Infodrops automates deep-dive research with an agentic pipeline: iterative search, relevance scoring, extraction, follow-ups, recursive exploration, and report export.
Deep research is slow because the hard part is not one search. It is deciding what is relevant, extracting what matters, finding gaps, and following those gaps until the answer is complete.
Infodrops needed to behave like a patient analyst: explore, score, extract, follow up, and return a useful brief instead of a pile of links.
We built the web app, job orchestration, billing, research pipeline, report export, and real-time progress feed.
| Before | After Ego Eimi | |
|---|---|---|
| Deep-dive research | About five hours per query | About ten minutes, a −95% drop |
| Source coverage | Manual searching, a pile of links | 30+ vetted sources scored per query |
| Crawling cost | Repeated work on the same pages | 67% less duplicate crawling through caching |
| Traction | A new product with no users | 120 paying teams in three months |
The platform handles the business layer around the AI: authenticated job management, admin oversight, subscriptions, caching, exports, deployments, and tests.
67% less duplicate crawling through cachingI started this company not knowing what would happen; less than a month with Ego Eimi and I already had a working product. Amazing!
A code-audit SaaS surfacing prioritized security, quality, and maintainability findings.
An automation platform for repetitive but complex work with agents, memory, and integrations.
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