The 2026 Icecat roadmap focuses on enhancing the speed, reliability, and usability of our platform for all users, from channel and brand partners to internal Icecat teams. It includes improvements across search, data accessibility, automation, analytics, and system infrastructure, aiming to streamline workflows, reduce errors, and provide faster, more accurate access to product information. By modernizing core systems, optimizing processes, and introducing intelligent tools, these developments will empower users to work more efficiently, maintain higher data quality, and deliver better experiences.
| Development | Value | Delivery Timeline |
| Classic Search Improvement & AI Search | Search users will find products faster and more accurately thanks to improved relevance, smarter ranking, and cleaner classic search behavior, while Multilingual AI Search removes language barriers by understanding queries in different languages and returning consistent, high-quality results making product discovery easier, more intuitive, and globally accessible. | Q1 – Q3 |
| Chat-Bot to Answer Users Questions About Product | Users can instantly get clear, accurate answers to product questions in natural language such as features, rich content, manuals, and others without searching through the page. The chatbot provides trusted, up-to-date information directly from Icecat, improving Icecat MCP discoverability. | Q1 |
| Development | Value | Delivery Timeline |
| Product Health Score Reporting | Partners will be able to receive a single, consolidated report with clear insights into the data quality of their products, evaluated against selected partner standards. This will help them quickly identify gaps, inconsistencies, and improvement areas, ensure compliance with partner requirements, improve overall product data quality, and reduce manual effort in audits. | Q1 |
| Partner Taxonomy Features Management | This functionality streamlines the process of attaching product features to channel partner taxonomies, reducing manual effort and minimizing errors. It allows the team to efficiently manage feature assignments, maintain consistency across partner standards, and accelerate product onboarding and updates, ultimately improving operational efficiency and the quality of product data delivered to partners. | Q1 |
| Brand User Product Processing List | Brand users can focus exclusively on a curated list of their products, reducing distractions from unrelated items. This functionality allows them to efficiently manage, review, and update their product data, improving productivity, minimizing errors, and ensuring that attention is directed only to the products that matter most to their brand operations. | Q1 |
| ETL Processes Streamlining | This functionality significantly improves editorial team efficiency, control, and accuracy in managing product data. By enabling asynchronous processing with progress visibility, task cancellation, and flexible GTIN import/export management, editors can handle large data volumes confidently and reduce errors. The ability to roll back assets and upload partner-specific descriptions ensures that corrections and updates are quick, precise, and consistent. | Q1 – Q2 |
| Features Matching Tool | This tool automates the process of matching product features to batches of products based on defined criteria. It reduces manual effort, ensures consistency and accuracy in feature assignments, and speeds up product data preparation. | Q1 – Q3 |
| Product Data Extraction From Channel Partner Feeds | This tool simplifies access to product information provided by channel partners, enabling quick extraction of relevant data for product descriptions. It reduces the time spent manually gathering partner data, ensures consistency and completeness of product content, and allows editors to efficiently enrich product datasheets with accurate, up-to-date information. | Q3 |
| User Activity Automatic Detect | This functionality enables proactive monitoring of partner activity, allowing the team to identify engagement patterns, detect potential issues, and reach out proactively. By automatically capturing user actions, it helps teams provide timely support, gather actionable feedback, and strengthen partner relationships. | Q3 |
| Images Automatic Content Processing | This functionality automates the categorization and batch management of product images, reducing manual effort and accelerating media handling. Editors can quickly organize, tag, and process large volumes of images, ensuring consistency and compliance with standards. | Q4 |
| Custom Features Value Functionality Upgrade | This upgrade modernizes the existing functionality to reduce errors, simplify maintenance, and streamline the processing of new feature value requests. For the taxonomy team, it enables faster, more reliable management of custom feature values, improving workflow efficiency and accuracy. | Q4 |
| Taxonomy Attributes Automatic Translation | This functionality automates the translation of category names, feature names, feature values, and feature descriptions, reducing the time spent on routine multilingual tasks. For multilingual users, it ensures faster, more consistent, and accurate translations, minimizing manual effort and errors. | Q4 |
| Ticketing System Security Upgrade | This upgrade modernizes the ticketing system’s architecture and code, improving security, reliability, and user experience. For partners, it ensures that the information is protected, system performance is more stable, and interactions with the ticketing system are smoother and more intuitive. | Q4 |
| Development | Value | Delivery Timeline |
| MCP Server: Tools for Product Data Accessibility | These tools provide users with fast, reliable, and flexible access to product data stored in the MCP server. | Q1 |
| MCP Server: Tools for Product Statistics Accessibility | These tools provide users with easy access to product-related statistics, enabling them to monitor popularity and analyze trends. This means faster insights into product data usage, more informed decision-making, and the ability to identify opportunities proactively. | Q1 |
| MCP Server: Tools for Product Search | These tools enable users to quickly and accurately find products within the MCP server using advanced search capabilities. This means faster access to relevant product data, and more efficient workflows. | Q1 – Q3 |
| MCP Server: Tools for Product Data Flow to Icecat | These tools enable seamless transfer of product data from users to Icecat, ensuring that information is accurate, complete, and up-to-date. This reduces manual effort, minimizes errors, and accelerates the publishing process. | Q2 |
| API Product Data Retrieval | This functionality is going to provide an intelligent, efficient alternative to traditional index files for accessing product data. For channel partners and integration teams, it allows fast, precise retrieval of product content, reducing complexity and manual handling. | Q2 – Q3 |
| Taxonomy API | This API is going to provide comprehensive access to Icecat’s taxonomy, including updates, changes, and filtered views tailored to user needs. For channel partners and integration teams, it enables quick retrieval of relevant taxonomy information, and ensures alignment with the latest Icecat taxonomy structure. | Q3 – Q4 |
| Live, XML, JSON, and other services performance boost and stability in disaster | This improvement enhances the speed, reliability, and resilience of Icecat’s data delivery services. Consistent performance even under high load, and uninterrupted service during system failures or disasters are the key deliverables of this roadmap point. | Q1 – Q4 |
| Push API Optimizations | This development improves the performance and reliability of Push APIs under high-load conditions, reducing errors and ensuring timely data delivery. For brand partners, autoimport teams, and internal users, it means more stable, efficient, and predictable updates of product information. | Q1 – Q2 |
| Development | Value | Delivery Timeline |
| Instant Product Metadata Retrieval | This optimization ensures that rarely changing data such as brand, category, feature, and configuration metadata is quickly and reliably accessible. For all users of Icecat services, it reduces latency, improves system responsiveness, and provides a smoother experience when retrieving essential product metadata. | Q1 |
| Re-engineering Product Permissions | This development centralizes product access control into a single, dedicated service, replacing scattered implementations. It ensures more predictable and reliable access to product data. For Icecat development teams, it simplifies maintenance, accelerates enhancements, and decreases the risk of bugs. | Q1 – Q4 |
| Icecat.biz database and queue brokers optimizations | These optimizations streamline data storage and messaging systems to create a faster, more scalable, and reliable platform. For all users and internal teams, this means more consistent, accurate, and timely product data, fewer system errors, and improved overall service performance. Operationally, it reduces duplication and inefficiencies, minimizes bugs, and enables smoother handling of high volumes of data and messages. | Q1 – Q4 |
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