Release Summary 26.07 | Apr 06, 2026
The following key features and improvements, along with bug fixes, have been released in Algonomy DXP products in the release version 26.07.
Discover
Discover 2.0 Early Access
We are excited to announce the Early Access release of Discover 2.0, our next generation Browse API that unifies your search and category navigation onto the modern Find platform. This major upgrade leverages streaming catalog ingestion to provide near real-time updates and full-catalog coverage, eliminating the delays and product restrictions of our legacy system. Merchandising and B2B teams can now deliver richer shopper experiences out of the box with native support for dynamic faceting, custom filtering, sorting, and customer-aware visibility rules. Because the new Browse API shares the exact same request and response architecture as the Find Search API, development teams can seamlessly update their endpoints and begin side-by-side testing today.
Recommend
Streaming MCMP Attribute Support in Advanced Merchandising
Support has been added to enable the streaming compatibility attribute compatibility$mcmp_algo_compatibility to work with the Advanced Merchandising compatibility feature. This allows compatibility attributes generated through the AI compatibility process to be used seamlessly in merchandising rules.
When selecting Compatibility as a criteria in an Advanced Merchandising rule, the attribute is displayed as ‘algo_compatibility’. Selecting this attribute applies the associated list of compatible product IDs from the attribute value, enabling streamlined setup of compatibility-based rules for Streaming Catalog clients.
Jira: ENG-31964
Engage
Engage Campaign List: Filter for Active and Expired Campaigns
The Engage campaigns page has been enhanced with a filter to make it easier to manage active campaigns. By default, the page now displays only campaigns that have no end date or whose end date has not yet passed, helping users focus on currently active rules.
A checkbox labeled “Show expired” has been added at the top of the page. The checkbox is unchecked by default. When selected, it displays all campaigns, including those with end dates in the past, allowing users to review expired campaigns when needed.
Jira: ENG-31930
Ensemble AI
Display Ensemble Scores in Dashboard
Ensemble scores are now displayed within the Dashboard to provide better transparency into ranking decisions. Users can view both the overall ensemble score and the relevance score returned by the API, helping them understand why ensembles are ordered in a specific way.
Scores are shown when viewing ensembles within a style and across styles. By default, the values are displayed with two decimal precision and include the Ensemble score (API label: score) and Relevance score (API label: llmscore).
Jira: ENG-32040
Dashboard Chatbot
Pass Page Context for Improved Responses
The dashboard chatbot has been enhanced to receive the user’s current page context when handling queries. This improves its ability to answer page-specific questions, such as metric or field definitions related to the page the user is viewing.
The user’s current page context is now passed to the chatbot API using the CSH Id value. This helps the LLM focus on the relevant documentation page and provide more accurate, context-aware responses.
Jira: ENG-31904
Other Feature Enhancements
The following feature enhancements and upgrades have been made in the release version 26.07.
|
Jira # |
Module/Title |
Summary |
General Availability |
|---|---|---|---|
|
Recommend: CategoryCP2 Model in Configurable Strategies |
The CategoryCP2 (Categories Bought Together) model, based on category co-purchase data, is now available in Configurable Strategies and has been added to the new page under the “Other” model type group. This enables more relevant category recommendations and provides greater control over configuration, including the ability to specify the category tier. The model supports Category Affinity, Category Context, and Fixed Category Seed as personalization seed options, along with User Affinity, Smart Shuffle, and Margin for sorting. No additional filters are required. Users can enable category recommendations within the strategy and optionally include the seed product in the results. |
06-Apr-26 |
|
|
Recommend: Use Primary Category as Seed for Category-Based Strategies |
Category-based strategies now use the product’s primary category as the seed when a product seed is provided. This ensures that CategoryTopSellers and related CategoryBestSeller strategies return results that are contextually relevant to the shopper. This logic also applies to Configurable Strategies that use Category Context as the seed. If a product does not have a primary category defined, the platform continues to follow the existing category selection logic. |
06-Apr-26 |
|
|
Recommend: Product List Model Support in Configurable Strategies |
Support has been added for the Product List model (recsUsingCustomInput) in Configurable Strategies and on the new Configurable Strategies page under the “Other” model type group. This enables users to define a fixed list of products for manual recommendations, sort them by affinity, and apply brand or category diversity rules. The enhancement also supports future use in Offer Personalization. Users can select Product Context or Fixed Product List as seed options. The Fixed Product List supports an unlimited number of products and allows multiple product IDs to be entered at once using a comma-separated format. Sorting options include User Affinity, Smart Shuffle, and Margin. Additional options allow users to diversify by category or brand, enable category recommendations, and include the seed product in the results. |
06-Apr-26 |
|
|
New Templates Added to Dynamic Experience UI |
Two new templates have been added to the New Dynamic Experience UI: Subscription Footer Bar and Subscription Lightbox. These templates enable users to quickly configure subscription-based experiences in commonly used layout formats. |
06-Apr-26 |
|
|
Find: Find Mesos Job Status Report Enhancement |
The Find Mesos Job Status Report layout has been updated to improve visibility and clarity. The “JOBS NOT RUN” section is now displayed at the top of the report for quicker identification of issues. In addition, the report now shows only the latest failed job ID for each failed job, reducing noise and making it easier to track the most recent failure. The enhancement is working as expected. |
06-Apr-26 |
|
|
Enterprise Dashboard: New Configurable Strategies Page Enhancements and Fixes |
Several updates have been made to improve consistency on the new Configurable Strategies page. The “Advanced Filters” label has been renamed to “Advanced Settings.” The Strategy Preview payload has been aligned with the legacy page, including adding the missing regionExtId, correcting the seed format to a string, and ensuring parameters match the old implementation. For Category or Brand Affinity with Best Seller models, the preview now correctly uses seedStrategy: "FIRST_VALID" unless “Use Multiple Items” is selected. Additional UI fixes include correcting price labels in the View Results tab, updating the archive icon tooltip to “Archive,” and disabling the “User Wishlist” model when Wishlists are not enabled in Site Config, with a tooltip explaining the restriction. |
06-Apr-26 |
|
|
Chatbot: Chatbot Voice Mode Implementation |
Voice mode has been implemented in the chatbot to allow users to ask questions and hear responses without typing or reading text. Users can enable or disable voice mode, after which the interaction runs hands-free. The solution leverages the new voice technology provided by the Science team, enabling automatic detection of when a user has finished speaking and seamless transmission of input to the chatbot. The implementation was completed in collaboration with the Science team and supports smooth entry into and exit from voice mode. |
06-Apr-26 |
|
|
Find: SFI: Batching for Category-Based Product Updates |
The Streaming Find Indexer (SFI) experienced an Out of Memory (OOM) error during large category updates, where the category fan-out process attempted to update a very large number of associated products in Solr at once. This led to consumer interruption, increased Kafka lag, and stale search data until recovery. To address this, batching has been implemented in the category product update flow to limit memory usage during large updates. The solution bounds processing volume and improves stability during high-cardinality category events. The enhancement is working as expected. |
06-Apr-26 |
|
|
Dashboard Chatbot: Bypass Page Context for Home Page Queries |
The chatbot flow has been updated to handle questions asked from the dashboard home page differently. When a user submits a query from the home page, the chatbot no longer attempts to search only within the corresponding documentation page. Instead, it skips directly to the broader documentation search flow, allowing the LLM to evaluate all available documentation. This prevents limited responses and improves overall response quality and performance. |
06-Apr-26 |
|
|
Chatbot: Handling “Show Variety” Question |
An issue was identified where the chatbot was unable to answer a question about the “Show variety” option in Advanced Merchandising, even when the context was specified. The root cause was related to configuration and documentation indexing behavior. Configuration updates were made to improve document loading and embedding retrieval, ensuring the relevant Advanced Merchandising documentation is correctly indexed and accessible. The chatbot can now successfully retrieve and respond with the appropriate explanation. The enhancement is working as expected. |
06-Apr-26 |
|
|
Helper Chatbot: Chatbot Prompt Enhancement for Unresolved Questions |
The chatbot has been updated to better handle broad or unclear questions. The UI now passes the documentation page name (from Alias.xml) as context, and this value is included in vector embeddings metadata. The LLM first searches within the current page’s documentation before falling back to the broader documentation search. If no answer is found after both steps, the chatbot now asks the user to provide more context instead of returning a generic response |
06-Apr-26 |
|
|
Ensemble AI: LLM Optimization for Vector DB Searches |
Performance improvements have been implemented to optimize LLM-driven vector database searches in Ensemble AI. Enhancements focus on improving batch processing and refining vector query handling to support onboarding additional clients for LLM jobs. Optimization changes were delivered within the defined scope, while the image embedding workflow remains unchanged for now. The enhancement is working as expected. |
06-Apr-26 |
Bug and Support Fixes
The following issues have been fixed in the release version 26.07.
|
Jira # |
Module/Title |
Summary |
General Availability |
|---|---|---|---|
|
Find: Related Searches Generator Job: Support Multiple Mongo Pipelines |
The Related Searches generator job was failing for queryType: "topAndZeroResultSearches" due to an unsupported MongoDB pipeline stage ($facet), resulting in job failure . Since separate pipelines for topSearches and zeroResultSearches already exist, the job has been enhanced to support running multiple Mongo query pipelines instead of relying on $facet. With this update, the job executes the required pipelines independently and combines the results as needed, avoiding the unsupported stage and ensuring stable execution. The issue has been fixed. |
06-Apr-26 |
|
|
Enterprise Dashboard: Fixes to InSegment Option in Configurable Strategies |
Updates have been made to improve the InSegment behavior in Configurable Strategies. When custom segments are used in a strategy, the segment dropdown in the View Results tab now correctly displays the segment names. In addition, when opening a saved strategy, no model is preselected by default, ensuring the configuration reflects the saved state accurately. The issue has been fixed.
|
06-Apr-26 |
|
|
Discover, Find: Discover Merge Logic Scalability Improvements |
The existing DocListMerger.merge logic had O(n²) complexity, making it inefficient for large catalog clients. The merge handling has been updated to ensure better scalability and performance for high-volume Browse API requests. The rrEnableDiscoverMerge parameter is now automatically controlled based on request conditions. It is set to ‘false’ when start + rows > 500, or when a custom sort is passed in the request. When start + rows ≤ 500 and no custom sort is provided, the existing behavior remains unchanged with rrEnableDiscoverMerge set to ‘true’. All valid Browse API requests continue to return successful 200 responses without errors. |
06-Apr-26 |