Automate the 3‑week market research Excel grind with an AI agent

Executive Summary

Many mid-market companies and startups—product managers, corporate strategy teams, and small market-research shops—spend roughly three weeks per competitive or market-intelligence brief running manual web pulls, Excel joins, interviews, and slide production. This is costly and inconsistent: across an addressable pool of ~300,000 mid-market and startup buyers, intelligence workflows are often outsourced or run ad hoc, representing a potential $18.0B market if priced at about $6,000 ACV per customer. You could build a multi-step AI agent that automates source discovery, structured extraction, cleansing and synthesis, then emits design-first deliverables—editable decks, competitor matrices, and exportable Excel sheets—while surfacing provenance and confidence scores for every claim. The product would combine connector templates, a human-in-the-loop review workflow, continuous monitoring for updates, and API/Slack/Notion integrations so teams get a polished, subscriptionized stream of insight rather than raw CSVs. This market is attractive now because LLMs and agent orchestration have matured enough to manage multi-step pipelines, customers increasingly prefer design-first SaaS outputs, and buyers are shifting toward subscription intelligence rather than one-off reports. Conservatively, automating even 70% of the three-week grind for a $6,000-ACV customer creates meaningful ROI and supports the $18B TAM with clear monetization paths. To stand out you must prioritize defensible data-quality and provenance, verticalized templates, and a UX that delivers board-ready artifacts, not just data; these are practical differentiators versus general-purpose scraping tools and analytics platforms. Challenges include managing hallucinations, legal/source access constraints, and the need for upfront template and connector work, but solving those creates a repeatable subscription product that can win in a medium-competition market.