Two Types of Information Services Providers

In practice, information services providers generally fall into two groups.

First, there are commercial providers. These organizations sell premium information via subscriptions or similar models. Their audiences are typically professionals — analysts, researchers, lawyers, policy experts — who rely on fast, precise access to trusted content as part of their daily work.

Second, there are public or governmental organizations that are obligated to publish and provide access to authoritative information. For these groups, search underpins transparency, accessibility, and trust.

Different missions. Same reality.

If users can’t find what they need, the value of the information itself drops sharply.

Why So Many Organizations Built Custom Search

To meet these expectations, many information services providers built their own search solutions using open-source technologies like Elasticsearch, Solr, or OpenSearch.

That decision usually made sense at the time.

These platforms offer:

• A high degree of customizability
• Fine-grained control over relevance and ranking
• Flexibility to model complex content and metadata

For organizations with specialized content and demanding users, off-the-shelf search products simply didn’t cut it. Custom search was often the only viable option.

When Customization Becomes a Problem

Over time, though, these custom implementations tend to grow organically.

New features get added. Edge cases accumulate. Different teams contribute code across years. Search logic becomes tightly coupled to ingestion pipelines and applications.

The result is something we see over and over again:

• Search is powerful
• Search is mission-critical
• Search is hard to change safely

Many teams reach a point where even small enhancements feel risky. And that’s before you add AI into the mix.

The New Pressure: AI-Driven Search

Today, information services providers are under pressure to introduce capabilities like:

• Vector and hybrid search
• Semantic discovery beyond keywords
• GenAI-powered question answering and summaries

These aren’t “nice to have” features anymore. Users increasingly expect them.

The problem is that most legacy search architectures were never designed with these capabilities in mind. Bolting AI onto already complex systems often increases operational risk and long-term maintenance cost — exactly what teams are trying to avoid.

So organizations get stuck.

They can’t rip and replace search.

They can’t stand still.

Modernizing Search Without Starting Over

This is where modernization – done carefully – matters.

Our approach focuses on building on the work information services providers have already done, not throwing it away.

By introducing Pureinsights Discovery as a unifying platform, we help organizations:

• Simplify and stabilize existing search implementations
• Reduce custom code and operational complexity
• Preserve domain-specific relevance logic
• Create a clean foundation for vector, hybrid, and GenAI-powered search

The goal isn’t to add another layer of complexity. It’s to make search easier to evolve, safer to operate, and ready for what comes next.

A Real-World Example: EMARKETER

A good example of this approach is our work with EMARKETER, a leading provider of market and consumer insights.

For EMARKETER, search is central to how subscribers discover analyst research, forecasts, and insights. Their search implementation had evolved over time and needed to support new AI-driven discovery use cases — without compromising reliability or relevance.

By modernizing their search using Discovery, EMARKETER was able to:

• Introduce vector and hybrid search capabilities
• Lay the groundwork for AI-powered discovery
• Improve maintainability while preserving existing relevance logic
• Confidently evolve their search experience going forward

If you want to go deeper, you can explore:

• A short demo of EMARKETER’s AI Search: EMARKETER AI Search Demo
• The full customer story: EMARKETER Launches AI Search – Pureinsights Customer Story – Pureinsights
• A conversation with EMARKETER’s VP of AI: How AI Search Transforms Business: EMARKETER’s Journey with Pureinsights

Search Is Mission-Critical — But Not Everyone’s Core Business

One thing we hear often from information services providers is:

“Search isn’t our business.”

And that’s fair.

Search needs to be reliable, performant, and continuously improving — but most organizations don’t want to dedicate large teams to keeping it running and up to date. That’s why we also support customers through our Managed Services offering.

Managed Services allow teams to:

• Reduce operational risk
• Stay current as search and AI technologies evolve
• Focus internal effort on content, users, and outcomes

Final Thoughts

Information services providers have unique requirements. They need precision, flexibility, and trust. Fully bespoke search systems have become hard to maintain, while off-the-shelf products often don’t fit.

Our experience working with many information services providers – including EMARKETER – shows there’s a better path. One that respects existing investments, modernizes what matters, and creates a sustainable foundation for AI-driven discovery.

When search is critical to the product, getting this right isn’t optional.

If you’re thinking about how to modernize mission-critical search – and prepare it for AI – we’d be happy to share what we’ve learned.

• Kamran Khan

CEO, Pureinsights

Additional Resources

• Smarter Search and Chatbots Demo
• Understanding AI Agents and Agentic AI — Without the Hype – Pureinsights
• Why 95% of GenAI Projects Fail – And How to Beat the Odds – Pureinsights
• Outsell Inc. research and advisory firm to the information services industry