GEO Intelligence Platform

AI search is no longer experimental. It is now the front door to discovery.

Google AI Overviews appear above organic listings on a majority of high-intent searches. ChatGPT, Gemini, Claude, and Perplexity are influencing customer decisions before users ever reach your website. The brands winning visibility are no longer just optimizing for rankings. They are optimizing for citation, entity understanding, and AI discoverability.

This month’s releases move GEO Intelligence and Content Studio further in that direction: from monitoring AI visibility to actively helping teams govern, improve, and scale it. 

Google AI Overviews Tracking

A hospitality brand recently asked us a simple question:

"We can see our rankings. But can we see whether AI is recommending us?"

Until now, most teams couldn’t.

That gap matters because Google AI Overviews are becoming one of the highest-volume AI discovery surfaces on the internet. The customer gets an answer before they ever see your website, your ad, or your OTA listing.

If your brand is missing from that answer, you lose visibility before the click even happens.

What’s New

GEO Intelligence now tracks brand presence inside Google AI Overviews alongside ChatGPT, Gemini, Claude, and Perplexity.

Your team can now:

• Monitor branded and unbranded prompts
• See when your brand is cited
• Identify when OTAs or competitors appear instead
• Understand visibility gaps across AI platforms from one place

This is a major step toward unified AI visibility monitoring across the entire discovery ecosystem.

What’s Next

This release lays the groundwork for a much broader AI discovery layer arriving across Q2 and Q3, including:

• Unified GEO Visibility Overview
• OTA Mention Tracking
• Competitive Share of Voice by destination
• Prompt Volume integration to prioritize high-demand queries

The goal is simple: help brands understand not just whether they appear in AI search, but where visibility is being lost and why.

Why It Matters

Brands cited in AI-generated answers are already seeing materially higher engagement rates than brands left out of the conversation.

AI search is changing how discovery works. Rankings still matter. But citations are becoming the new visibility layer.

Now you can measure them directly. 

AI Model Upgrades for Prompt Recommendations

One of the biggest misconceptions in AI search today is that recommendations stay useful forever.

They don’t.

AI platforms evolve constantly. A recommendation engine trained on older model behavior quickly becomes stale, causing teams to optimize for signals that no longer influence visibility.

What’s New

Prompt Recommendations and GEO optimization guidance now run on the latest available AI models.

That means:

• fresher optimization insights
• recommendations aligned to current AI behavior
• better prioritization for content and schema teams
• less time spent chasing outdated gaps

Your recommendations now reflect how AI systems interpret brands today, not six months ago.

What’s Next

In Q3, Prompt Optimization introduces continuous evaluation and improvement workflows so recommendations evolve over time instead of remaining static.

That intelligence layer will eventually connect directly into:

• GEO Prompt Recommendations in Content Studio
• Centralized Entity Management
• automated optimization workflows across content and schema

The long-term vision is not just AI monitoring.

It’s AI systems actively helping teams improve discoverability continuously.

Why It Matters

The teams succeeding in AI search are not necessarily publishing more content.

They are acting on better signal.

Better models create better recommendations. Better recommendations create better prioritization. Better prioritization creates better visibility outcomes.

That compounding loop matters.

Profile Selection Improvements

Sometimes the biggest operational problems are the least visible.

For enterprise teams managing hundreds of locations, a single incorrect property selection can cascade into:

• incorrect reporting
• wrong optimization decisions
• duplicate work
• hours of avoidable cleanup

At scale, this wasn’t occasional friction. It was workflow debt.

What’s New

Profile selection now prioritizes full address and location-level details instead of relying primarily on URLs.

Teams can distinguish similar properties faster and select the correct profile confidently on the first try.

It sounds small.

But for multi-location businesses managing GEO across hundreds of properties, this removes friction from nearly every workflow inside the platform.

What’s Next

This release is foundational for Multi-Profile Prompt Management arriving in Q2.

That capability will allow enterprise teams to manage GEO monitoring and prompt workflows centrally across brands and properties from a single interface.

Reliable profile identification is what makes that possible.

Why It Matters

The most valuable workflow improvements are often the ones teams stop noticing because the friction disappears entirely.

Less rework.

Less confusion.

Faster execution.

More time focused on improving visibility instead of managing operations. 

Improved Citation Handling for Outdated AI Sources

AI engines do not cite the web as it exists today.

They cite the web as it existed when the model or index last processed it.

That distinction creates confusion constantly.

Teams would click a citation, see a changed or expired page, and assume the data inside GEO Intelligence was incorrect.

In reality, the AI model was referencing an earlier indexed version.

What’s New

GEO Intelligence now surfaces clear messaging whenever a cited source may reflect an earlier indexed state rather than the current live page.

Your team immediately understands:

• why the citation looks different
• whether the source has changed
• what the AI model likely referenced

No more second-guessing the platform data.

What’s Next

This becomes the foundation for Citation Management arriving in Q2, including:

• citation quality scoring
• governance workflows
• AI citation fix recommendations

Q3 then expands into Performance Attribution, connecting visibility improvements directly back to content and schema changes.

Why It Matters

AI visibility management requires trust in the underlying data.

The faster teams can distinguish real visibility problems from outdated source states, the faster they can focus on fixes that actually improve discoverability. 

Content Studio

Enhanced User Experience in Content Studio

The brands winning in AI search are not just creating better content.

They are moving faster from idea to execution.

As AI-generated discovery expands, content velocity and structured publishing are becoming competitive advantages, especially for multi-location businesses managing dozens or hundreds of properties.

What’s New

Content Studio now includes a redesigned creation experience built for faster workflows and better content management.

Teams can now:

• discover content opportunities faster through the Content Intelligence Hub
• organize broader initiatives through My Projects
• locate existing content instantly with improved filters in My Content

The editor itself has been significantly upgraded:

• real-time article streaming
• inline markdown rendering
• insertable FAQs, CTAs, and inbound links
• AI Chat directly inside the editor for rewrites, tables, summaries, and refinements

Your team no longer has to jump between workflows to finish content.

What’s Next

This redesign becomes the foundation for several major Q2 and Q3 launches:

• Knowledge Vault
• On-Brand Content Standards
• Moderation Workflow with role-based approvals
• Social Publishing
• Content Decay Detection
• GEO Prompt Recommendations

The direction is clear: fewer disconnected tools and more intelligent, AI-assisted content workflows.

Why It Matters

The brands capturing AI visibility are publishing:

• more structured content
• more frequently
• across more surfaces

This release removes operational friction between idea and publish-ready output so teams can scale content production without scaling complexity.

Dynamic Content Templates

One of the clearest patterns emerging in AI search is that structure matters.

AI systems consistently favor content that is:

• semantically organized
• contextually rich
• consistent across pages

For enterprise brands managing hundreds of locations, achieving that consistency manually is nearly impossible.

What’s New

Content Studio now supports Dynamic Content Templates.

Teams can create reusable templates for:

• location pages
• homepage sections
• dining pages
• offer pages
• campaign landing pages
• and more

Each section includes:

• customizable prompts
• character guidance
• drag-and-drop ordering
• editable structure controls

During generation, teams simply:

• Select the brand
• Enter the website URL
• Add target keywords
• Map templates to pages
• Generate structured content at scale

The structure is defined before generation begins, which dramatically improves consistency and output quality.

What’s Next

Q3 introduces Verticalized AI Recommendations tailored to industry-specific workflows and business intent.

Q4 expands into Template Guardrails, embedding governance and brand standards directly into the generation process.

Longer term, the platform moves toward an agentic experience where AI selects the right template and builds the content workflow autonomously from a single prompt.

Why It Matters

The future of enterprise content creation is not manual scaling.

It is structured scaling.

Define the framework once.

Apply it everywhere.

Improve consistency, velocity, and AI discoverability simultaneously.

That is the direction modern content operations are moving toward, and this release is an important step there.