MBA
Compare

MBA vs Klevu AI Search & Discovery

Category-leading AI on-site search and visual merchandising (now part of Athos Commerce), sold as premium $449-$649/month modules, where recommendations are behavioral widgets rather than inspectable co-purchase math.

Platforms compared:ShopifyBigCommerceMagento / Adobe CommerceMulti-platform

When MBA wins

You want inspectable co-purchase math (support/confidence/lift per rule), margin-aware ranking, real catalog bundles, and agent-callable MCP tools, on flat pricing with a free WooCommerce tier, and you treat search as a separate, already-solved layer.

When Klevu AI Search & Discovery wins

Your primary problem is on-site search relevance or polished visual merchandising for an established storefront, and you want a mature, category-leading product with a 3,000+ brand install base and deep A/B and campaign tooling.

Feature comparison

Color-striped rows favor MBA, Klevu AI Search & Discovery, or are even. We mark each so you can scan for the trade-offs that matter to you.

FeatureMBAKlevu AI Search & Discovery
On-site search
MBA does not ship a search engine. It re-ranks and adds recommendations; search is your existing engine (Shopify Search & Discovery, Magento ElasticSearch, or Klevu itself).
Best-in-class, self-learning AI search: autocomplete, NLP/semantic matching, typo tolerance, synonyms, no-results recovery. This is Klevu's core competency and reputation.
Visual merchandising UX
Configurable engines and thresholds, bulk Opportunities actions, name+SKU grids, live mining progress. Functional, but not a drag-and-drop campaign builder.
Mature drag-and-drop merchandising dashboard with campaign scheduling and A/B + multivariate testing on category pages. Deeper and more polished than MBA here.
Recommendation logic transparency
Six mining engines (sql_pairs, fp_growth default, seasonal_cohort, return_aware, hui, ai_catalog), plus a co_occurrence fallback emit explainable support, confidence, and lift per rule, with synthetic-vs-observed badging the merchandiser can inspect and override.
Behavioral engine: collaborative filtering plus clickstream signals surfaced through templates (frequently bought together, also-viewed). Confidence scores exist, but per-rule support/confidence/lift is not exposed as an audit surface.
Profit-aware ranking
The hui (High-Utility Itemset) engine ranks by margin contribution, with Opportunities tiers (Top / High-Margin / Emerging / Underperforming Attach).
Merchants can manually boost high-margin or seasonal items via merchandising rules, but there is no automatic margin-weighted recommendation ranking surfaced as an engine.
Real bundle / kit creation
Creates actual catalog bundle SKUs with pricing strategy, AI-generated copy, and a draft-to-live lifecycle plus attribution, pushed to the platform's native bundle product.
Renders recommendation impression widgets (frequently-bought-together), not merchandisable bundle products with their own SKU and pricing.
Agent-native / MCP integration
Exposes recommendations, substitutes, and basket analysis via a public REST API and a 19-tool MCP server (18 off Shopify) callable from any MCP host, plus ACP agentic-commerce endpoints.
No MCP server, ACP, or public agent-callable recommendation API found. The adjacent agentic effort in Klevu's orbit (Kleio) is a separate company.
Data residency / model choice
Mining runs locally inside Magento and WooCommerce installs; AI is bring-your-own-key direct to your provider (default claude-haiku-4-5 / gpt-4o-mini, selectable up to claude-opus-4-8 / claude-sonnet-4-6 / gpt-4.1). OroCommerce is a thin hosted client that proxies mining to the hosted backend.
Data is processed in the Klevu / Athos SaaS cloud, with no bring-your-own-LLM-key option. Standard managed-SaaS model.
B2B depth
B2B-aware mining on OroCommerce (per-organization context, cross-store insights), reorder-prediction data through the REST API, and a recommendation API for building custom B2B flows.
B2B is search-experience focused: AI search tuned for B2B catalogs, bulk/call-for-pricing display, attribute filtering. No quote-bundle or reorder-prediction surface.
Maturity, install base, references
Early-stage, pending listing on most platforms. Case studies are being assembled from beta merchants.
3,000+ brands including Puma, Yamaha, Callaway, and ColourPop; 4.9/5 on Shopify, BigCommerce Elite Partner, global support footprint and proven conversion-lift case studies.
Product feed syndication
GMC XML, Meta CSV, and TikTok CSV feeds.
1,400+ channel syndication via the Intelligent Reach capability folded into Athos. Much broader feed reach.
Pricing accessibility
Free $0 tier, Plus $99/mo flat (or ~$79/mo on annual). No GMV or revenue share, no usage metering.
Transparent on Shopify (rare for the category) but premium: $449-$649/mo per module, quote-based and $1,000-$1,600+/mo off-Shopify, with no free tier.

Pricing snapshot

MarketBasketAnalysis

Flat, transparent plan pricing: Free ($0) and Plus $99/mo flat (or ~$79/mo on annual). One paid plan, everything in it. These are product plans, not per-platform prices, and the same plans apply across every platform. Metered on capability and compute, never on GMV. No revenue share, no add-ons.

See plans

Klevu AI Search & Discovery

Module-based SaaS billed monthly, scaled by request/impression volume. Shopify App Store lists three separately-purchased modules: Recommendations $449/mo (500K impressions), Category Merchandising $549/mo (250K category views), Site Search $649/mo (50K search requests), each with a 14-day trial. Off-Shopify (BigCommerce, Adobe Commerce, Salesforce) is quote-based, with combined mid-market deployments commonly $1,000-$1,600+/mo. No free tier.

Visit Klevu AI Search & Discovery

The honest verdict

1

Klevu is not really a head-to-head competitor: it is a category-leading AI search and merchandising suite, and MBA does not ship a search engine. If your problem is search relevance or polished merchandising UX, Klevu is the stronger, more mature choice and the two products pair well.

2

Where they overlap, recommendations, MBA wins on auditability: six selectable mining engines emit support/confidence/lift per rule with synthetic-vs-observed badging, while Klevu's behavioral engine surfaces recommendations through templates without a per-rule audit surface.

3

MBA also wins on margin-aware ranking (the hui engine), real catalog bundle creation, B2B-aware mining on OroCommerce, and agent-native surfaces: a public REST API, a 19-tool MCP server (18 off Shopify) callable from any MCP host, and ACP endpoints that Klevu does not offer.

4

Klevu wins decisively on maturity, brand scale (3,000+ brands), feed syndication breadth (1,400+ channels), and merchandising polish (drag-and-drop, campaign scheduling, A/B testing). MBA is early-stage by comparison.

5

Honest recommendation: pair them. Run Klevu for search and visual merchandising; layer MBA for inspectable co-purchase math, profit-aware bundles, and agent-readiness, at a fraction of the price (free $0 tier and $99 Plus vs $449-$649+/mo modules).

Want the full buyer's deep-dive?

This page is the per-vendor short version. For the long version, read “MBA vs Bloomreach” (8 pages on the enterprise-vs-mid-market trade-off) or “MBA vs the widget cluster” (4 pages of pricing math vs Glood, Rebuy, and PickyStory).

Try MBA on your own store

14-day money-back guarantee on all paid platforms. WP.org free tier on WooCommerce. No credit card required for the free path.