Ventura Growth, a Certified Service Partner of The Trade Desk, has rebranded as Mogl and launched three new business units aimed at tackling data fragmentation, retail media complexity, and international expansion.

Founded in 2022, the company has built its reputation helping independent agencies and growth brands access programmatic tools and training on The Trade Desk’s platform. With over 500 advertisers supported, Mogl’s shift signals broader ambitions.

The new divisions include:

• Mogl Data – a practice dedicated to modern marketing infrastructure, offering cloud architecture support, identity resolution, and real-time reporting across Snowflake, CDPs, and other platforms.

• Mogl Retail – services for brands navigating retail media networks, now the third-largest digital ad channel, with a focus on budget efficiency and cross-retailer performance.

• Mogl UK – a London-based arm providing localized access and support for European clients.

Mogl Growth, the company’s flagship programmatic media service, remains one of the largest partners in The Trade Desk’s Certified Service Partner program.

“Our goal isn’t just platform access—it’s helping marketers move faster, think smarter, and create more value,” said Marty Skotnicki, President and co-founder of Mogl.

Industry partners echoed the move. “Mogl has been instrumental in the rapid growth of our Certified Service Partner program,” said Matt Fogarty, GM of Channel Partnerships at The Trade Desk.

The rebrand positions Mogl as a scale-ready partner for independent agencies and challenger brands seeking more control over their advertising and data strategies.

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When it comes to marketing, words are cheap. Every brand claims authenticity, innovation, or customer-first values—but proving it is another story. Share One, an Austin-based startup, thinks it has the answer: verified video testimonials that audiences can actually trust.

The company just closed its Series A funding round, signaling fresh momentum for its platform built to capture, authenticate, and share genuine customer stories. In a digital landscape where AI-generated content and polished scripts often ring hollow, Share One’s model leans on what consumers increasingly crave—proof that feels human.

The Trust Gap in Marketing

Global ad spend is pushing past the trillion-dollar mark, yet marketers face a stubborn credibility crisis. Shiny campaigns no longer guarantee conversions, as audiences grow more skilled at spotting what’s staged. Share One’s pitch is simple: swap the corporate gloss for authentic, verifiable testimonials that buyers can believe.

Instead of quick-cut soundbites, the platform blends tech with human interviewers who coax real experiences out of customers. Each story is vetted for authenticity, creating a growing library of narratives brands can deploy across campaigns, sales decks, and digital channels.

As CEO Dan Lievens puts it: “Our goal isn’t just to record a video—it’s to capture a story someone else can see themselves in. When the story is real, it carries more weight than anything a brand could write on its own.”

Investors Bet on Authenticity

The new funding will help Share One expand its engineering muscle, refine editing workflows, and roll out advanced features to lower costs and accelerate testimonial turnaround. The aim: make verified video content as scalable as any other digital asset in a marketer’s toolkit.

That scalability could prove vital. The testimonial space is crowded with DIY apps and automated tools, but Share One is betting that its human-plus-tech hybrid model—interviewers for nuance, software for scale—offers a more credible middle ground between cheap tools and pricey production agencies.

What Share One Delivers

In just three years, the company has worked with hundreds of brands, from scrappy startups to large enterprises, helping them ditch hollow marketing claims for customer voices that resonate.

Its platform includes:

• Streamlined scheduling and customer outreach

• Interview prep for richer storytelling

• Professional production and editing aligned to brand tone

• Multi-channel “Social Share Pack™” distribution kits

• Compliance and verification baked in

It’s not just testimonial collection—it’s testimonial curation, with the polish of an agency and the credibility of lived experience.

Why It Matters

As marketing shifts toward authenticity-driven content, Share One’s approach speaks to a broader trend: user-generated trust as currency. Consumers may ignore a polished ad, but they’ll listen when a peer shares a verifiable story. With this Series A, Share One is positioning itself as the bridge between customer experience and brand credibility.

Whether it’s a growth-stage SaaS or a global enterprise, the platform promises something traditional campaigns can’t easily buy: trust that sticks.

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In an era when marketers are drowning in traffic data but struggling to turn clicks into customers, White Peak Marketing thinks it has the fix. The Reno-based agency will debut MaximizeOS™, a fully managed marketing service designed to convert more traffic into revenue, at the upcoming B2B Marketing Expo in Las Vegas (Oct. 15–16).

The service aims to help businesses move beyond the outdated “traffic-first” mindset and focus instead on what really matters: maximizing conversions, customer lifetime value, and ROI in a digital world increasingly shaped by AI.

MaximizeOS: Playing Offense in an AI-Driven Market

MaximizeOS isn’t just another marketing dashboard. White Peak bills it as an end-to-end managed service, engineered to:

• Personalize buyer journeys in real time

• Boost conversion rates and average order value

• Cut down time-to-purchase

• Extend customer lifetime value

The timing couldn’t be better. With ad costs climbing and generative AI eating into organic search traffic, marketers face mounting pressure to justify spend. MaximizeOS promises to help businesses squeeze more growth out of every click—without burning through budgets.

A Stage and a Statement

White Peak’s CEO, Tim Woda, will drive home the company’s message during his talk, “#ShiftHappens: Digital Marketing Has Changed. Play Offense While Others Panic,” on Oct. 15 at 1:15 PM in Theater 8.

Woda doesn’t mince words: “The digital marketing landscape has shifted, and most marketers haven’t. While advertising costs skyrocket and AI cannibalizes organic traffic, many businesses are chasing traffic instead of fixing what happens after the click. That’s a fatal mistake.”

His session will offer a blueprint for adapting—personalizing buyer journeys, targeting mid-funnel audiences with SEO, and using AI to create demand before prospects even know they need it.

Why It Matters

MaximizeOS underscores a larger trend in martech: moving from volume metrics (traffic, impressions) toward verified outcomes (conversions, revenue, lifetime value). Competitors like HubSpot, Salesforce, and Adobe have been rolling out AI-powered tools in similar directions, but White Peak’s positioning is more direct: hands-off for clients, all-in on ROI.

With its launch at the Expo, White Peak is betting that businesses are ready to stop panicking over AI-driven disruption and start using it to their advantage.

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B2B marketers are drowning in intent signals and SaaS dashboards, but confidence in pipeline delivery has never been shakier. DemandScience, a global player in performance marketing, is trying to fix that with the launch of Ionic and Labs, two offerings designed to puncture what it calls the “Marketing Data Mirage.”

That mirage? The false confidence created when marketing teams lean on dubious signals, scattered platforms, and content that doesn’t land—burning budget on activity that doesn’t actually convert.

A Unified System for Real Buyers

At the heart of this rollout is Central, DemandScience’s new intelligence and insights hub. Instead of marketers stitching together data vendors, orchestration platforms, and content syndicators, Central brings it all under one roof.

The system is anchored by three core components:

• Ionic: the intelligence and orchestration layer that blends verified buyer data, real-time behavior signals, and AI-driven orchestration into one closed-loop system. It’s fully transparent, showing where signals come from and how campaigns adapt in real time. Importantly, it’s embedded directly into every DemandScience program—no extra platform to buy.

• Labs: a services arm staffed with “demand scientists.” Labs combines human expertise, AI, and Ionic’s intelligence to run always-on campaigns across paid media, email, web, syndication, and events.

• Central: the hub where marketers monitor audiences, track performance, and tap AI-powered recommendations for their “next best move.”

Together, the trio aims to replace vague intent scores, cut through AI-fueled content fatigue, and collapse siloed orchestration into a streamlined cycle where each campaign improves on the last.

Industry Voices

“Marketers don’t need another intent score they can’t trust or another platform to manage,” said Derek Schoettle, CEO of DemandScience. “They need confidence that every signal represents a real buyer, that campaigns execute across channels without added complexity, and that content connects. Ionic and Labs deliver all three.”

That sentiment resonated with early users. Manoj Jasra, CMO at Emids, noted that too many teams are “chasing intent signals we can’t verify” while juggling rising complexity. The appeal of DemandScience’s system, he said, is that it simplifies the entire process: verified data in, meaningful growth out.

Why It Matters

The B2B marketing stack has grown bloated, with intent data vendors, orchestration tools, and content platforms fighting for budget. Yet pipeline confidence is at a low. By folding intelligence, services, and optimization into one system, DemandScience is positioning itself as an alternative to the patchwork approach dominated by players like Bombora, 6sense, and TechTarget.

If the system delivers on its promise—verified signals, better orchestration, and content that actually resonates—it could help marketers shift from chasing phantom intent to building predictable, compounding pipeline.

Ionic, Labs, and Central are available globally now.

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Retail media is booming—and so is the competition. With McKinsey projecting commerce media to claim 20% of global ad spend by next year, brands and retailers are scrambling to build their own high-margin ad networks. But data silos, clunky workflows, and legacy tech have slowed many enterprise efforts.

Enter GrowthLoop, the AI-driven marketing innovator that today unveiled its Compound Marketing Engine for Commerce Media Networks. The new solution promises to let enterprises finally put their vast stores of first-party data to work—fast, securely, and at scale.

The timing couldn’t be sharper. GrowthLoop has already landed Costco as a strategic partner to expand its retail media operations, signaling serious market traction.

Unlocking the First-Party Goldmine

“Enterprises sit on a goldmine of customer data in the cloud, but legacy systems keep it locked away,” said Chris O’Neill, CEO of GrowthLoop. “The future of commerce media belongs to enterprises that can instantly activate that data. With GrowthLoop, we’re unlocking it and putting AI directly into the hands of marketers.”

That’s the bet: empower marketers to move at the speed of advertising demand without endless engineering cycles. GrowthLoop’s AI agents build high-precision audience segments, generate campaign recommendations in natural language, and deliver real-time measurement—all while keeping data inside the enterprise’s cloud for compliance and security.

What’s Inside the Engine

The new commerce media solution sits on GrowthLoop’s composable architecture, meaning it plugs into data clouds like BigQuery, Snowflake, and Databricks with ease. Features include:

• Self-service audience building: Create hyper-granular segments in minutes, enriched with device IDs, purchase history, and household-level insights.

• Agentic AI support: Always-on intelligence suggests new audiences and brand segments to accelerate campaign setup.

• Multi-brand management: Role-based access and permissions for enterprises managing multiple networks under one roof.

• Ad-tech flexibility: Integrations with 70+ destinations, from onsite networks to DSPs and ID graphs, plus one-click “multi-export” deployment.

• LiveRamp onboarding: Boost match rates and extend advertiser reach across channels.

• On-demand measurement: Move from sluggish reporting to near real-time results in the cloud.

• Enterprise-grade security: SOC 2 Type II compliance, clean-room integrations, and full audit trails.

Why It Matters

Commerce media networks are the new cash cow for retailers, but building them has been messy. Traditional vendors like Criteo, The Trade Desk, and CitrusAd have carved out footholds, but many enterprises have struggled to operationalize their own data.

GrowthLoop’s pitch is that it combines compliance-grade governance with the speed and intelligence of AI, creating a scalable path for retailers to monetize audiences and for advertisers to access high-intent shoppers.

For an industry sprinting toward a trillion-dollar ad future, that’s no small promise.

GrowthLoop’s Compound Marketing Engine for Commerce Media Networks is available now.

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When law firms talk about “digital transformation,” it often sounds like consultant-speak. But in the case of UK-based Howes Percival, the move is concrete: the award-winning firm is doubling down on its partnership with NetDocuments, the cloud-first document management system (DMS) widely regarded as a leader in the legal tech space.

The expanded agreement is part of a broader business transformation strategy that leans heavily on workflow automation and secure collaboration. For a firm recognized for its “world-class” workplace engagement, it’s not just about keeping up with digital change—it’s about freeing up lawyers to do more actual lawyering.

From Three Hours to 30 Minutes

The firm plans to apply NetDocuments’ document automation across its legal templates and processes, promising speed gains that matter in the trenches. For example, drafting power of attorney documents—a task that previously took three hours—will soon take just 30 minutes. In the world of billable hours, that’s not just an efficiency boost; it’s a competitive edge.

And it’s not all behind the firewall. With NetDocuments’ integration into Microsoft Teams, client and third-party collaboration gets a security-first upgrade—crucial in an era where breaches and compliance headaches haunt law firms.

A Tighter Tech Stack, Not a Bigger One

Lee Killner, IT Director at Howes Percival, summed up the firm’s approach bluntly: “Too often, IT teams default to buying new software, creating complexity and distracting from client service.” Instead, the firm is paring back to a tighter set of core apps, with NetDocuments at the center.

That mindset—fewer, smarter tools rather than endless add-ons—is gaining traction across industries. It reflects a broader trend in legal tech, where the focus has shifted from adopting flashy solutions to making core systems smarter and more user-friendly.

Why This Matters

NetDocuments isn’t the only player in the DMS space—rivals like iManage and Worldox have long vied for dominance—but its cloud-first, automation-driven positioning seems well-timed. As more firms confront client demands for faster turnaround and cost transparency, shaving hours off routine tasks isn’t just operational efficiency; it’s survival strategy.

Kerri Dearing, VP of International Business at NetDocuments, put it more diplomatically: “By driving innovation through the apps legal professionals use every day, law firms can be confident they are empowering their teams to do their best work.” Translation: this is as much about retention and morale as it is about efficiency.

The Bigger Picture

For Howes Percival, with more than 250 partners and fee earners on the roster, scaling automation could mark a pivotal moment in its modernization journey. But the ripple effects extend beyond one firm. If document drafting can be slashed from hours to minutes without compromising compliance, it resets expectations for clients—and puts pressure on competitors still relying on manual-heavy workflows.

The broader takeaway: legal tech’s “boring” tools—document management systems, automation engines, collaboration integrations—are quickly becoming the real battleground for differentiation. And in that fight, NetDocuments just secured another loyal ally.

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The creator economy may be booming, but brand partnerships can be a minefield. From mismatched values to reputational risks, one wrong collaboration can undo years of careful marketing. That’s the challenge Later—the platform powering creator commerce—says it’s tackling with its newly launched AI-Powered Brand Suitability Insights.

Billed as an enterprise-ready solution, the tool helps marketers vet creators with more nuance than the usual red-flag checks. Instead of stopping at risk detection, Later promises a dual view: spotting potential pitfalls while highlighting which creators are most likely to deliver performance and ROI.

Beyond “Brand Safety”

Most existing brand safety tools focus on negatives—flagging profanity, controversial topics, or conflicts of interest. Later’s pitch is that this approach only tells half the story. By layering AI-driven analysis over publicly available creator data, the platform produces a comprehensive report that combines risk assessment with performance potential.

Marketers receive:

• Executive Summary: Key risk levels, metrics, and a recommendation.

• Brand Suitability Score: A straightforward fit rating.

• Risk Matrix: Category-by-category scoring across 12 risk areas, from misinformation to brand conflicts.

• Audience Intelligence: Insights into follower quality and engagement.

• Performance Analytics: Benchmarks across platforms.

• Transparent Data Sources: Clear sourcing so teams know exactly where the numbers come from.

The idea: make creator partnerships both safer and smarter.

Context: Why This Matters Now

As influencer marketing grows more sophisticated, so do the risks. Brands are increasingly wary of controversies spilling over from creators’ personal content. At the same time, pressure for measurable ROI is rising—especially in an era where ad budgets face scrutiny.

By fusing risk and performance metrics, Later is positioning its platform as a way to future-proof brand investments. As CEO Scott Sutton put it, “Marketers shouldn’t have to choose between protecting their brand and achieving performance outcomes.”

The Competitive Angle

Later isn’t alone in this space. Companies like CreatorIQ, Captiv8, and Tagger have all rolled out tools for vetting influencers, often with a heavy emphasis on brand safety. But Later’s differentiator is its dual-sided scoring system: protect brand equity while also spotlighting creators most likely to drive growth.

Chief Customer Officer Phoebe Maclachlan summed up the appeal: the feature “reduces the risks of mismatched collaborations while unlocking the upside of the right ones.” In other words, it’s not just about avoiding disasters—it’s about finding the partnerships that actually move the needle.

The Bottom Line

Later’s AI-powered Brand Suitability Insights reflects a broader trend: the shift from blunt risk-avoidance to precision brand-creator matching. For marketers, that means less guesswork, fewer PR headaches, and a clearer case for ROI. And in a noisy creator economy, clarity may be the most valuable insight of all.

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AI has already transformed how marketers generate content, but what if the AI could actually think like a marketer? That’s the bold promise behind Markethinking, a new reasoning model from Marketeam.ai that bills itself as the world’s first autonomous intelligence engine purpose-built for marketing.

Rather than just spitting out copy on command, Markethinking is designed to research, analyze, strategize, and execute marketing campaigns with minimal human intervention. In other words, it’s not just a writing tool—it’s a full-blown marketing strategist in code.

Moving Beyond Prompt-Driven AI

Most large language models are built for general-purpose tasks. Markethinking flips the script with a narrow but deep focus: marketing. The 8-billion-parameter model, post-trained on Qwen3 with more than 10 billion tokens of curated marketing data, is engineered to work natively with marketing platforms, CRM systems, and SaaS tools.

This specialization allows it to:

• Continuously monitor competitors, sentiment, and campaign performance.

• Brainstorm strategic opportunities in real time.

• Draft and execute multi-channel campaigns.

• Optimize results dynamically, all while keeping brand voice and customer psychology in check.

That’s a tall order, but if it works as advertised, it could redefine what “autonomous marketing” really means.

Outperforming the Giants

Marketeam.ai claims Markethinking outpaces leading models—including DeepSeek, Qwen, Gemma, and LLaMA—on domain-specific benchmarks. Internal tests reportedly showed stronger brand alignment, more consistent tone, and higher factual reliability. Even under budget constraints, the model delivered higher engagement and conversion rates compared to rivals.

CTO and co-founder Sahar Millis framed the difference bluntly: “The industry has been focused on content generation. We built an LLM that has brand understanding and context engineering baked into its reasoning.”

Open-Source, But With Boundaries

In a notable move, Marketeam.ai has made a research checkpoint available on Hugging Face, where it’s already been downloaded over 10,000 times. Developers are plugging it into their own marketing workflows, testing the boundaries of autonomous brand intelligence.

But there are caveats. The model was purpose-built for marketing—step outside that lane, and performance falls off quickly. Unlike GPT-4 or Gemini, you won’t be using this to code apps or solve math proofs. It’s laser-focused on campaign strategy, planning, and execution.

A Continuous Intelligence Loop

The architecture is designed for integration: feeding data from CRMs, analytics platforms, and market signals into a continuous intelligence loop. This lets agents not just monitor the landscape but adjust campaigns on the fly—something most human teams struggle to do at scale.

VP of R&D Coby Benveniste emphasized the technical leap: “Traditional models struggle with real-time marketing data. We’ve built reasoning chains that can track multiple tasks while keeping context coherent.”

Why It Matters

Marketing AI is maturing fast. First came generic content tools, then audience insights platforms. With Markethinking, Marketeam.ai is trying to carve out a new category: reasoning models purpose-built for marketing ecosystems.

If the approach sticks, it could push the industry away from AI “assistants” toward truly autonomous agents—ones that don’t just follow prompts but proactively run campaigns. Competitors like Jasper and Copy.ai will likely need to respond, either by deepening their domain intelligence or risk looking like glorified text editors.

Looking Ahead

Commercial implementations of Markethinking are set to roll out in Q3 and Q4 2025 as the core of Marketeam.ai’s Integrated Marketing Environment (IME). For marketers under pressure to do more with leaner teams and tighter budgets, an autonomous agent that can think strategically could be a game-changer—or at least a powerful copilot.

The catch? Trust. Brands will need confidence that an autonomous AI can not only execute campaigns but also uphold brand equity, manage risks, and make judgment calls marketers usually guard closely.

If Marketeam.ai can clear that hurdle, “autonomous marketing intelligence” may become the next big buzzword—and this time, maybe one worth believing.

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