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Looking for experience!

A rep opens the CRM Monday morning. A target account: "no recent activity." They move on. Meanwhile that same account just posted 40 sales roles, closed a round, and quietly repriced - on the open web, where the CRM never looks. That gap is where pipeline dies. (76% of companies say fewer than half their CRM records are accurate - Validity, 2025.) Markster Recon closes it. Point it at any company and it runs a real pipeline, not a prompt: COLLECT - six Bright Data products fire in parallel: LinkedIn hiring (Web Scraper API), news + funding (Web Unlocker), competitor landscape (Discover API), market results (SERP API), JS-rendered pricing (Browser API), and funding research (Deep Lookup). SOURCE - every datum carries provenance: source URL, timestamp, method. Click any claim and verify it live. Nothing is unattributed. SCORE - confidence is computed (coverage x signal strength), not guessed by a model. SYNTHESIZE - the LLM writes the Account Action Plan: the read, routes in, who shapes the decision, honest evidence gaps, next actions. It writes narrative only - it can never invent a signal. Then the part most projects skip: Recon acts. It writes the decision into a live HubSpot - gtm_* properties, a sourced note on the timeline, and an urgent task where an AI agent executes or prioritizes for the rep. And it polices itself: a thin or low-confidence run is gated to "review only," so a weak signal can never look like an approved action. It is a standing watch on your target list, not a one-time lookup: run the loop on a schedule and you catch the window the day it opens. Judge-testable, no login: any company returns a full plan plus a preview of exactly what hits the CRM. It runs on a real production CRM, and synthesis is provider-portable - Azure OpenAI, AI/ML API, or open-source via Featherless. Built by a team that runs GTM on this exact stack. Live web -> sourced signal -> CRM action. That's the loop.
31 May 2026