There is a lot of noise around AI right now. Most organizations are trying to figure out where it actually fits and what is worth investing in, especially across large, content-rich systems.

We work with universities, government agencies, and other public-serving organizations to apply AI in ways that are practical and grounded. In most cases, that means improving how people find information, helping teams manage large amounts of content, and making existing systems more useful.

We are not an AI-first agency. We focus on content systems and search, and apply AI where it meaningfully improves those systems. The goal is not to introduce something new for its own sake, but to make what you already have work better.

Where AI Fits

In most environments, AI is not a standalone product. It is something that enhances existing systems.

We see the most impact in a few areas:

• Search experiences that return more relevant results and clearer summaries
• Content organization and tagging across large, complex sites
• Assistive tools that help teams create and maintain content
• Interfaces that allow users to find answers without navigating multiple sections

The focus is on reducing friction for both users and internal teams, not replacing the systems you already rely on.

AI and Search

Search is often the most immediate opportunity.

Many organizations already have large amounts of content, but users struggle to find what they need. AI can improve this by refining how results are ranked, generating contextual summaries, and making it easier to understand what a page or document contains before clicking through.

For example, we have worked on search implementations where AI-driven summaries help users find relevant information across thousands of pages and documents, reducing the need to navigate multiple sections of a site.

We have experience with platforms like Algolia, ElasticSearch, and Solr, and can layer AI-driven capabilities on top of those systems to improve how search performs in practice. This is often one of the fastest ways to create meaningful improvement without a full redesign.

Generative Engine Optimization (GEO)

Search is shifting. People are not just clicking through lists of links. They are asking questions and getting direct answers from systems like ChatGPT, Google, and other AI-driven interfaces.

This has introduced a new layer often referred to as Generative Engine Optimization. It is less about ranking a page and more about making sure your content can be understood, trusted, and surfaced by these systems.

In practice, this comes back to fundamentals. Clear structure, well-organized content, and direct answers to real questions all make it easier for AI systems to interpret and reference your content. The same work that improves search also improves how your organization shows up in these newer interfaces.

We approach this as an extension of content strategy and information architecture. Rather than optimizing for a single platform, the goal is to make your content usable across both traditional search and AI-driven experiences.

AI for Content Systems

Large, content-rich websites tend to accumulate complexity over time. Content is duplicated, inconsistently structured, or difficult to maintain.

AI can help support this by assisting with tagging, identifying patterns across content, and helping teams maintain consistency. It can also support workflows where content needs to be updated, translated, or reused across multiple channels.

In this context, AI typically refers to systems that can interpret content, generate summaries, and assist with organizing and retrieving information. We approach this carefully. The goal is to support editorial teams, not replace them, and to ensure that any automation aligns with how content is actually managed.

Integration with Existing Platforms

AI is most effective when it is connected to your existing systems.

We work within Drupal and WordPress environments, integrating AI capabilities into the CMS, search layer, or connected services. This might include APIs, third-party tools, or custom implementations depending on the needs of the project.

The focus is on making these capabilities feel like part of the platform, not something separate that requires additional overhead.

Accessibility and AI

AI can play a role in improving accessibility, but it needs to be applied carefully.

It can assist with identifying issues, improving content clarity, and supporting alternative formats. At the same time, it does not replace the need for thoughtful design and manual testing.

As an accessibility-first agency, we approach AI as a tool that can support accessibility efforts, not substitute for them.

A Practical Approach

Most organizations do not need a full AI strategy from day one. They need a clear place to start.

We typically begin by identifying a small number of high-impact use cases and building from there. That might be improving search, supporting content workflows, or integrating AI into a specific part of the user experience.

From there, we expand based on what is working and what is actually providing value.

Frequently Asked Questions

Where should we start with AI?
Search and content workflows are often the most practical starting points. They tend to deliver clear improvements without requiring major changes to existing systems.

Do we need to replace our current CMS?
No. AI can usually be integrated into existing platforms like Drupal and WordPress.

How do you approach accuracy and reliability?
We focus on use cases where results can be validated and where AI supports, rather than replaces, human decision-making.

Is AI appropriate for government and higher education?
Yes, but it needs to be implemented carefully, with attention to accessibility, privacy, and accuracy.