Sacra estimates that Peec hit $11.5M in annual recurring revenue (ARR) in June 2026, up from $5M in December.

The company went from zero to $5M ARR in its first eleven months after launching in February 2025, then doubled to $10M ARR in the five months that followed, a pace that implies roughly 15% monthly ARR growth through the first half of 2026.

Blended ARPU increased alongside revenue. At the $10M ARR mark in May 2026, Peec had 2,500+ customers, implying roughly $4,000 in ARR per customer, up from around $3,100 per customer at the time of its November 2025 Series A and around $2,000 per customer six months after launch.

That ARPU expansion appears tied to a mix shift toward larger agency and enterprise accounts. The US crossed 50% of revenue before the company opened its New York office in May 2026, and named customers now include Chanel, Hugo Boss, TUI, Zalando, Squarespace, Wix, and Axel Springer, alongside the European startups n8n, Attio, ElevenLabs that anchored the early customer base.

Agencies represent roughly half the customer base and are an important revenue driver: they start tracking two or three clients on Peec and expand to twenty-five or more, producing strong net dollar retention within that cohort.

Peec is in talks to raise a new round at a pre-money valuation of approximately $200M, roughly 2x its Series A valuation of just over $100M.

The Series A was a $21M round closed in November 2025, led by Singular, with participation from 20VC, Antler, Combination VC, identity.vc, and S20.

Before the Series A, Peec raised a €5.2M seed round in July 2025 led by 20VC, alongside a €1.8M pre-seed in April 2025 and an initial ~$120K from Antler in January 2025 following the team's pitch day in December 2024.

Total funding raised across all rounds is $29M.

Peec tracks brand presence in AI search. Marketing teams enter the questions their customers ask, things like "What's the best CRM for a 50-person agency?" or "Which travel booking site has the cheapest flights to New York?", and Peec runs those prompts daily through ChatGPT, Gemini, Claude, Perplexity, and other AI engines, storing the answers over time so teams can compare trends instead of relying on one-off screenshots.

The core dashboard reports four metrics for each prompt: visibility (what share of AI responses mention the brand at all), share of voice (the brand's slice of mentions among tracked competitors), sentiment (how positively the brand is described), and position (average rank order when mentioned).

A sources layer ties those metrics to the underlying citations. For every prompt run, Peec captures which domains and URLs the AI cited or retrieved when generating its answer. Marketers can see, for example, that a competitor is repeatedly sourced from a specific Wirecutter article, a Reddit thread, or a Trustpilot page, then decide whether to pursue coverage in that outlet, update their own content to match the format, or push for a mention in that community.

Actions automates part of that review process. Instead of manually sorting through hundreds of source URLs, it groups them into opportunity buckets, owned pages, editorial coverage, user-generated content, and reference sources, assigns each a relative opportunity score, and suggests next steps like publishing a new content type or pursuing placement on a particular class of third-party site.

Peec collects data through browser automation rather than official APIs, simulating real user sessions in the same web interfaces consumers use. The company's view is that API outputs often differ from what users actually see, including differences in cited sources and answer structure.

Two newer modules extend the platform beyond brand-level monitoring. Crawl Insights uses server log data to show which AI bots visited which pages, how often, and with what status codes, giving technical SEO teams a second lens on how AI systems access their content infrastructure. AI Shopping Analytics, launched in June 2026, lets e-commerce brands upload a product catalog and track SKU-level visibility inside ChatGPT's shopping experience, including which products get recommended, win rate, average position, and the prompt-level drivers behind recommendations.

The platform also integrates with Looker Studio for dashboarding, exposes a REST API for custom workflows, and offers an MCP server so tools like Claude and Cursor can query Peec data directly in plain language.

Peec sells B2B SaaS to marketing teams and agencies, with pricing based on the number of prompts tracked, models selected, and tracking frequency rather than seat count.

The core pricing unit is one prompt x one model x one day = one credit. A team tracking 150 prompts across three models daily burns 450 credits per day. Brand plans run from $95/month for 50 prompts to $495/month for 350 prompts, with unlimited users on every tier, a choice that reduces friction around adding colleagues or clients.

Agency plans are a separate SKU for multi-client operations, with shared credit pools, pitch workspaces for prospective clients, and centralized billing across accounts. Agencies that standardize on Peec can become multi-account revenue sources and a distribution channel for the category: they sell GEO services to clients and use Peec as the measurement layer.

The cost structure is heavier than a typical SaaS business because Peec's data collection method, browser automation rather than API calls, requires ongoing engineering to maintain across multiple AI platforms as those platforms update their interfaces. That compute and infrastructure burden likely compresses gross margins relative to pure-software peers, while also underpinning the product's differentiation claim that its data reflects what real users actually see.

Expansion is consumption-led. As teams track more prompts, add more models, or bring on more client projects, they move to higher tiers where per-prompt unit costs decline. With no per-seat pricing, internal adoption can spread without added license cost, which can increase stickiness and make the product harder to cut in a budget review.

The GEO and AI visibility category is splitting into three tiers: enterprise platforms building full execution stacks, SEO incumbents bundling AI visibility into existing contracts, and self-serve specialists competing on price and simplicity. Peec sits between these groups, with overlap above on enterprise workflows and below on self-serve monitoring.

Profound is the closest competitive comp and the most direct threat.

It overlaps with Peec on brand visibility, competitor benchmarking, sentiment, citations, and multi-engine monitoring, but extends further upmarket with autonomous agents, content generation, and integrations across AWS, Cloudflare, GA, and WordPress. Profound serves more than 10% of the Fortune 500 and has raised over $155M, which gives it procurement credibility that Peec currently lacks, particularly around compliance certifications like SOC 2 Type II and HIPAA that are required in many enterprise buying processes.

AthenaHQ competes from a similar angle, combining monitoring with on-page and off-page GEO analysis, competitor impersonation, and agentic content workflows. Its positioning is more execution-oriented, which makes Peec's monitoring-first stance look narrower by comparison.

Semrush, which generated $444M in revenue in 2025 and was acquired by Adobe for $1.9B, and Ahrefs both now offer AI visibility as a module inside their existing SEO suites.

Semrush's AI Visibility Toolkit draws on billions of prompts from its clickstream and keyword data. Ahrefs Brand Radar tracks visibility across 400M+ search-backed prompts and connects to its broader backlink, keyword, and traffic graph. Neither product matches Peec's prompt-level granularity or source citation depth, but both can be sold as a line item inside an existing SEO contract, a distribution advantage that purpose-built tools struggle to overcome.

HubSpot's AEO product, built on its acquisition of XFunnel, adds a bundling threat from the marketing suite side, offering basic AI visibility monitoring at $50/month or free within Marketing Hub Pro.

Otterly.AI competes most directly with Peec in the self-serve mid-market, offering daily monitoring across major engines, competitor benchmarking, and citation tracking starting at $29/month.

Its main threat is price floor compression: if the category commoditizes around running fixed prompt sets and recording mentions, low-cost specialists can pressure Peec from below. Peec's defense is product depth, sentiment analysis, URL-level citation gaps, competitor source analysis, MCP connectivity, and the Actions recommendation engine, but that advantage narrows if rivals close the feature gap. AirOps, which Sacra estimates at $13M ARR in 2025 and valued at $225M, approaches from the content-generation side, building toward a platform that both measures AI visibility and performs the marketing work to improve it.

Peec's core wedge is AI search analytics, but the same buyer, marketing, SEO, and content teams, controls budget across adjacent surfaces that Peec is starting to address. Its TAM expansion comes from adjacent products, a broader set of budget owners, and wider geographic demand as AI search usage scales.

AI Shopping Analytics, launched in June 2026, is the clearest near-term expansion.

As ChatGPT and Google AI Mode add native shopping experiences, which products get recommended by AI, and why, becomes a commerce analytics problem, not just a brand awareness problem. Peec's catalog-level tracking of win rate, position, mentioned price, and prompt-level recommendation drivers can pull budget from e-commerce and merchandising teams, not just SEO teams.

The Actions feature and MCP server point to a second expansion, becoming the data layer inside AI-native marketing workflows rather than a standalone dashboard. If Peec data feeds into Claude, Cursor, or internal BI tools automatically, the product becomes embedded in weekly reporting loops and harder to replace.

Peec's source classification system, distinguishing editorial, corporate, user-generated, and reference sources, maps onto the workflows of PR and communications teams, not just SEO practitioners.

Because AI answers draw on earned media, community discussions, and third-party reference pages as much as owned content, the budget owner for AI visibility is increasingly spread across brand, PR, and content functions. Peec's multi-team collaboration model, unlimited seats, shared dashboards, client reporting, fits that multi-stakeholder buying pattern.

The agency channel is a structural expansion lever. Agencies that standardize on Peec for client reporting can scale usage as they win new accounts, starting with two or three clients and expanding to twenty-five or more, without Peec running a separate sales motion for each end brand.

Peec's product is already built for multi-country, multi-language tracking, with country-level segmentation native to the platform and support for 115 languages.

The New York office opened in May 2026, formalizing the US go-to-market, which already accounts for more than half of revenue. The broader demand driver is that AI search is globalizing quickly: Google AI Overviews now reach over 2.5 billion monthly users, and AI Mode crossed 1 billion monthly active users globally in 2026, making brand visibility in AI answers a budget line in markets beyond the US and Europe.

As AI search behavior spreads to Japan, Korea, Brazil, and other markets where Peec already has customers, the addressable base for AI visibility software expands without requiring a fundamental product change.

Platform dependence: Peec's data collection stack depends on continued access to the consumer-facing interfaces of ChatGPT, Gemini, Perplexity, Claude, and other AI engines, and if any of those platforms restrict browser automation, alter how citations are rendered, or launch a first-party analytics product for marketers, Peec's core data advantage and product utility could compress faster than the company can engineer around it.

Monitoring commoditization: As Semrush, Ahrefs, and HubSpot bundle AI visibility into existing SEO and marketing suite contracts at lower incremental cost, the standalone value of a monitoring-only product like Peec faces structural pricing pressure from incumbents that can offer good-enough coverage as a feature rather than a product, a dynamic that has historically compressed the market for point solutions in adjacent categories like rank tracking and web analytics.

Execution gap: Profound, AthenaHQ, and Scrunch AI are all racing toward agentic, integrated execution stacks that both measure AI visibility and autonomously generate and deploy the content changes needed to improve it, and if enterprise buyers increasingly define the category around that monitor-plus-execute loop rather than analytics alone, Peec's monitoring-only stance risks leaving it underweight in the highest-value tier of the market.