Octolens

Octolens is an analytics tool. AI-filtered social listening across social networks, developer communities, news, podcasts, newsletters and review sites. Mentions are scored for relevance, sentiment and intent, then pushed to Slack, CRM, webhooks or an MCP-connected agent. API access is included on every plan.

Octolens is a social listening platform built around one premise: most mention monitoring tools drown teams in keyword noise, so the filtering layer matters more than the crawl. It watches social networks, developer communities, news outlets, podcasts, newsletters and review sites, then uses an AI relevance pass to score each hit for relevance, sentiment and intent before anything reaches a human. Mentions land in a single feed, get tagged as bug reports, feature requests, praise or buying intent, and are pushed onward to Slack, email, a CRM or a custom webhook. The audience skews toward product-led software companies with public-facing communities. The customer roster shown on the homepage includes Vercel, Cursor, Supabase, PostHog, Sentry and Railway, and the use cases it names are reputation defense, competitor tracking, customer feedback mining, content research and developer relations. A DevRel lead watching Hacker News and Stack Overflow threads, or a product manager collecting feature requests from Reddit, is the core user. Brands whose names are common words are explicitly addressed through the relevance scoring, since low-scoring mentions are suppressed by default. In practice the workflow starts with a keyword list that applies across every source at once. Coverage runs from Reddit, X, LinkedIn, YouTube, TikTok, Bluesky, Facebook and Instagram through Hacker News, GitHub, Stack Overflow and DEV, plus app store and Trustpilot reviews. The Scale tier adds podcasts, newsletters, web results and news from a large outlet index. Delivery is where Octolens differentiates itself from legacy listening suites: API access, webhooks and an MCP server ship on every plan rather than sitting behind an enterprise contract, so mentions can feed an internal dashboard or be queried from Claude, ChatGPT, Cursor or a custom agent. Against traditional social listening vendors, the pitch is breadth of source types and openness of data access at lower tiers. The tradeoffs are real: keyword history is shallow when you first add a term, there is no contact enrichment or influencer database, and the product assumes you already have somewhere to route the signal.