Explee

A sales development rep at a software company spends hours scrolling LinkedIn for fintech companies with 50-200 employees in the Midwest

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A sales development rep at a software company spends hours scrolling LinkedIn for fintech companies with 50-200 employees in the Midwest. She manually builds lists, hunts for decision maker emails, then enriches each lead one by one. Explee replaces that entire workflow with AI search across 103 million companies and 536 million decision makers. She filters by industry, size, location, and technology stack, then pulls email addresses and phone numbers for marketing directors in one export. This system converts credits into data points, where 100 credits cost a dollar and get you varying amounts of company profiles, contact details, or enrichment runs.

Explee works through three overlapping databases. The global B2B set covers companies worldwide. The Google Maps dataset adds 218 million entries for local businesses and storefronts. The US-specific slice includes 17 million companies and 100 million decision makers with deeper detail. A lookalike company finder identifies businesses similar to your best customers by analyzing firmographics and digital footprints. Semantic search understands queries like "European SaaS companies hiring aggressively" without exact keyword matches.

Custom AI enrichment fills data gaps you define. A growth marketer at an agency wants to know which prospects use Salesforce and have raised funding in the past year. She sets those as enrichment criteria, and the system researches each company to populate those fields. Free accounts get three criteria and 2,000 rows of enrichment. Pro accounts handle up to 50 criteria while enterprise goes to 100 criteria across 10 million rows.

A business development manager at a consulting firm needs contacts at manufacturing companies expanding internationally. He searches for manufacturers with recent job postings in foreign markets, exports the list, then enriches it with CFO and operations VP emails. The segments explorer groups companies by patterns the AI detects, surfacing clusters he wouldn't think to filter for manually.

The credit system creates budgeting friction. Accessing a company profile costs credits. Pulling an email costs more. Phone numbers cost the most. A free account gets 500 welcome credits, which translates to 1,000 company records or up to 333 emails depending how you spend them. Credits expire after two months on paid plans, so unused allowances vanish. Export limits cap how much data you can pull at once. Free users max out at 2,000 records per export. Starter accounts allow 5,000. Only Pro and Enterprise get unlimited exports.

Explee lacks integrations. There's no CRM sync, no Zapier connection, no way to push enriched data directly into Salesforce or HubSpot. You export CSV files and upload them manually. Teams working across multiple tools face constant import-export cycles. The multi-seat access helps collaboration, but everyone still operates inside Explee's interface rather than their existing stack.

Starter plans at 49 dollars monthly include 5,000 credits and one seat. Growth at 329 dollars adds five seats and 40,000 credits. Pro costs 490 dollars with unlimited seats and 75,000 credits. Enterprise pricing stays custom.

Companies without dedicated sales ops struggle here. The credit math requires planning. Running out mid-month means upgrading or waiting. Small teams doing occasional prospecting pay for credits they won't use. Businesses already locked into other lead databases face duplicate costs. Solo consultants and freelancers looking for a few contacts quarterly should skip this. The free tier works for testing, but real prospecting burns through 500 credits fast.

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