The Pure AI Blog Short Dispatches from AI's Front Lines
The Pure AI Blog is researched, fact-checked, edited and updated by the editors of PureAI.com, with writing assistance from AI. To submit your company's press release for consideration, contact [email protected].
Akeneo, a leader in product experience, launches a suite of high-velocity capabilities engineered to improve speed and adaptability in digital commerce, particularly as retailers and brands manage growing product assortments and channels. Akeneo's latest innovation aims to use AI agents to help teams maintain accurate, enriched product data while dynamically supporting discovery, personalization and engagement across digital touchpoints. High-impact new features include the Akeneo Digital Showroom, Stripe Agentic Commerce Suite partnership, a native MCP server and customized components that enable teams to extend PIM with purpose-built interfaces. Akeneo’s platform is designed to serve as a foundation for these AI-driven interactions by ensuring product information is consistent, contextual and ready for automated use.
The focus on agentic AI reflects broader changes in commerce operations. For e-commerce and IT leaders, Akeneo’s message underscores that as AI agents take on more autonomous roles, product information management becomes increasingly central to sustaining speed, trust, and relevance in digital commerce environments. The release further confirms Akeneo's evolution into an AI-powered execution platform.
Posted by Pure AI Editors on 01/12/20260 comments
Cordial, a leader in messaging for enterprise marketing teams, has announced two new AI Agents with capabilities designed to bring artificial intelligence into the work marketers do every day, rather than limiting it to background workflows and automation. The updates focus on helping teams interpret customer signals, generate content and adjust engagement strategies in real time as data changes across channels. Agents include the Email Production Agent that aims to execute heavy email marketing tasks such as personalization, logic, orchestration and measurement. The Data Intelligence Agent monitors campaigns and audience reaction in real-time, offering marketers the opportunity to identify trends and amend campaigns as they launch. Cordial's approach is intended to reduce lag between insight and action, particularly as customer behavior becomes more fragmented and harder to predict.
The move reflects a broader shift in marketing technology toward operational AI that supports decision-making, not just orchestration. By embedding AI into execution tasks, Cordial is aligning with the growing demand for adaptive engagement that responds continuously rather than through static rules. Cordial Agents are also designed to work collaboratively, which strengthens context, briefs, understanding and coordination strategies. For marketing leaders, the announcement highlights how AI is increasingly being positioned as a day-to-day collaborator rather than a behind-the-scenes optimization tool.
Posted by Pure AI Editors on 01/12/20260 comments
Relativity, a legal data intelligence company, has introduced aiR for Case Strategy, a generative AI capability designed to help legal teams analyze matters earlier and develop case strategy more efficiently. The offering applies large language models to case materials to surface key facts, timelines, themes and potential arguments, with the goal of supporting faster insight during investigations and litigation preparation. The tool is built on its existing aiR platform and integrates directly with data already managed in RelativityOne.
The launch reflects growing adoption of generative AI across the legal technology market, particularly in areas that extend beyond e-discovery into higher-level legal analysis. Using a platform like aiR allows legal teams to focus more efficiently on their arguments and allows greater collaboration across teams with a centralized hub of shared case intelligence repositories. For law firms and corporate legal departments, tools like aiR for Case Strategy signal a shift toward using AI not only to manage data volumes, but to inform legal judgment earlier in the case lifecycle.
Posted by Pure AI Editors on 01/12/20260 comments
Narvar, a platform for beyond-buy intelligent personalization, has introduced NAVI, an AI assistant designed to automate post-purchase customer experiences for retailers. The assistant is designed to manage common customer inquiries, such as order tracking, delivery delays, returns and exchanges, by acting autonomously across Narvar’s post-purchase workflows. NAVI is expected to be released at the NRF 2026 Retail Show and aims to apply intelligence and context at scale to achieve operational autonomy. Navi's goal is to reduce contact center volume while giving consumers faster, more consistent answers after checkout.
Post-purchase interactions have become a growing cost center for retailers as e-commerce volumes rise and delivery expectations tighten. Narvar’s approach is tightly scoped to order lifecycle events and logistics data, with NAVI designed to enable post-purchase workflows that smoothen operations without the need for system replacements. For retailers, agentic assistants that can resolve routine issues without escalation may help improve satisfaction while controlling support costs during peak seasons.
Posted by Pure AI Editors on 01/12/20260 comments
Samsung used its CES 2026 First Look event to outline a broader vision for “AI Living,” emphasizing how artificial intelligence can act as a personalized companion across the home. The company highlighted updates across TVs, appliances, mobile devices and smart home services that rely on on-device and hybrid AI to adapt to user behavior while limiting unnecessary cloud dependency. Samsung's goal is to build a unified, personal experience across mobile, visual displays, home appliances and services. Other announcements include an expansion into the healthcare sector with dementia detection research and personalized health coaching. Updates also included Vision AI for next-level viewing, an advanced Odyssey gaming monitor and updates to home appliances such as Family Hub, Bespoke AI Laundry Combo and the Bespoke AI Jet Bot Stream Ultra, among others.
The strategy reflects a wider shift in consumer technology toward ambient and embedded AI. Samsung’s approach focuses on tying AI capabilities into its SmartThings ecosystem, positioning connected devices as cooperative systems rather than independent endpoints. For device makers and platform partners, the announcements underscore how AI is becoming a foundational layer in consumer electronics design rather than a premium add-on.
Posted by Pure AI Editors on 01/05/20260 comments
TransAI, an AI hardware designer, plans to debut TransAI Note at CES 2026, positioning it as the first dedicated on-device AI hardware designed specifically for meeting transcription and note-taking. Unlike cloud-dependent assistants, the device performs speech recognition and summarization locally, reducing reliance on external servers and minimizing data exposure. TransAI's approach is aimed at professionals and organizations that handle sensitive conversations and want AI assistance without sending audio or text data off-device. At its core is NoteBrain, which is the proprietary on-device AI model trained for meeting notes specifically. It then generates structured meeting notes with summaries, key points and actionable items all on one device.
The launch comes as enterprises increasingly scrutinize how generative AI tools handle confidential information. TransAI’s hardware-first model reflects a different architectural choice, emphasizing edge AI and privacy-by-design. For regulated industries such as healthcare, legal services and finance, on-device processing could make AI-assisted meeting capture more viable, especially where recording policies or compliance requirements restrict cloud-based tools.
Posted by Pure AI Editors on 01/05/20260 comments
Veeam, a market leader in data resilience, has partnered with ServiceNow to integrate data resilience capabilities directly into enterprise IT workflows, linking backup, recovery and cyber response operations with ServiceNow’s platform. The collaboration is designed to help organizations manage data protection events—such as ransomware incidents, system outages, or recovery testing—within familiar ServiceNow processes used by IT operations, risk and security teams. By surfacing Veeam data inside ServiceNow, customers can automate notifications, trigger remediation workflows and track recovery actions alongside other operational incidents. The Veeam App for ServiceNow allows organizations to decentralize backups, streamline incident responses and enhance visibility. Additional features include automated compliance, bi-directional synchronization, accelerated traceability and seamless integration for ServiceNow users.
The partnership reflects a broader shift toward operationalizing cyber resilience rather than treating backup and recovery as standalone functions. Veeam–ServiceNow alignment emphasizes workflow automation and cross-team visibility. For large organizations managing complex environments, embedding data resilience into ServiceNow workflows may help standardize response and reduce friction during high-impact events.
Posted by Pure AI Editors on 01/05/20260 comments
Wherobots, the spatial intelligence cloud that enables data innovation, has introduced RasterFlow, a new service designed to simplify how organizations apply AI and machine learning to satellite and overhead imagery. Built by the creators of Apache Sedona, RasterFlow automates imagery mosaicking, preprocessing, model execution, and change detection in a single workflow, removing much of the custom engineering traditionally required to productionize geospatial AI. The platform enables faster deployment of custom models on proprietary imagery while writing results to Apache Iceberg tables for downstream use in platforms such as Databricks and Snowflake.
The launch comes as enterprise investment in Earth intelligence accelerates. The aim of RasterFlow is to turn raw imagery into actionable insights to combine with enterprise data and AI to produce effective risk assessments and optimization routes, among other uses. Early users and partners, including the Taylor Geospatial Institute and Spyrosoft, are applying RasterFlow to use cases ranging from agriculture and climate analysis to logistics and risk assessment. For data and AI teams, RasterFlow reflects a broader shift toward treating geospatial data as a first-class input for real-time, production AI systems rather than a specialized analytics niche.
Posted by Pure AI Editors on 01/05/20260 comments
LangGrant, a leader in database modernization and synthetic data, has launched the LEDGE MCP Server, an enterprise database orchestration and governance engine designed to manage how large language models (LLMs) interact with structured and unstructured data. The platform acts as a control layer between LLMs and enterprise databases, enabling organizations to define access rules, enforce policies and monitor usage across AI-driven applications. LangGrant says the server removes friction between LLMs and enterprise data. It is intended to support retrieval-augmented generation (RAG) and agent-based workflows while reducing the risk of unauthorized access or data leakage.
As enterprises move LLMs from experimentation into production, data governance has emerged as a major challenge. LangGrant’s approach focuses specifically on LLM-to-database interaction with capabilities such as LLM governance, token dashboards, analytics plans, database cloning on demand and complete automated database context at scale. For security and data teams, the release reflects growing demand for infrastructure that treats AI access to data with the same rigor as traditional applications.
Posted by Pure AI Editors on 01/05/20260 comments
Arbe, a leader in high-resolution radar solutions, has announced a collaboration that combines its high-resolution radar technology with NVIDIA’s AI computing platforms to create an integrated system for AI-based driving applications. The joint approach is designed to improve how vehicles perceive and interpret their surroundings by pairing Arbe’s radar, which delivers detailed detection in challenging conditions, with NVIDIA’s accelerated computing for sensor fusion and real-time processing. Arbe claims that the collaboration accelerates the adoption of safer and affordable autonomous driving solutions.
The announcement reflects continued investment in multi-sensor strategies as automakers seek safer and more scalable paths to autonomy. Arbe’s focus on ultra-high-resolution radar, combined with NVIDIA's accelerated computing capabilities, differentiates its approach. For automotive engineers and platform developers, tighter integration between sensing hardware and AI compute highlights the industry’s shift toward end-to-end, software-defined vehicle systems.
Posted by Pure AI Editors on 01/05/20260 comments