Every capability we have shipped — from the first evaluation agents to AI Share of Voice, the Fact Checker and enterprise-grade coverage.
If you sell in the Netherlands, you could not see what AI tells a Dutch buyer about you. Now you can.
You can now track the answers that a buyer in Amsterdam gets, asked in Dutch, as you already track other European markets. A brand that sells in the Netherlands sees where it wins and where a local rival takes its place, before it puts budget into that market.
When an engine cites a Facebook post as its source, you could not see what that post said about your brand. Now you can.
Genezio now reads the Facebook posts, videos, reels, pages and events that the engines cite, as it already reads LinkedIn and Instagram. A consumer brand can see which community pages and which posts shape the answers about it, and decide where to show up or what to correct.
You cannot fix what you learn about too late. This release tells you which of your targets are at risk while you can still save them, which of your pages the AI engines cannot read, and which engine answers your buyers without you.
You learn that a target is at risk weeks before the review, and not in it. The goals that need you come first, thus a quarter no longer ends with a surprise.
You can see where you win and where you are absent, one engine at a time, and you can show your CMO the answer as a buyer meets it. An engine that leaves you out is a market you can now name and work on.
Some of your best content is invisible to the engines, thus it earns you no citation and no mention. Genezio names those pages and the exact text to fix, and content you already paid for starts to work.
See Content AnalysisA false claim about your brand reaches you while it is still small, and not after your customers find it. Your reputation no longer waits for somebody to remember a check.
A brand with hundreds of citations sorts them in minutes. You also see which creators and which social accounts the engines trust about you, thus you know who to work with.
Knowing that an engine mentions you is the start. This release tracks whether the specific claims it makes about you hold up over time, shows which AI bots actually read your site, and opens the platform's data to your own tools through a public API.
Pick a claim about your brand and Genezio tracks it across every run: how often AI answers agree or disagree, how that agreement moves over time, and how it differs from one model to the next. Each verdict keeps the pages it cited, so you can see which domains sit behind the answers that get you right and the ones that get you wrong.
Account owners create API keys, each limited to the brands it needs, and read Genezio data from their own reporting stack. The API covers visibility, recommendation, citations, sentiment, fact checking, query fan-outs, products and conversations, and manages topics, scenarios, competitors and personas. It is described in OpenAPI and documented with a full reference.
ChatGPT now shows sponsored placements inside answers. A new Ads page captures each ad in your tracked conversations and shows who advertises on your topics, which creatives they run, the topics and scenarios that trigger them, and your share of ad visibility against competitors.
Upload an access log from your site or CDN and see which AI bots visit, what they read, how your server answers them, and how often the pages they read end up cited in AI answers. Each visit is checked against the IP ranges that the AI providers publish, so a fake user agent shows up as unverified instead of inflating the count.
For each website of a brand, Crawlability reads robots.txt and the sitemaps and shows which of 49 AI bots can crawl the site. A host is flagged when a main AI search bot is blocked, when robots.txt is unreachable, or when no valid sitemap exists.
Account owners define their own roles and give each one a level for every area of the product. Members and invites take a custom role or a built-in one.
Content Hub now shows the plan of an article for your approval before it writes, and one run produces every format you ask for.
An MCP client such as Claude can now create and change Scorecard goals. The goal agent does the build, the same way it does in the dashboard.
See the MCP serverDashboards answer the questions someone thought to build them for. Scorecard answers yours: describe a business goal in plain words, and an agent turns it into a metric that updates every day.
Describe a goal in a conversation, for example the share of recommendations you win against one competitor in one market. The goal agent writes the metric, runs it on yesterday's data every day, and puts it on a board you arrange yourself.
The New Content wizard starts with the content type, and a brief can generate its own type. Each version highlights the text that changed, and an article gives its schema.org JSON-LD markup.
See Content HubContent Analysis has a mode for landing pages, and it can start one analysis for each URL of a list.
See Content AnalysisA brand can seed its topics from a Search Console CSV export, which works without a live connection.
Each persona shows its country, and its conversations take that country's language.
Genezio now connects to the two places your traditional web data already lives, so AI visibility can be read next to the traffic and the search behaviour around it.
A native GA4 connection that correlates AI visibility and recommendation metrics with downstream web traffic behaviour, including attribution for AI-influenced visits that arrive without a referrer header.
Connect Search Console to a brand to correlate traditional search visibility with AI recommendation trends, and to generate topics directly from the queries your site already ranks for.
The market moved from “are we mentioned” to “are we mentioned correctly.” This release followed it: a new headline metric, an agent that catches false claims, and the enterprise certifications and coverage to run all of it at scale.
A new headline metric measuring a brand's share of visibility across AI answers versus its competitors, with sentence-level brand attribution per AI response.
The Knowledge Base Layer is a brand truth layer that verifies what an AI engine states during a conversation. The Fact Checker agent sits on top of it and flags when an engine says something false about your brand — bringing the agent suite to five: Prompter, Comparer, Introspector, Recommender and Fact Checker.
How AI talks about a brand, not just whether it does: tone, trend over time, and an AI-perceived SWOT.
Captures the exact text fragments AI engines cite and maps them back to the source sections they came from, so you can see which passages are being retrieved and which are ignored.
See Content AnalysisProcess server logs to show which AI crawlers visit a site and which of those visits turn into citations — tying crawl activity to real server traffic instead of estimates.
A new module for tracking product and retailer visibility inside AI shopping conversations. Launched and in active testing with clients.
See In-Chat ShoppingSOC 2 Type II certification achieved, removing a recurring blocker in enterprise procurement, alongside broader authentication and coverage.
Reusable templates for generating on-brand articles and briefs, plus the ability to choose which AI engines run on each topic for more granular testing.
See Content HubSelf-serve onboarding went into production in January, and the product consolidated around four specialised agents — each with a strategy adapted to the customer's business type.
Self-serve functionality went live in January, removing the manual setup that every new account previously depended on.
Prompter, Comparer, Introspector and Recommender were refined into a coherent suite, each running a strategy adapted to the customer's business type. Personas and multi-turn conversations were sharpened as the core differentiators.
Explains why a competitor's article gets cited — comparing the content against the topic and scenario it is winning on.
See Content AnalysisGenerate an article or a brief from a topic, a set of keywords and a subject, closing the gap between finding a content gap and filling it.
See Content HubDirect brand-versus-competitor comparison, and clustering of the fanned-out queries an engine generates from a single prompt.
Every citation is now classified as first-party, competitor, social media, news or community, which required auto-detecting the domains each competitor owns.
Ask questions of your own visibility data in natural language, including through the Genezio connector for Claude as a skill and over MCP.
See the MCP serverBrand Analysis became the primary driver of sales conversations, so it was rebuilt from the ground up — new interface, deeper analysis types, and a mode for agencies running several brands.
A rebuilt interface, significantly more advanced than the previous dashboard and designed for deeper analytical exploration.
Analysis now works at the level of the queries an engine fans out from a prompt, and of the individual statements it makes about a brand.
Introspector, Recommender and Comparer joined the product as distinct topic types, each probing brand presence from a different angle.
Agency mode in Brand Analysis, for teams running the platform across multiple client brands.
For agenciesBrand Analysis went from feature to finished product, with coverage across the four engines that mattered most to customers, and user management to go with it.
The Brand Analysis feature was completed — a periodic report giving customers insight into their brand's visibility across leading LLMs.
A brand can now be analysed across ChatGPT, Google AI Overview, Perplexity and Google AI Mode.
User management functionality was added to the dashboard.
The agent library grew in both directions — existing agents got better, and three new ones covered ground the suite had been missing.
Industry Bias, Sanitization and Capability Detection joined the evaluation agent library.
Fact Checker, Functional Tester, Offtopic, Competitor Advertising and Security were all improved.
A dashboard showing how a chatbot has evolved over time, rather than only how it performs in a single run.
Audit logs were added to the platform.
The platform pivoted: a new core product for evaluating agentic AI applications, with a dashboard, a scalable simulation engine, and the first library of testing agents.
A new core product, with a dashboard where clients manage knowledge bases, personas, test agent libraries, simulations and detailed reports.
Clients can run thousands of conversations in parallel, across multiple languages and configurations.
The first version of our own suite of testing agents, covering three families.
