as cards inside ChatGPT.