• Integrated campaign planning
  
• Unified data insights
  
• Creative production support
  
• Post-campaign measurement
  

Global footwear and accessories retailer ALDO Group is consolidating its digital marketing strategy—and it’s handing the keys to P3 Media. The company has named the Shopify-focused agency its digital marketing partner for the entire ALDO portfolio, including ALDO, Sperry, G.H.Bass, and Call It Spring.

The move signals a deeper push into performance marketing and digital commerce as the retailer manages an increasingly complex ecosystem spanning ecommerce, marketplaces, and thousands of physical stores worldwide.

A Global Digital Overhaul

ALDO Group has long positioned itself as an omnichannel retail innovator, blending brick-and-mortar retail with robust ecommerce operations. But as digital retail evolves—and performance marketing grows more data-driven—the company is aiming to tighten its media strategy across brands and markets.

P3 Media’s mandate: unify media buying, streamline campaign execution, and build a scalable digital growth engine that works across ALDO’s global portfolio.

In practice, that means aligning paid media, creative, data analytics, and AI-powered optimization under a single strategy rather than fragmented campaigns by brand or region.

The goal is straightforward but ambitious: accelerate digital revenue while maintaining consistent brand performance worldwide.

“ALDO Group operates at the forefront of digital retail, managing a highly complex global commerce ecosystem across multiple brands and markets,” said Monica Provenza, Head of Digital Commerce at ALDO Group. “At this inflection point in digital commerce technology, it was critical to partner with an agency that can operate as a true extension of our team while bringing every tool necessary to help us achieve our ambitious growth vision.”

Why P3 Media Won the Pitch

The partnership follows a competitive pitch process in which ALDO evaluated potential agencies on media expertise, responsiveness, strategic vision, and innovation capabilities.

P3 Media ultimately secured the contract by positioning itself as a hybrid partner: part media agency, part ecommerce growth consultancy.

The firm is best known as a Shopify Platinum Partner, a designation reserved for agencies with deep expertise in Shopify’s enterprise commerce platform. Its client work typically blends performance marketing, data science, and AI-driven optimization—an increasingly common formula among digital commerce agencies trying to differentiate beyond basic media buying.

For ALDO, that blend of commerce and marketing expertise appears to have been decisive.

“P3 demonstrated the strategic depth, technical fluency, and collaborative mindset we were looking for,” Provenza said.

A Portfolio Play

Unlike many agency appointments that focus on a single brand, this deal spans ALDO Group’s entire footwear portfolio.

That includes:

• ALDO, the company’s flagship global fashion footwear brand

• Sperry, known for boat shoes and heritage lifestyle products

• G.H.Bass, a historic American footwear label

• Call It Spring, a younger, trend-driven brand aimed at Gen Z shoppers

Managing performance marketing across four distinct brand identities—and multiple regions—adds a layer of complexity.

Each brand serves different audiences, price tiers, and geographic markets. Aligning them under a single performance marketing framework requires balancing centralized data with localized creative strategies.

That’s precisely where ALDO expects P3 Media to deliver.

The AI Factor

Another notable element of the partnership is the emphasis on AI-driven marketing.

Retailers increasingly rely on machine learning for tasks like audience targeting, campaign optimization, predictive merchandising, and customer lifetime value modeling.

Agencies, meanwhile, are racing to build AI into their marketing stacks to stay competitive.

P3 Media says it plans to combine its AI capabilities with media and creative strategy to support ALDO’s digital expansion.

“It’s an honor to partner with ALDO Group and support such an iconic portfolio of brands,” said Aanarav Sareen, CEO and co-founder of P3 Media.

David Wagoner, the agency’s CMO and co-founder, emphasized the collaborative nature of the partnership.

“From the outset, the ALDO team has communicated a clear and compelling vision for where they want to go,” Wagoner said. “We’re excited to align our media, data, creative, and AI capabilities around that vision and help bring their next chapter of digital marketing to life.”

Why This Matters for Retail Marketing

ALDO’s agency consolidation reflects a broader shift happening across retail.

Brands with complex global footprints are increasingly moving away from fragmented marketing stacks—multiple agencies, regional media buyers, disconnected analytics platforms—and toward unified growth partners.

The reasons are both strategic and practical:

• Performance marketing has become highly data-intensive

• AI-driven optimization requires centralized datasets

• Ecommerce growth demands tight integration between media and commerce platforms

Retailers also face rising acquisition costs across platforms like Google, Meta, and TikTok, making optimization and efficiency critical.

By consolidating media execution under one agency partner, brands aim to improve attribution, streamline decision-making, and scale campaigns more effectively.

The Bigger Commerce Strategy

For ALDO Group, the move fits into a broader digital transformation effort underway across the fashion retail industry.

Footwear brands are increasingly investing in:

• Direct-to-consumer ecommerce

• Marketplace expansion

• Omnichannel fulfillment

• Data-driven marketing strategies

Retailers that once relied heavily on physical stores are now treating digital channels as their primary growth engine.

ALDO already operates thousands of retail locations globally, but its ecommerce presence continues to expand across multiple platforms and markets.

Partnering with a Shopify-specialized agency suggests the company intends to deepen its commerce integration with marketing performance—something many fashion brands are now prioritizing.

What Comes Next

The immediate focus for P3 Media will likely involve consolidating campaign infrastructure and optimizing media performance across ALDO’s global operations.

Longer term, the partnership could extend into broader areas such as AI-powered personalization, creative automation, and deeper integration between marketing and commerce analytics.

For ALDO, the outcome will be measured in a familiar metric: digital growth.

For the agency world, the deal is another sign that enterprise retailers increasingly want marketing partners capable of blending technology, commerce expertise, and performance marketing under one roof.

In the modern retail playbook, media buying alone no longer cuts it.

Get in touch with our MarTech Experts.

At Embedded World 2026, industrial computing company DFI is rolling out a new wave of edge AI platforms designed to push artificial intelligence beyond pilot projects and into real-world industrial deployment.

Working closely with Intel, the company plans to showcase application-driven edge AI systems built for robotics, defense infrastructure, and medical imaging—sectors where reliability, power efficiency, and long-term system stability matter just as much as raw AI performance.

The announcement underscores a broader shift in industrial AI: moving from experimental proof-of-concept deployments to scalable, production-ready systems capable of operating in harsh environments.

Edge AI Moves From Lab to Factory Floor

Edge AI has been a major talking point across manufacturing, robotics, and infrastructure sectors for several years. But many deployments have remained limited to controlled demonstrations.

Industrial operators now want something different: platforms that combine AI inference with real-time control, deterministic networking, and long operational lifecycles.

DFI says its latest product portfolio is designed around exactly those requirements. Rather than building standalone AI appliances, the company is focusing on layered computing platforms that integrate AI acceleration, real-time processing, and industrial I/O in a single architecture.

The approach is particularly relevant for robotic automation systems such as robotic arms used in production lines—applications where even milliseconds of latency can affect precision and safety.

New Edge AI Hardware for Defense and Medical Applications

Among the products debuting at Embedded World 2026 is the PTH9HM COM-HPC Mini module, a credit-card-sized computing engine optimized for size, weight, and power (SWaP)—a key requirement in defense and unmanned systems.

Powered by Intel Core Ultra Series 3 processors with integrated Intel Arc GPU, the module supports real-time 8K vision processing and AI inference for applications including:

• Autonomous navigation

• Target recognition

• Threat detection and tracking

The module is engineered for rugged environments, operating in temperatures from –40°C to 85°C. It includes up to 64GB of LPDDR5x memory and supports PCIe Gen 5 connectivity, dual 2.5GbE networking, and TPM 2.0 security for mission-critical deployments.

For healthcare environments, DFI is introducing the PTH171 and PTH173 Mini-ITX edge AI motherboards, designed for medical imaging and diagnostic systems.

These boards use Intel Core Ultra Series 3 processors capable of delivering up to 180 total TOPS (trillion operations per second) of AI performance. They include integrated Intel Arc graphics, PCIe Gen 5 expansion, and extensive display and I/O connectivity—features that support high-resolution imaging systems and diagnostic devices.

The boards also include Intel vPro manageability, allowing healthcare providers to remotely manage and maintain systems deployed in hospitals or diagnostic centers over long operational lifecycles.

One Platform for Robotics and Industrial Automation

Another key component of the showcase is the SF101-PTH compact industrial system, a performance-oriented edge platform built around Intel’s heterogeneous computing architecture.

Instead of relying on discrete GPUs, the system integrates:

• CPU processing

• Integrated GPU acceleration

• Dedicated NPU (Neural Processing Unit)

This combination enables the platform to run real-time control systems, machine vision workloads, and AI inference simultaneously.

The architecture also integrates real-time technologies such as Intel Time Coordinated Computing and Time-Sensitive Networking, enabling millisecond-level responsiveness for industrial control systems.

By eliminating the need for additional GPUs, the system improves power efficiency and reduces total cost of ownership—two critical factors in industrial environments where equipment may operate continuously for years.

Building the Foundation for Physical AI

DFI’s focus on robotics applications reflects a growing industry trend often referred to as “physical AI”—the integration of AI systems into machines that interact directly with the physical world.

Unlike cloud-based AI models that primarily process data, physical AI systems must combine sensing, inference, and real-time actuation.

That makes edge computing essential.

Robotic arms on a manufacturing line, for example, must analyze visual input, make decisions, and execute movements almost instantly. Sending those tasks to the cloud introduces latency that can disrupt operations.

DFI says its platforms are designed to handle those workloads locally while maintaining deterministic system behavior and long-term reliability.

Just as importantly, the company says the same platform architecture can be reused across multiple use cases—including machine vision, industrial control systems, and intelligent infrastructure—reducing engineering complexity for system integrators.

Intel’s Software Ecosystem Plays a Key Role

The collaboration also relies heavily on Intel’s edge AI software ecosystem.

Through tools such as OpenVINO and Intel Edge AI Suites, developers can build, optimize, and deploy AI models tailored for edge environments.

These tools help system integrators manage AI workloads across distributed industrial deployments while maintaining lifecycle stability—an essential requirement for sectors like manufacturing and healthcare where equipment often remains in service for a decade or longer.

According to DFI marketing head Jarry Chang, the company’s strategy focuses on aligning hardware capabilities with real-world operational requirements rather than simply maximizing compute performance.

“Edge AI deployment starts with understanding industry requirements, not selecting compute performance in isolation,” Chang said. “By working closely with Intel, we focus on building edge AI platforms that map real operational needs—such as latency, reliability and lifecycle stability—to practical system architectures.”

A Broader Shift in Industrial AI

DFI’s announcements highlight a broader transformation happening across industrial AI markets.

Early edge AI deployments often relied on experimental hardware or specialized accelerators designed for narrow use cases.

Today, industrial operators are increasingly demanding standardized platforms that can support multiple workloads—AI inference, real-time control, networking, and security—within a single edge computing architecture.

That shift is helping accelerate adoption across sectors including manufacturing automation, defense systems, medical imaging, and smart infrastructure.

By positioning its new portfolio as a scalable edge computing foundation rather than a collection of single-purpose systems, DFI is aiming to capture that next phase of industrial AI growth.

And if the strategy works, the company’s edge platforms could become a core building block for the next generation of AI-powered machines operating outside the data center.

Get in touch with our MarTech Experts.

A new study from BrightEdge suggests AI search engines aren’t just answering questions—they’re quietly shaping brand reputations.

According to the company’s latest research, Google AI Overviews is 44% more likely to surface negative sentiment about brands than ChatGPT overall. But ChatGPT delivers criticism at a far more critical moment: right before customers make a purchase.

For chief marketing officers and digital teams, that dynamic introduces a new category of brand risk—one that traditional SEO metrics can’t fully capture.

The findings, powered by BrightEdge’s AI Catalyst platform, arrive as AI-powered search becomes mainstream. The company estimates more than three billion people now interact with Google AI Overviews and ChatGPT monthly, meaning AI-generated commentary about brands is reaching audiences at unprecedented scale.

And unlike traditional search results, where negative reviews might hide on page two, AI systems often summarize sentiment directly in the answer.

AI Is Becoming a Brand’s Editorial Voice

In many ways, AI search behaves like an editor.

Rather than simply indexing content, modern AI systems analyze information across the web—including news coverage, reviews, forum discussions, and historical controversies—and compress it into a single response.

That means a brand’s digital past, including long-forgotten controversies or outdated reviews, can resurface instantly when users ask questions.

“For better or worse, AI is your brand’s new editorialist,” said Jim Yu. “Each engine characterizes your brand differently, and CMOs must treat them as distinct, dynamic environments.”

Negative Sentiment Is Rare—but Still Massive

At first glance, the amount of negative sentiment appearing in AI responses seems relatively small.

BrightEdge found that:

• Google AI Overviews show negative sentiment in about 2.3% of brand mentions

• ChatGPT shows negative sentiment in about 1.6% of mentions

But scale changes the equation.

Across billions of queries each month, even those small percentages translate into millions of negative brand exposures delivered directly in AI-generated answers.

And because AI responses are often reused across similar queries, the same criticism may appear repeatedly for many users asking similar questions.

Google vs. ChatGPT: Two Very Different Critics

The study also found that the two AI systems behave differently when evaluating brands.

Google AI Overviews tends to surface negativity tied to controversy and external events, including:

• Lawsuits

• Regulatory scrutiny

• Product recalls

• Data breaches

• Public boycotts

In contrast, ChatGPT focuses more on product-level critiques, including:

• Feature limitations

• Compatibility issues

• Value-for-money debates

• Purchase recommendations

The result is that the same brand might face very different criticism depending on the AI platform.

A retailer might appear in Google’s AI responses because of a lawsuit mentioned in the news, while ChatGPT might highlight product return policies or payment restrictions.

The divergence stems largely from their source ecosystems.

Google’s AI Overviews lean heavily on news coverage and authoritative media, while ChatGPT often reflects product reviews, community discussions, and forums like Reddit.**

ChatGPT Hits Hardest Near the Point of Purchase

Perhaps the most surprising finding is when negative sentiment appears.

Most criticism in Google AI Overviews appears early in the customer journey.

BrightEdge found that 85% of Google’s negative sentiment surfaces during informational searches, when users are researching products or building shortlists.

ChatGPT behaves very differently.

While 68.5% of its negative responses also occur during the informational stage, nearly 19.4% appear during the consideration-to-purchase phase—when consumers are deciding whether to buy.

That’s 13 times higher than Google’s 1.5% rate at that stage.

In other words:

• Google shapes brand perception early in the funnel

• ChatGPT can directly influence conversion decisions

For marketers, that difference matters.

A negative AI response at the research stage may influence awareness. But criticism delivered just before purchase can derail a sale entirely.

AI Engines Rarely Agree on Which Brand Is at Fault

Another surprising discovery: AI platforms often disagree about which brand deserves criticism.

When BrightEdge analyzed queries where both engines surfaced negative sentiment, Google and ChatGPT flagged different brands 73% of the time.

This suggests that monitoring a single AI platform provides an incomplete view of brand perception.

Instead, companies may need to track sentiment across multiple AI ecosystems—each with its own content sources, ranking signals, and reasoning models.

Industry Differences Are Emerging

The research also found that AI criticism varies significantly by industry.

For example:

Electronics:
Both platforms show higher negativity rates, with Google leading due to product recalls and technology controversies.

Education:
Google is nearly twice as negative as ChatGPT, reflecting coverage tied to political and institutional scrutiny.

Apparel:
The pattern flips. ChatGPT is three times more negative than Google, largely because product evaluations dominate the conversation rather than controversy.

For brands, that means AI sentiment monitoring must be tailored to the dynamics of each vertical.

AI Is Surfacing the Internet’s Long Memory

Another challenge highlighted in the report is the way AI engines resurface historical content.

Because AI summarizes information across a brand’s entire digital footprint, events from years—or even decades—ago can reappear in modern responses.

Examples cited by BrightEdge include:

• A decade-old smartphone safety recall appearing in responses to queries about battery life

• A celebrity-brand partnership discussed in an old Reddit thread resurfacing as evidence of brand sentiment

• Insurance companies criticized for not renewing homeowner policies in California appearing in AI comparisons

In traditional search, users might need to dig through multiple pages to find such content.

In AI-driven search, those details appear instantly in the answer.

A New Metric for CMOs: AI Sentiment Visibility

For marketing leaders, the takeaway is clear: AI search has introduced a new layer of brand management.

Tracking visibility in AI-generated answers is no longer enough.

Companies now need to monitor how AI describes their brand, not just whether it appears in results.

That includes measuring:

• AI sentiment across platforms

• Share of voice in AI responses

• Source ecosystems influencing AI answers

• Funnel-stage impact on conversions

“Sentiment monitoring across all AI engines is no longer optional,” Yu said. “It’s a revenue imperative.”

As generative AI continues to reshape search, brands may find themselves optimizing not just for algorithms—but for AI’s evolving editorial judgment.

Get in touch with our MarTech Experts.

Customer data may be plentiful in ecommerce, but it’s rarely unified. That’s the gap Opensend hopes to close with its latest move.

The company announced it has acquired Fueled.io, a startup focused on organizing and activating first-party customer data for online merchants. The combined platform aims to help ecommerce brands transform anonymous site traffic into identifiable, actionable customer profiles—without requiring a full rebuild of existing marketing stacks.

The deal signals a growing shift in the marketing technology landscape as brands move away from third-party tracking and toward identity-driven, first-party data strategies.

Bridging the Anonymous Data Gap

Ecommerce businesses face a familiar challenge: the majority of site visitors remain anonymous, leaving marketers with incomplete customer profiles and fragmented data.

Opensend’s core technology focuses on solving that problem through identity resolution—identifying and enriching shopper activity across devices and sessions. By contrast, Fueled specializes in collecting and organizing first-party behavioral data such as:

• Purchases

• Site engagement

• Customer lifecycle events

• Marketing interactions

The acquisition combines those capabilities into a single workflow.

In simple terms, Opensend can identify who a visitor might be, while Fueled ensures that the resulting customer signals are structured and usable across marketing systems.

The goal is to create a seamless bridge between anonymous browsing activity and fully actionable customer data.

A Unified Customer Data Engine

For merchants, the combined offering promises deeper insights and stronger activation across multiple marketing channels.

Brands will be able to use enriched identity data to power:

• Paid advertising campaigns

• Lifecycle messaging and email marketing

• On-site personalization

• Customer analytics and measurement

By connecting identity resolution with structured data activation pipelines, the platform helps brands build more complete shopper profiles.

Those enriched profiles can then fuel targeting, personalization, and attribution across marketing workflows.

“This acquisition creates a new standard for how ecommerce brands identify and engage with their customers,” said Dahn Tamir. “By pairing our identity resolution with Fueled’s robust data activation pipelines, we’re enabling brands to grow and activate their audiences like never before.”

Why First-Party Data Is the New Battleground

The timing of the acquisition reflects broader changes across digital marketing.

With growing privacy regulations and the gradual decline of third-party cookies, brands increasingly rely on first-party data—information collected directly from customers through their own channels.

But gathering first-party data is only part of the equation.

Many companies struggle to:

• Centralize data from multiple touchpoints

• Maintain clean, structured event pipelines

• Activate those signals across advertising and CRM platforms

Platforms like Opensend and Fueled are designed to address exactly that gap.

Rather than replacing existing tools, the companies emphasize integration—allowing merchants to activate customer signals across their current marketing stacks.

Shared Customers Accelerate the Integration

The companies say many merchants already use both platforms, which should simplify the transition.

Existing shared customers will gain expanded identity enrichment capabilities combined with stronger data activation infrastructure as the products merge.

That integration could improve the accuracy of marketing signals used for segmentation, targeting, and performance measurement.

For ecommerce operators increasingly focused on measurable ROI, stronger signal quality can translate directly into better campaign performance.

Fueled Founder Joins Opensend Leadership

As part of the acquisition, Sean Larkin will join Opensend as Chief Product Officer.

In his new role, Larkin will lead product integrations and innovation across the combined platform, focusing on performance optimization and expanded data activation capabilities.

“Opensend has built a reputation for integrity and innovation in data,” Larkin said. “Our shared focus on transparency, accuracy, and respect for the customer made this partnership a natural fit.”

Larkin also emphasized the democratizing impact of the combined technology.

“Together, we’re giving merchants of all sizes the tools that only enterprise players previously had access to.”

The Bigger MarTech Trend: Identity + Activation

The Opensend–Fueled deal reflects a broader consolidation trend within marketing technology.

Historically, identity resolution platforms and customer data platforms (CDPs) operated in separate categories.

Identity platforms focused on identifying users, while CDPs focused on organizing and activating customer data.

Today, those categories are converging.

Brands increasingly want end-to-end customer intelligence systems that can:

1. Identify anonymous users

2. Build unified profiles

3. Activate data across channels

4. Measure marketing impact

The acquisition effectively positions Opensend closer to that unified model.

Privacy and Data Responsibility

The companies also emphasized responsible data practices as part of the deal’s strategic focus.

As regulators and consumers scrutinize how companies collect and use data, platforms that prioritize transparency and compliance are gaining importance.

According to Opensend, the combined platform will emphasize privacy-forward data practices, ensuring that brands can leverage first-party signals while respecting consumer expectations and regulatory requirements.

What Comes Next

Following the acquisition, Fueled will operate under the Opensend brand while its technology becomes integrated into the broader platform.

The combined company plans to focus on expanding tools that help ecommerce brands:

• Identify anonymous visitors

• Build unified customer profiles

• Activate first-party data across marketing channels

• Improve campaign measurement and attribution

In an era where customer data is both a strategic asset and a regulatory minefield, the companies are betting that merchants want a simpler way to turn data into action.

If they’re right, the future of ecommerce marketing may depend less on collecting more data—and more on finally making sense of the data brands already have.

Get in touch with our MarTech Experts.

The race to automate creative production just took another leap forward. Luma AI has introduced Luma Agents, a new class of AI collaborators designed to execute entire creative workflows—from initial concept to final asset delivery—across text, images, video, and audio.

The system targets agencies, marketing teams, studios, and enterprise organizations looking to scale creative output without multiplying tools or workflows. Instead of relying on a patchwork of AI generators and orchestration platforms, Luma’s approach consolidates the entire creative process inside a unified AI system capable of maintaining context across formats.

The launch reflects a broader shift in generative AI: moving beyond single-task tools toward autonomous AI systems that manage complex creative production pipelines.

From AI Tools to AI Collaborators

Most generative AI platforms today operate as standalone tools—one for writing copy, another for image generation, another for video production.

Producing a full campaign often means juggling multiple platforms, exporting files between them, and rebuilding context at every step.

Luma says its Agents aim to remove that friction.

“Creative work has never lacked ambition; it’s lacked execution capacity,” said Amit Jain. “Creative teams shouldn’t have to spend their time orchestrating tools. Agents aren’t shortcuts. They’re collaborators that maintain context, coordinate execution, and advance projects.”

Instead of generating a single output on demand, Luma Agents operate as persistent project collaborators capable of planning, producing, evaluating, and refining creative work over multiple iterations.

How Luma Agents Work

At the core of the system is an agent-based environment where human teams guide strategy and creative direction while AI handles execution tasks.

Within that environment, agents can:

• Execute projects end-to-end from planning to production

• Maintain shared context across text, images, video, and audio assets

• Develop multiple creative directions simultaneously

• Evaluate and refine outputs through iterative feedback

• Integrate with enterprise production systems via APIs

The platform also functions as a collaborative workspace, allowing human creators and AI agents to work together in a multiplayer-style environment where tasks are dynamically routed and refined.

For marketing teams managing complex campaigns, that could mean generating multiple creative variations, adapting content across markets, or producing multimedia assets at scale without manually coordinating dozens of tools.

Already Deploying Inside Global Agencies

Luma says its Agents are already being deployed inside major global agency networks.

Organizations including Publicis Groupe and Serviceplan Group are integrating the system into their creative and production workflows.

The goal is to accelerate campaign development while maintaining brand consistency across multiple regions.

According to Alexander Schill, the technology is already helping streamline collaboration across international teams.

“Luma is now part of our broader House of AI ecosystem and integrated directly into our creative workflows,” Schill said. “It allows our teams across more than 20 countries to collaborate more smoothly and develop great work faster.”

For global agency networks juggling hundreds of campaigns across markets, automation at the production layer could significantly improve throughput.

The Technology Behind the System

The platform is powered by what Luma calls Unified Intelligence, a new architecture designed to move beyond the industry’s typical “model pipeline” approach.

Today’s generative AI systems often rely on specialized models connected together:

• One model generates text

• Another generates images

• Another handles video

• Orchestration software attempts to combine their outputs

While effective for narrow tasks, these pipelines can lose context as information passes between models.

Unified Intelligence takes a different approach by training a single multimodal reasoning system capable of understanding and generating across formats within the same architecture.

The first model built on this system is Uni-1, a multimodal transformer capable of reasoning with both language and images in a shared token space.

Instead of generating assets sequentially through separate systems, Uni-1 can theoretically plan, imagine, and render creative outputs in a single reasoning process.

Luma compares the approach to how human creators work.

When an architect sketches a building, they’re simultaneously thinking about structure, light, and spatial experience—not switching between separate “models” for each concept.

Unified Intelligence aims to mimic that kind of integrated cognition.

Coordinating the AI Model Ecosystem

While Uni-1 forms the foundation, Luma Agents can also coordinate with leading external AI models when appropriate.

The system can route tasks to models such as:

• Ray3.14

• Veo 3

• Sora 2

• Kling 2.6

• Nano Banana Pro

• Seedream

• GPT Image 1.5

• ElevenLabs

Agents automatically select the most suitable model or capability for each step of a project while maintaining persistent context across all assets and iterations.

The result is a hybrid approach where a unified reasoning system orchestrates a broader AI ecosystem.

Built for Enterprise Creative Workflows

Unlike consumer AI generators, Luma Agents are designed for enterprise environments where compliance, intellectual property, and governance matter.

Enterprise safeguards built into the platform include:

• Full IP ownership retained by customers

• Automated content review to reduce copyright risk

• Documentation verifying human oversight in the creative process

• Mandatory human approval workflows before public release

• Cloud infrastructure with enterprise-grade security controls

These features are intended to address concerns that many large organizations still have about deploying generative AI in production environments.

The Bigger Shift: AI-Native Creative Production

Luma’s launch reflects a broader transformation happening across the creative industry.

Early generative AI tools focused primarily on producing single assets—an image, a paragraph, or a short video clip.

But as organizations adopt AI at scale, the bottleneck has shifted from generation to workflow orchestration.

Creative teams don’t just need AI that produces content. They need systems capable of:

• Managing projects across formats

• Maintaining context across iterations

• Coordinating multiple AI models

• Integrating into production pipelines

That’s the gap AI agents aim to fill.

If platforms like Luma succeed, the role of AI in creative industries could evolve from tool to collaborator—helping teams produce more content, more quickly, without sacrificing strategic control.

And for agencies and marketing teams operating in a world where demand for digital content keeps accelerating, that may prove to be the most valuable capability of all.

Get in touch with our MarTech Experts.

Unified commerce platform Cart.com has secured $180 million in growth equity financing, a move aimed at accelerating the company’s AI capabilities, software development, and nationwide fulfillment network.

The investment round is led by Springcoast Partners, with participation from existing backers including PayPal Ventures, Arsenal Growth Equity, Mercury Fund, and Oak HC/FT.

The new capital positions Cart.com to deepen its technology stack and expand operational infrastructure as brands increasingly seek integrated solutions that combine ecommerce software with physical logistics operations.

Building a Unified Commerce Operating System

Cart.com operates a commerce enablement platform designed to handle the entire lifecycle of digital retail—from storefront management and marketing tools to order fulfillment and supply chain logistics.

Brands and retailers including TOMS Shoes, PacSun, and Janie and Jack already use the platform to manage omnichannel commerce operations.

The company’s strategy focuses on integrating enterprise software, fulfillment infrastructure, and operational expertise into a single platform rather than offering standalone tools.

That unified approach reflects a growing demand among brands for technology platforms that can manage both digital commerce and physical logistics in one system.

“This investment will strengthen our balance sheet and provide us with the flexibility to accelerate our strategic priorities,” said Omair Tariq. “We’ve built a platform that combines commerce software with a scaled logistics network, and we’re just getting started.”

AI and Automation at the Center of Growth

A major focus for the new funding will be expanding Cart.com’s AI-driven capabilities.

The company plans to invest heavily in its commerce operating system, particularly in areas such as:

• Workflow automation for ecommerce operations

• Predictive analytics for inventory and demand planning

• Agentic AI systems capable of autonomously routing inventory

• Optimization tools to reduce shipping times and fulfillment costs

These AI capabilities aim to help brands manage increasingly complex supply chains and omnichannel distribution strategies.

For large retailers, the ability to automatically route inventory across warehouses and fulfillment centers could significantly reduce delivery times and operational costs.

Expanding the Fulfillment Network

In addition to software development, the funding will support expansion of Cart.com’s nationwide fulfillment infrastructure.

As ecommerce expectations continue to rise—particularly around fast delivery—brands increasingly rely on distributed logistics networks to meet customer demands.

Cart.com plans to invest in additional operational automation and infrastructure to support enterprise brands navigating these logistical challenges.

The company’s hybrid model—combining software with a physical fulfillment network—sets it apart from many commerce platforms that operate purely as technology providers.

Investor Confidence in the Commerce Infrastructure Model

For Springcoast Partners, the investment reflects growing confidence in platforms that unify commerce software and logistics.

“In an increasingly fragmented commerce landscape, Cart.com has differentiated itself by uniting enterprise software with physical logistics,” said Evan Nawrocki.

The firm believes Cart.com’s integrated model gives enterprise customers a measurable return on investment, particularly as brands look for more efficient ways to manage omnichannel commerce.

Leadership Expansion With Board Appointment

As part of the investment, Russell Klein will join Cart.com’s board of directors.

Klein brings extensive ecommerce experience. Prior to joining Springcoast, he served as Chief Commercial Officer at BigCommerce, helping scale the company from $30 million to more than $350 million in annual recurring revenue.

During his tenure, Klein also played a role in multiple financing rounds, the company’s mergers and acquisitions strategy, and its IPO.

“The team at Cart.com has demonstrated excellence in their ability to scale efficiently while continuing to innovate,” Klein said. “I’m excited to support the company as it expands its AI-driven capabilities and strengthens its position as a category-defining commerce platform.”

The Bigger Trend: Commerce Infrastructure Consolidation

Cart.com’s new funding reflects a broader shift happening across the ecommerce technology landscape.

As digital commerce grows more complex, brands increasingly prefer unified platforms that combine multiple operational layers:

• Ecommerce technology

• Inventory management

• Logistics and fulfillment

• Data analytics and AI optimization

Managing those capabilities through separate vendors can create operational complexity and fragmented data pipelines.

Platforms like Cart.com aim to solve that problem by delivering commerce infrastructure as an integrated system.

For enterprise brands juggling multiple sales channels—from direct-to-consumer storefronts to marketplaces and retail partners—that unified approach can significantly simplify operations.

What Comes Next

With the new funding secured, Cart.com plans to accelerate development of its AI-driven commerce operating system while expanding logistics infrastructure to support enterprise brands.

The company also signaled a focus on improving operational efficiency and moving toward sustainable profitability as it scales.

If Cart.com successfully executes its strategy, it could strengthen its position in a rapidly evolving category: platforms that combine commerce technology with the physical infrastructure required to deliver products to customers.

In an era where speed, efficiency, and omnichannel reach increasingly define retail success, that combination may prove to be one of the most valuable capabilities in modern commerce.

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Global advertising and media technology company Entravision is reshaping its U.S. leadership structure with a series of executive promotions aimed at accelerating revenue growth, expanding its Latino media footprint, and modernizing operations with digital and AI initiatives.

The company announced three key promotions across its U.S. media division:

• Maria Martinez-Guzman has been promoted to President of Entravision Media

• Eduardo Maytorena becomes President of Entravision Audio

• Winter Horton steps into the role of Chief Revenue Officer

All three executives will report directly to Michael Christenson as the company doubles down on audience growth, advertiser relationships, and operational modernization.

“These promotions align our leadership with our core objectives: serve our Latino audience and advertisers, lead with sales, and modernize our operations,” Christenson said in the announcement.

A New Leader for Entravision’s Video Business

As President of Entravision Media, Martinez-Guzman will oversee television programming, digital video initiatives, and national and local TV sales operations.

Her responsibilities include leading video content strategies across both traditional broadcast and streaming platforms—an increasingly important area as media companies shift toward digital distribution.

Martinez-Guzman brings extensive industry experience to the role. She began her career in Entravision’s McAllen office before spending more than two decades at Univision, where she most recently served as Executive Vice President of News.

Her return to Entravision signals the company’s intent to strengthen its video strategy across broadcast and streaming.

“Video has always been at the heart of my career,” Martinez-Guzman said. “It’s how we inform, tell stories, and build trust. I look forward to positioning Entravision as a leader in broadcast and streaming video.”

Audio Strategy Expands Under New Leadership

Meanwhile, Maytorena will take charge of Entravision’s radio and digital audio operations as President of Entravision Audio.

His role includes overseeing programming, network and national sales, and local market sales for radio-only markets.

Previously a Senior Vice President in Entravision’s Los Angeles market, Maytorena now steps into a larger strategic position focused on transforming the company’s audio business.

“I’m proud to help lead the next phase of growth,” Maytorena said. “We will change the audio game and transform it into a more integrated, dynamic platform.”

The move reflects a growing emphasis on digital audio formats—including streaming radio, podcasts, and connected-car listening—areas where advertisers increasingly allocate budgets.

Revenue Operations Get a Dedicated Leader

As Chief Revenue Officer, Horton will oversee sales across Entravision’s combined markets as well as sales operations and support functions across all regions.

Horton most recently served as a Senior Advisor to the CEO, helping develop Entravision’s evolving media strategy.

His background includes leadership roles at multiple media companies, including Liberman Broadcasting, the predecessor to Estrella Media, as well as Meruelo Media.

In his new role, Horton will focus on aligning the company’s media platforms—television, audio, and digital—to deliver integrated advertising opportunities.

“I’m thrilled to collaborate with an exceptional team as we bring the full strength of our media platforms to market,” Horton said.

Additional Leadership Changes Across the Company

Entravision also announced several other executive updates designed to strengthen operations, legal oversight, digital development, and AI strategy.

Key changes include:

• Mark Boelke will now serve as Chief Operating Officer in addition to his existing role as Chief Financial Officer.

• Jeff DeMartino has been promoted to Chief Legal Officer, expanding his responsibilities to include leading company partnerships.

• Jessica Martinez will serve as Executive Vice President of Digital Products and Operations.

• LeaAnna Hernandez becomes Executive Vice President of AI Strategy, reflecting the company’s growing focus on AI-powered media and advertising tools.

• Fred Roggin will serve as President of Entravision Digital.

Why the Leadership Shift Matters

Entravision’s leadership changes come as the company navigates a rapidly evolving media landscape.

The company has built a strong presence in Spanish-language broadcasting while expanding its reach into digital advertising technology, streaming platforms, and data-driven media solutions.

At the same time, brands increasingly seek targeted media channels that connect with multicultural audiences—particularly the growing Latino consumer market in the United States.

By restructuring leadership across video, audio, revenue, and digital operations, Entravision appears to be positioning itself to compete more aggressively across both traditional media and modern advertising technology ecosystems.

The addition of dedicated AI strategy leadership also signals that the company sees artificial intelligence as a core component of its future media operations.

For advertisers looking to reach Latino audiences across broadcast, digital, and audio platforms, Entravision’s evolving leadership structure could play a key role in shaping how those media opportunities are delivered in the coming years.

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