Onsite search is no longer a feature. It’s where revenue is won or lost. Shoppers who use search convert at two to four times the rate of shoppers who browse, and the gap is widening as AI raises the bar for what a “good result” feels like. If a query returns ten near-misses, the shopper doesn’t refine. They leave.
The category has also shifted underneath everyone in the last 18 months. Vector and semantic search went from cutting-edge to expected. Agentic AI moved from buzzword to feature roadmap. And a wave of consolidation, including the Searchspring and Klevu merger that formed Athos Commerce, has reshuffled who competes with whom.
This guide is for ecommerce leaders, merchandisers, and digital strategists trying to make a real decision in 2026. We’ve compared seven of the strongest platforms, what each one is genuinely good at, and where each one struggles, so you can match the tool to your situation rather than the loudest pitch.
What to look for in an ecommerce search and discovery platform
Before the list, a few things worth weighing as you evaluate any vendor:
Search intelligence beyond keywords. Hybrid search that combines lexical matching with vector and semantic understanding is now table stakes. Ask vendors specifically how they handle vague, subjective, or natural-language queries.
Merchandiser control without engineering tickets. Your team should be able to boost, pin, demote, and bundle products through a UI, run A/B tests, and schedule campaigns without filing a dev request. If every change requires code, the platform will slow you down.
Personalization depth. Does the platform personalize search results, category pages, recommendations, and content from the same shopper profile? Or do you need to stitch together three vendors to get coherence?
Platform fit. Shopify Plus, Salesforce Commerce Cloud, Adobe Commerce, BigCommerce, and Shopware all have different integration realities. A platform that’s native to your stack will deliver value faster than one that requires custom plumbing.
Total cost of ownership. List price is one input. The other is implementation time, ongoing maintenance, and whether you’ll need an agency to run it. Some platforms look cheap until you add the services bill.
Agentic AI roadmap. Most vendors are now shipping or promising AI agents that automate merchandising decisions, surface revenue opportunities, and answer strategic questions. Check what’s actually live versus what’s on a slide.
1. Algolia
Algolia is the developer-first search platform with the largest installed base, orchestrating over 1.75 trillion queries each year and trusted by more than 18,000 businesses. It’s built around speed, transparent APIs, and clean documentation, which makes it a favorite of engineering teams who want to compose their own discovery experience.
The recent Commerce Pipeline release strengthened Algolia’s Shopify integration with a new indexing foundation that dramatically improves speed and reliability, as well as enhanced analytics, campaign-driven merchandising, structured category support, and richer content discovery. Algolia also offers a free tier, which lowers the barrier to evaluation.
Best for: Engineering-led teams, large catalogs that need sub-millisecond response times, and brands that prefer to compose their own stack via APIs.
Watch out for: Merchandiser tooling is less mature than the engineering experience. Teams without dedicated developers can find the platform powerful but underutilized.
2. Bloomreach Discovery
Bloomreach sits at the enterprise end of the market, combining search, content management, and AI-driven personalization into a single digital experience platform. Its Loomi AI engine powers search, recommendations, and marketing automation from one place, which appeals to large retailers that want consolidation across discovery and lifecycle.
The trade-off is weight. Implementation is heavier than mid-market platforms, and the full DXP value only shows up when you adopt multiple modules. For brands that have outgrown point solutions and want one vendor running discovery, content, and CDP-style personalization, Bloomreach is one of the few credible options.
Best for: Large enterprises with dedicated discovery teams, complex multi-region catalogs, and the appetite for a platform-level commitment.
Watch out for: Long implementation cycles and a pricing model that scales quickly with catalog size and query volume.
3. Nosto
Nosto is the agentic Commerce Experience Platform built for retail brands that want search, merchandising, recommendations, and personalization running off a single intelligence engine rather than four stitched-together vendors. Its Personalized Search uses hybrid and vector technology to interpret intent, and its Category Merchandising automates KPI-driven sorting so merchandisers stop hand-curating thousands of pages.
What sets Nosto apart in 2026 is Huginn, the always-on AI commerce agent that orchestrates a network of purpose-built agents across search, merchandising, A/B testing, and personalization. Instead of buying separate tools and hoping they share data, Nosto’s experience.AI engine connects customer, product, and content data in real time, which is what makes the agentic layer actually useful. The platform supports more than 1,500 brands across 100+ countries, including Marc Jacobs, Kylie Cosmetics, MUJI, O’Neill, and FIGS, with seamless integrations into Shopify, Shopify Plus, Salesforce Commerce Cloud, Adobe Commerce, Shopware, Hyvä, and BigCommerce.
Best for: Mid-market and lower-enterprise retail brands on Shopify Plus and adjacent platforms that want unified search, merchandising, and personalization without managing multiple vendors.
Watch out for: Brands that only need a bare-bones search bar and nothing else may find the platform broader than their use case requires.
4. Constructor
Constructor has carved out a specific position: revenue-optimized search that ranks products by likelihood to convert rather than keyword relevance alone. It uses clickstream and behavioral data to power ranking, product boosting, and personalization, and the company is unusually transparent about A/B test results and documented revenue lifts.
The platform is particularly strong for high-SKU catalogs and enterprise B2B and B2C retailers that want sophisticated AI search with detailed merchandiser controls. Onboarding can be intensive, which means smaller teams without dedicated discovery resources may struggle to get the full benefit.
Best for: Enterprise retailers with large catalogs, in-house merchandising teams, and a culture of measuring everything against revenue.
Watch out for: Implementation complexity and a price point that reflects the enterprise positioning.
5. Athos Commerce (formerly Searchspring and Klevu)
In January 2025, Searchspring and Klevu merged under PSG Equity to form Athos Commerce, with Intelligent Reach later joining to add omnichannel feed management. The combined platform brings together Searchspring’s merchandising depth, Klevu’s AI search, and feed syndication into one suite.
For now, Searchspring and Klevu still operate as named products under the Athos umbrella while the unified next-generation platform rolls out. Searchspring remains strong for marketing and merchandising teams that want granular curation control. Klevu remains a sensible Shopify-native option with semantic NLP across 30+ languages.
Best for: Mid-market retailers that want strong merchandiser tooling and a clear Shopify or Magento integration path.
Watch out for: The unified Athos platform is mid-transition through 2026. Existing customers should ask about migration timelines, and new buyers should clarify which product they’re actually buying.
6. Coveo
Coveo is an enterprise search platform with deep machine learning roots, originally built for knowledge and support use cases before expanding into commerce. It uses ML ranking, behavioral signals, and 30+ pre-built connectors to deliver personalized search across complex environments.
Coveo tends to fit best at organizations that have search needs beyond ecommerce, such as B2B portals, service sites, or knowledge bases, where one unified search layer across multiple touchpoints is more valuable than a pure commerce specialist.
Best for: Enterprise organizations with multiple search use cases, B2B commerce with complex content alongside products, and teams that value ML transparency.
Watch out for: Implementation requires meaningful technical investment, and the commerce-specific merchandising experience isn’t as polished as platforms built purely for retail.
7. Lucidworks
Lucidworks Fusion, built on top of Apache Solr, is the platform of choice for very large retailers and B2B distributors that need search to run at extreme scale with deep customization. It’s powerful, flexible, and used in mission-critical environments across grocery, automotive parts, and industrial distribution.
The trade-off is operational lift. Lucidworks works best for organizations with existing DevOps and search engineering expertise, plus a clear process for relevance tuning. Teams without those resources can struggle to extract the platform’s full value.
Best for: Very large enterprises with internal search engineering teams, B2B catalogs with millions of SKUs, and use cases that demand heavy customization.
Watch out for: Total cost of ownership including engineering time, and a steeper learning curve for merchandiser teams compared to commerce-native platforms.
How to choose the right platform for your business
A few honest patterns we see when retailers make this choice well:
Start with the job you’re hiring the platform to do. “Better search” is too vague. “Increase revenue per session on our top 50 category pages” is a job. “Reduce zero-result searches by 80%” is a job. Specific jobs make vendor comparisons easier.
Weight implementation reality, not just features. A platform that takes nine months to launch can lose to a platform that’s live in six weeks, even if the nine-month tool has a slightly better feature checklist. Time to first revenue impact matters.
Talk to current customers in your size range and vertical. Vendor case studies will always show winners. Reference calls with similar brands will tell you what the day-to-day actually feels like, how responsive support is, and what the merchandiser experience is really like at 2pm on a Tuesday.
Check the agentic AI roadmap critically. Almost every vendor is now using the word “agentic.” The question to ask is: which decisions does the agent actually make autonomously today, what data does it act on, and what control do my merchandisers retain? Platforms like Nosto with Huginn have shipped concrete agentic capabilities, while others are still in roadmap territory.
Don’t underestimate platform fit. If you’re on Shopify Plus, the platforms with the deepest native Shopify integrations will move faster than those treating Shopify as one more endpoint. The same logic applies to Salesforce Commerce Cloud, Adobe Commerce, and Shopware.
The right ecommerce search and discovery platform isn’t the one with the longest feature list. It’s the one your team will actually use, that fits your catalog, your stack, and your growth stage. Whichever direction you go, the brands winning in 2026 are the ones treating search as a revenue channel, not a utility.
