Inseeq develops a platform designed to generate business leads utilizing large language models like ChatGPT. The service focuses on automating lead acquisition processes for sales and marketing teams. Users can expect a streamlined method for identifying and capturing potential customer contacts.
Funding
Funding not disclosed
Founders
Product
Problem
Sales and marketing teams spend extensive time manually researching prospects, crafting generic outreach, and keeping pace with rapidly evolving AI-driven search platforms, resulting in slow lead pipelines and low conversion efficiency.
Solution
inseeq delivers an AI‑native lead generation service that automates prospect discovery, qualification, and outreach at scale. By ingesting real‑time signals from large language models (ChatGPT, Claude, Perplexity, etc.), the platform surfaces high‑intent accounts and ranks them by relevance to the client’s product. Proprietary generative pipelines produce SEO‑ and GEO‑optimized content that aligns with the brand voice, while automated monitoring dashboards keep teams informed of visibility and sentiment across AI search. The end‑to‑end workflow reduces manual research, accelerates pipeline velocity, and aligns marketing output with the algorithms that now dominate discovery.
Target Audience
Primary customers are B2B SaaS, fintech, and e‑commerce companies that need a high‑velocity, AI‑driven pipeline for lead acquisition and brand visibility in the emerging LLM search ecosystem.
Features
- Real‑time AI visibility monitoring that tracks brand mentions, citations, and sentiment across major LLM‑based search engines via a unified API.
- Generative content engine powered by ChatGPT that creates 50+ SEO‑ and GEO‑optimized articles per month, preserving brand tone through human‑in‑the‑loop editorial review.
- Generative Engine Optimization (GEO) suite that restructures site content, builds knowledge‑graph citations, and continuously tests for higher LLM ranking.
- Custom AI dashboards and automated workflow orchestration that integrate with existing CRM, marketing automation, and analytics stacks.
- Proprietary AI reasoning layer that scores and prioritizes leads based on intent signals, firmographic data, and historical conversion patterns.
- Scalable, cloud‑native infrastructure with role‑based access controls and end‑to‑end encryption for secure handling of prospect data.
- Usage‑based billing model that aligns cost with delivered work rather than hourly rates, ensuring predictable spend for growth teams.