
Floqer is a GTM copilot that enriches leads from 75+ trusted data sources and uses AI agents to do the manual research your team shouldn’t. Start with a domain or list; Floqer finds people and companies, fills firmographic and contact fields, and summarizes relevance with citations. Intent-style signals and rules route prospects to the right play, while scoring, dedupe, and monitoring keep lists clean. The result is qualified pipeline without tab-hopping, spreadsheets, or ad-hoc scraping.
Connect a domain, list, or CRM export and let Floqer enrich records against 75+ industry data providers. It fills company and contact fields, normalizes job titles and industries, and returns evidence so operators can spot gaps or errors fast. Because enrichment is AI-assisted, you get summaries of why a record matches (or doesn’t) instead of raw fields alone. This yields cleaner inputs for outreach, scoring, and routing—without managing dozens of separate APIs.
Offload repetitive GTM digging to agents that read websites, news, and profiles to extract buying cues—tech stack mentions, initiatives, locations, and recent moves. Agents write human-readable notes with links so reps don’t re-do the work. Use prompts and guardrails to tailor what the agent collects per segment, then store results alongside each record. This turns unstructured web context into structured, reusable facts your playbooks can act on immediately.
Set up lightweight “if this, then qualify” rules that watch for intent-style signals (new hires, product launches, hiring pages, or blog themes) and update fit scores or route to the right owner. Combine signals with firmographic thresholds to prevent noisy lists. Because signals and enrichment live together, your team moves beyond static lists toward a living system that surfaces the few accounts worth time this week—reducing wasted touches and faster first meetings.
Keep databases trustworthy with automatic deduplication, domain/contact collision checks, and standardized fields. Apply scoring that blends fit (company traits) and interest (signals, freshness) so the best records rise to the top. Side-by-side comparisons make it easy to merge variants, while activity logs preserve what changed and why. Cleaner, ranked lists translate directly into higher reply rates and lower ops toil—especially when multiple teammates prospect in the same markets.
When records are ready, push them to the next step with exports, webhooks, or native connectors. Assign owners, add tags and notes, and share “research packets” that include the agent’s findings and links. Ops can create shared views by segment, while sellers leave feedback that trains rules over time. This closes the loop between research and outreach, so the same enriched source supports email, ads, and calling—without reformatting lists or chasing missing context.


B2B GTM teams that need reliable enrichment and prospect research without a patchwork of point tools: founders and first sellers, lean RevOps, agencies, and SDR pods. Useful for companies replacing manual web research and multi-tab enrichment with one workflow; ideal when intent-style signals, list hygiene, and explainable summaries matter more than raw volume. Great for startups moving from spreadsheets to a repeatable pipeline engine that scales with headcount.
Replaces scattered scraping, guesswork, and stale spreadsheets with a unified enrichment and research layer. It solves missing context (agents summarize “why this account”), noisy lists (signals + scoring + dedupe), and slow routing (rules that push to the next step). Teams spend less time hunting fields across tools and more time contacting accounts that match current priorities—building qualified pipeline faster and with clearer evidence behind every prospect added to the queue.
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