AI mentions API with sentiment analysis: eight options compared

An AI mentions API with sentiment analysis tells you two things about each AI answer: whether it named your brand, and how it described it. Most of the APIs below answer the first question. They differ a lot on the second: some label a sentence, some label a whole answer, some score the brand across many answers, and some return no sentiment at all.

heeb publishes this blog and is one of the eight options. Everything we say about the others comes from their own public documentation and pricing pages, read on October 10, 2026 and linked below.

Quick summary

Choose by what the sentiment value describes and by how you want to get the data. MentionsAPI labels the sentence around each mention, heeb labels each model answer that mentions your brand, and Sellm scores the brand from 0 to 1 with four sub-scores. DemandSphere, LLM Pulse and SE Ranking's SE Visible return sentiment on prompts you track inside their products. DataForSEO and cloro document no sentiment field, so with them you classify the answer text yourself.

What to check before you choose

Five questions separate these APIs once sentiment matters to you.

1. What the value describes. A label on one sentence keeps praise for a rival in the next sentence out of your score. A label on the whole answer also catches a caveat three paragraphs later. A brand-level score summarizes many answers and hides which one changed.
2. Label or number. Three labels are easy to count and to check by hand. A number carries more detail, but only if the vendor tells you how it is computed and keeps that method stable between reports.
3. Whether you can check it. An API that returns the answer text or the surrounding sentence lets you read why a label is negative. Without the text, you are trusting the classifier.
4. On demand or tracked. Some APIs answer a request you send now. Others expose data from prompts you set up in their product, collected on its schedule.
5. How you pay. Prepaid credits suit occasional or bursty use. A subscription suits a fixed set of prompts you check every day or week.

Sentiment in eight AI mentions APIs

Read from each vendor's documentation and pricing page on October 10, 2026. Plans and prices change, so follow the pricing links before you budget.

Strengths and limits of each option

heeb

heeb is an API for brand mentions in AI answers. One request sends a prompt to the model families you choose (OpenAI, Anthropic, xAI, Perplexity and Google AI Mode) and returns each answer's text, the brands the answer puts forward with their positions, its sources and citations, a mentioned flag and a sentiment label. Because the answer text comes back with the label, you can check any label against the words behind it.

Two limits matter for sentiment. First, heeb classifies sentiment only for answers that mention your brand. An answer that does not mention it still returns sentiment: "neutral", but that value is a placeholder, not an assessment, and the aggregate scores.sentiment currently averages every successful answer, placeholders included. Read mentioned before you read a label, and compute your own average over mentioned answers if you need one.

Second, mentioned is true when a brand name extracted from the answer matches the name you sent, ignoring case. If the extracted name differs, even by a suffix such as .com, the answer counts as not mentioned and gets no sentiment. Send the name the models are likely to use, and check the mentions list when a result looks wrong. A request also covers one brand, so a rival's sentiment needs its own request.

MentionsAPI

MentionsAPI's brand extraction docs define sentiment as the sentiment of the sentence that contains the mention, not of the whole answer, and return that sentence as context. That is the finest documented unit here, and context makes every label quick to audit.

Check which endpoint you build on. The sentiment field is documented on /v1/extract_brands and the older /v1/ask, and both pages mark themselves as legacy and point new integrations to /v1/check. The /v1/check reference does not list a sentiment field.

Its documented providers are OpenAI, Anthropic, Gemini and Perplexity. The extraction docs also note no alias map, so each spelling of a brand is its own entry.

Sellm

Sellm's LLM Mentions API returns an overall summary.sentiment from 0 to 1 and, per result, a brandSentiment object with four sub-scores: trustworthiness, authority, recommendation strength and fit for query intent. It covers ChatGPT, Claude, Perplexity, Gemini, Grok and Microsoft Copilot, runs each prompt several times (Sellm calls these replicates) and reports share of voice and coverage.

It is the only option here that breaks sentiment into named dimensions. The page does not explain how those scores are produced, so read a sample of answers before you report a change in one of them.

DemandSphere

DemandSphere's LLM API documents a /v5/llm/sentiment endpoint that returns a polarity score, a magnitude, a category of positive, neutral or negative, and trends over time windows you choose. The data covers prompts you track in the DemandSphere platform, which also tracks classic search rankings. Its pricing page lists ChatGPT, Gemini, Perplexity, Google AI Mode and AI Overviews.

It fits a team that wants AI answers and SERP tracking in one subscription. The public page summarizes the fields rather than publishing a full schema, so ask for one before you build on it.

LLM Pulse

LLM Pulse's Answers API returns each stored AI answer with its mentions, citations, sources and a sentiments list. The documented example carries an analysis label, a numeric score, a short comment and topics such as quality or reliability.

The comment and topics explain a label better than a bare number does. The data comes from prompts tracked in an LLM Pulse project across ChatGPT, Perplexity, Gemini, Google AI Mode and AI Overviews, and the pricing page lists API access on the Scale plan and above.

SE Ranking SE Visible

SE Ranking offers two AI APIs, and only one returns sentiment. The SE Visible API, marked beta, returns positive, neutral or negative toward the brand in prompt results, plus aggregate metrics such as a sentiment score and the share of positive, neutral and negative results. SE Ranking's separate AI Visibility API reports brand mentions, links and share of voice, without a sentiment field.

SE Visible covers ChatGPT, Google Gemini, Perplexity, Google AI Mode and Google AI Overview. It works on projects and tracked prompts, and usage counts against plan limits rather than per-request credits.

DataForSEO and cloro

Neither documents a sentiment field. DataForSEO's LLM Mentions API searches its own collection of AI answers from Google's AI Overview and from ChatGPT (US only) and returns questions, answers and cited sources. cloro returns the answer text and sources for each engine you query, including ChatGPT, Perplexity, Gemini, Microsoft Copilot, Grok and Google AI Mode.

Both give you the text to run your own sentiment model on. That is a good choice when you want to control the method, and extra work when you want a field you can store as it arrives.

Which API fits which buyer

• You need to know which sentence turned negative. MentionsAPI, if you can build on its extraction endpoints.
• You check a set of questions across several model families and keep the raw answers in your own database. heeb returns the answer text, ranked mentions, citations and a label per model in one result, billed per model call with no subscription.
• You report trust or authority as separate measures. Sellm, after you have checked the sub-scores against the answers.
• Your team already works in an SEO suite. DemandSphere, LLM Pulse or SE Visible expose sentiment on prompts the subscription tracks.
• You want your own classifier. cloro or DataForSEO return the text; you add the sentiment step.
• You want to start without paying. MentionsAPI and heeb both give new accounts free credits for a first test on your own questions. cloro has a free monthly tier, without sentiment.

Next step

Pick two questions where you expect AI answers to disagree about your brand, run them through the two APIs you shortlisted, and read every negative or neutral label against the answer text. To try heeb, the LLM Mentions API walkthrough covers the API key, the request and fetching the result, and the API reference lists every response field.