About

Eleanor Rosco

Founder and Principal Consultant at Rosco

Eleanor helps trust-sensitive businesses understand whether AI systems mention them, which competitors get recommended ahead of them, and what to fix first. Her work is built for companies that need clearer priorities, not another layer of vague reporting.

Why Rosco exists

A more practical approach to AI search

Eleanor started Rosco after seeing that many search-dependent businesses were stuck between expensive, vague services and oversized software that generated more reporting than real decisions.

She kept seeing the same problem: firms did not know whether AI systems were mentioning them, who was getting chosen ahead of them, or which pages and third-party signals were shaping those answers.

Rosco is built to close that gap with practical analysis, clear priorities, and implementation help that turns findings into steady improvement.

Who she helps

Built for businesses where trust and recommendation matter

Eleanor works especially well with firms that need to be understood and trusted before a buyer ever reaches out. That includes insurance agencies, brokerages, advisors, dental practices, and specialty clinics.

These are often businesses that know AI search is starting to matter, but do not want bloated tooling, jargon-heavy reporting, or a vague retainer that never turns into clear priorities.

Her approach is plainspoken and evidence-first: find out whether the business is in the answer set, see who is getting picked ahead of it, and focus on the next improvements that will actually matter.

Point of view

What Eleanor believes

Most businesses do not need another giant dashboard first. They need clearer priorities and follow-through.

AI search tends to reward businesses that are easier to understand and easier to trust.

If your business is hard for AI systems to understand, you can lose consideration before a buyer reaches your site.

This is usually an incremental process, not a one-time fix.

The right next fix matters more than a longer list of recommendations.

“The work is usually less about gaming a system and more about making it easier for AI systems to understand why your business should be recommended.”

How Rosco works

Analysis first, then practical follow-through

Rosco is not designed to be a giant feature suite, and it is not positioned as a magic automation engine. The goal is to help businesses understand what AI systems are actually saying about them and what to do next.

That usually means a mix of reporting, source analysis, practical recommendations, and implementation help. Some parts of the process are AI-assisted, but the standard stays the same: the work should be honest, useful, and grounded in evidence.

Rosco is built for steady improvement, not vanity reporting.