# Demand-Genius B2B-specific AEO and content-intelligence platform that tracks how AI engines present a brand to buying committees and ties content to pipeline and revenue, with customers including Braze, Cognism, Captify, Sensat, Cleo, and TryHackMe. Funding not disclosed. Recent work: an evolution from manual content attribution into an AEO platform with AI agents, intent-cluster visibility tracking across five engines, and a stakeholder-mapping agent. ## Scores | Score | Value | Why | |---|---|---| | Presence | 52 | Early and small (2-10 staff); funding not disclosed, but real B2B logos (Braze, Cognism, Captify) | | Velocity | 58 | Shipping fast off a 2024 launch; evolved attribution → AEO platform, steady content research cadence | | Agent-Readiness | Low | No API, MCP, SDK, CLI, or llms.txt found | *Product-overall scores from the AdamGTM Analyst Desk (floor 50). Canonical, always-current: https://stack.adamgtm.com/aeo* ## The Solution & Approach Demand-Genius is an AEO platform built specifically for B2B revenue teams. It runs prompts across ChatGPT, Gemini, Perplexity, Claude, and Copilot and aggregates the results at the intent-cluster level rather than tracking individual queries. The reasoning: any single buyer intent has hundreds of possible prompt variations, so clustering by intent gives a visibility score, citation rate, and mention rate that reflect the full range of how buyers actually ask, not one phrasing. That intent-cluster framing is its core measurement bet. The product started life as a content-attribution tool with slow, manual setup and grew into a broader AEO platform. The Content Intelligence side deploys AI agents that score content across dimensions like differentiation, citability, extractability, and accuracy, with custom agents for brand-specific attributes, and it analyzes your site or a competitor's by URL with no integration required. A stakeholder agent maps how AI currently describes a brand against the priorities of each person in a buying committee. What separates it from the broad-market AEO crowd is the B2B-plus-revenue angle. Demand-Genius connects AI-visibility signals to buyer-journey and conversion data so a team can see which AI conversations correlate with deals and invest in what moves revenue rather than chasing referral volume. That pedigree is no accident: the founders met at Zephr, a subscription/paywall platform, and the attribution DNA shows. ## Best for B2B marketing and demand-gen teams with an existing content library that want AEO measurement framed around buying committees and pipeline, not generic brand-mention counting. The customer roster skews mid-market-to-enterprise B2B SaaS. ## Pricing & trial Self-serve and transparent: a Free tier (default intent clusters, monitoring across the major LLMs, basic content audit), Smart at $99/month (custom clusters, competitor comparison, ICP/stakeholder segments), Genius at $399/month (deeper audits, journey mapping and attribution, onboarding), and a sales-led Super-Genius tier for multi-product/multi-region. Annual billing saves 20%. A consultant-led AEO Strategy Sprint is offered separately. [Pricing](https://demand-genius.com/pricing/). ## Agent Experience How you build on this platform (or wire it into your own agents): | Surface | Available | Docs | |---|---|---| | API | No | — | | MCP | No | — | | SDK | No | — | | CLI | No | — | | llms.txt | No (404) | — | No public developer or agent surfaces found. Demand-Genius is a use-it-in-the-UI product today; there is no documented way to wire its data into your own agents. Higher tiers add Slack/Teams support for humans, not a programmatic interface. ## Reference customers Braze, Cognism, Captify, Sensat, Cleo, TryHackMe. ## Case studies & customer stories - No named, public customer case studies found as of 2026-06-06. The site publishes benchmark research (below) rather than per-customer stories. ## Recent moves - **2026-05-13**: Published a detailed account of evolving from a manual content-attribution tool into an AEO platform with AI agents — sitemap scraping replacing manual URL entry, 14 content-analysis templates, intent-cluster aggregation, and a stakeholder agent. [source](https://demand-genius.com/resource/how-demand-genius-evolved-from-manual-content-attribution-to-aeo-platform/) - **~2026-02**: Posted analysis of 50,000 B2B content pieces, finding only ~7% of newly published content is evergreen and under 20% shows strong authority signals. [source](https://www.linkedin.com/company/demand-genius) - **~2025-12**: Released a benchmark report on 50,000+ pages from 50 B2B fintechs covering AI-era content adaptation. [source](https://www.linkedin.com/company/demand-genius) - **~2025-10**: Announced a partnership with Superpath on a first annual Content Attribution Report, noting only 11% of content teams feel most of their impact is captured. [source](https://www.linkedin.com/company/demand-genius) ## Company, Financials & Funding History Founded in 2024 by Tom Rudnai (Founder/CEO) and James Carter (co-founder), who met at Zephr, a subscription/paywall technology company. Development began around April 2024, with a bare-bones launch in October 2024 and the first proper version by end of 2024. The team is small (2-10 employees) and the company has been featured in PreSeed Now (March 2025), suggesting an early, pre-seed/seed-stage profile. **Funding not disclosed.** No round amounts, investors, or valuation were found in public sources as of 2026-06-06. ## Analyst placement None found. Demand-Genius does not yet carry a G2 category placement, analyst grid position, or verified review presence as of 2026-06-06. ## Links [Homepage](https://demand-genius.com) · [Pricing](https://demand-genius.com/pricing/) · [Content Intelligence](https://demand-genius.com/use-cases/content-intelligence/) · [LinkedIn](https://www.linkedin.com/company/demand-genius) *Last updated 2026-06-06 · refreshed weekly*