From native search to AI-powered discovery
Search has quietly become one of the most important parts of any website experience. When it works well, users find what they need instantly. When it doesn’t, they leave.
For organisations using SilverStripe CMS, the good news is there are a range of powerful search options available, from simple built-in functionality to advanced AI-driven search solutions.
Here’s a look at the top approaches we’re seeing across New Zealand and beyond.
1. SilverStripe Native Search
Best for: small to medium websites with simple needs
SilverStripe includes a native search capability out of the box. It’s quick to implement and works well for basic keyword matching across page content.
Pros:
- Fast to set up
- No external infrastructure required
- Low cost
Cons:
- Limited relevance tuning
- Not suited for large or complex content sets
For smaller websites, native search can be enough. But as content grows, most organisations start to feel its limitations.
2. Apache Solr
Best for: enterprise-grade search with structured content
Apache Solr has long been a go-to search engine for enterprise SilverStripe builds. It offers powerful indexing, faceting, and filtering capabilities.
Pros:
- Highly configurable
- Strong performance at scale
- Advanced filtering and faceted search
Cons:
- Requires infrastructure and maintenance
- More complex to implement
- Less flexible for modern AI-driven experiences
Solr is still a solid choice, particularly for government and large content-heavy platforms, but it’s increasingly being challenged by newer approaches.
3. Elasticsearch
Best for: scalable, flexible, modern search experiences
Elasticsearch is one of the most popular search engines in the world and integrates well with SilverStripe.
Pros:
- Excellent scalability
- Real-time indexing
- Strong ecosystem and tooling
- Supports relevance tuning and analytics
Cons:
- Can become costly at scale
Elasticsearch strikes a balance between power and flexibility, making it a strong default choice for many modern builds.
4. AI-Powered Search Solutions
Best for: personalised, intent-driven discovery
This is where things get interesting. AI search solutions are rapidly changing how users interact with content.
Rather than relying purely on keywords, AI search understands intent, context and behaviour.
Technologies like:
- Vector search
- Semantic search
- Natural language queries
can be layered on top of platforms like Elasticsearch or used via external services.
Examples include:
- Azure Cognitive Search
- Algolia
- Custom AI layers using embeddings and large language models
Pros:
- Handles natural language queries
- Improves relevance dramatically
- Enables personalisation and recommendations
Cons:
- Higher implementation complexity
- Requires careful tuning and governance
- Cost considerations
For organisations focused on user experience, AI search is quickly becoming the new standard.
5. Hybrid Approaches (The New Best Practice)
Best for: future-proof, high-performing platforms
Increasingly, we’re seeing hybrid search architectures emerge.
This might look like:
- Elasticsearch for indexing and speed
- AI models for semantic understanding
- Behavioural data to refine results over time
This approach allows organisations to combine the reliability of traditional search with the intelligence of AI.
Choosing the Right Approach
The right solution depends on a few key factors:
- Content volume and complexity
- Performance requirements
- Budget and infrastructure
- User expectations
A simple content site might thrive with native search, while a large-scale platform with diverse audiences will benefit from an AI-powered or hybrid solution.
Where Toast Fits In
At Toast, we design and build SilverStripe platforms with search as a core experience, not an afterthought.
From implementing robust Elasticsearch solutions to layering in AI-driven search and personalisation, we help organisations turn search into a powerful tool for engagement, discovery, and conversion on your platform.
