Tofu, the AI-powered platform for B2B marketing teams, has successfully raised $12 million in Series A funding. Led by SignalFire, with participation from HubSpot Ventures and other investors, this funding will further accelerate Tofu’s mission to simplify marketing workflows and enhance campaign performance for GTM (go-to-market) teams. Tofu’s platform consolidates campaign execution across multiple channels, helping teams scale personalized, omni-channel campaigns with greater efficiency.

Developments

• Series A Funding Success
  Tofu has raised $12 million in Series A funding, led by SignalFire and supported by HubSpot Ventures, Tau Ventures, Correlation Ventures, and a range of other investors. This funding will help drive the platform's growth and innovation.

• Solving the Martech Tool Overload
  Tofu’s unified platform addresses a significant pain point for marketing teams: the overwhelming number of martech tools. By consolidating campaign execution, Tofu allows GTM teams to manage their campaigns without juggling multiple point solutions.

• Impressive Growth and Adoption
  Over the past year, Tofu has seen exceptional growth, with a 12x revenue increase and a 36x surge in content generated. The platform has gained traction among both startups and enterprises like RingCentral, Check Point, and Bluecore, highlighting its scalability.

• Efficiency and Engagement Boost
  Companies using Tofu’s platform report substantial improvements in marketing performance. The platform enables faster campaign creation, with teams experiencing up to a 75% reduction in creation time. Engagement rates across channels have risen by 230%, showing Tofu’s impact on marketing efficiency and results.

• Platform Capabilities for Diverse GTM Teams
  Tofu’s solution is designed for various marketing functions, including demand generation, content marketing, lifecycle marketing, event marketing, digital marketing, and outbound SDR campaigns. It caters to the specific needs of different GTM teams, making it a versatile tool for diverse marketing strategies.

With its Series A funding and strong growth trajectory, Tofu is well-positioned to revolutionize B2B marketing. By providing a unified platform that consolidates omni-channel campaigns, Tofu helps marketing teams reduce complexity, increase efficiency, and drive higher engagement and conversion rates.

Zefr has expanded its pre-impression content avoidance controls on Meta, offering advertisers more refined control over content adjacencies while ensuring large-scale reach. This expansion is part of Zefr Max, providing global availability and offering advertisers complete transparency on where their ads are served. The new solution enhances brand safety and performance across Meta's platforms.

Features and Benefits

• Building on Meta's Existing Controls
  This new feature enhances Meta's first-party Inventory Filters, which help maintain brand suitability on the platform. Zefr’s pre-impression content avoidance solution offers advertisers the ability to create custom blocklists and implement real-time optimizations, further improving their campaign’s contextual relevance.

• How the Solution Works
  Zefr utilizes AI combined with a human-in-the-loop process to classify content for blocking before an ad is served, and offers post-bid transparency. Advertisers can customize exclusions by risk level and create dynamic blocklists based on real-time events or specific brand concerns.

• Transparency and Performance
  Advertisers can access real-time transparency dashboards, offering clear visibility into performance metrics and blocked content. Zefr’s AI decision-making process is explainable, ensuring transparency while continuously refining content exclusions to align with campaign objectives.

• Future-Proof Brand Suitability
  Zefr’s commitment to ongoing optimization ensures that as social media evolves, brands are equipped with up-to-date tools for effective content adjacencies. This future-proof approach helps advertisers maintain brand safety and relevance as platform dynamics shift.

With this expanded capability, Zefr offers advertisers a more powerful and transparent way to control content adjacencies on Meta. By providing customizable blocklists and real-time optimization, Zefr helps brands safeguard their messaging while maintaining scale and performance.

AdLib Media Group, a leading provider of DSP-agnostic media buying solutions, has announced the appointment of Will Batson as Head of Growth. This strategic hire highlights AdLib’s commitment to accelerating its growth and broadening the adoption of its omni-channel programmatic platform.

Features and Benefits

• Will Batson's Appointment
  Will Batson brings years of experience and proven success in the AdTech industry, having previously served as cofounder and CRO of Hudson MX. His ability to drive significant growth and manage large-scale operations will be crucial in advancing AdLib’s market presence. His leadership will help shape the company's go-to-market strategies and client base expansion.

• AdLib’s Platform
  The AdLib platform simplifies and automates cross-channel media buying for advertisers. It operates with a lean, scalable model that allows marketers to launch campaigns across multiple DSPs and channels quickly and efficiently. With features such as unified campaign management, real-time optimization, and dynamic budget allocation, AdLib enables marketers to maximize results and streamline operations.

• Batson’s Role and Impact
  As Head of Growth, Batson will focus on expanding AdLib's client base and enhancing its growth strategies, with the goal of helping advertisers drive superior outcomes while adapting to the rapidly evolving digital advertising space. His expertise is expected to play a key role in shaping AdLib’s future success.

With Will Batson at the helm of growth, AdLib is poised for significant expansion. The combination of his industry expertise and the company’s innovative platform will strengthen AdLib’s position as a leader in simplifying programmatic advertising, helping advertisers stay ahead in the competitive digital landscape.

Monetate, a leader in personalized ecommerce experiences, has appointed Steve Maher as its new Chief Executive Officer. With Maher's leadership and extensive background in AI-driven customer experience platforms, Monetate aims to accelerate its transformation into AI-powered search, discovery, and dynamic merchandising solutions.

Features and Benefits

• Steve Maher’s Leadership
  Steve Maher brings over 20 years of enterprise technology leadership to Monetate, having previously led organizations through significant growth stages at both growth-stage companies and Fortune 500 firms. His expertise in AI-driven customer experiences aligns perfectly with Monetate's vision to revolutionize personalized customer journeys using AI and natural language processing (NLP).

• Monetate’s Evolution
  Under Maher’s leadership, Monetate is focused on deepening its AI-driven tools, especially in Personalized Search, to help brands better understand and engage with customers. The company has already made significant strides with the launch of its AI-powered Site Search and Category Pages products, which use machine learning, NLP, and large language models (LLMs) to interpret shopper intent and curate tailored product recommendations.

• Monetate’s Impact
  Monetate’s solutions are designed to optimize customer journeys by curating relevant product collections and enhancing product discovery, ultimately improving conversion rates and revenue. Maher’s leadership will expand the company’s influence across new markets and verticals, driving deeper investments in AI-powered personalization.

With Steve Maher at the helm, Monetate is positioned for continued growth and innovation. By leveraging AI and advanced technologies, the company is committed to helping ecommerce brands deliver intuitive, personalized customer experiences that drive business results.

GumGum, a leader in contextual-first technology for digital advertising, has launched the Digital Advertising Pulse Check, a new initiative aimed at tracking consumer sentiment towards data-heavy, identity-targeted ads. The initiative is based on a survey of over 1,500 North American consumers and reveals increasing discomfort with ads that rely heavily on personal data.

Findings from the Pulse Check

• Offensive Identity Ads
  The survey found that nearly half of respondents (49%) have been targeted by ads that felt stereotypical or offensive. Among those, 31% described the ads as "clueless rather than malicious," while 18% felt they "completely missed the mark." Only 27% found the ads appropriately tailored.

• Cookies Are Creepy
  When asked about their feelings regarding cookies (used for tracking online behavior), 56% of consumers reacted negatively. A third of them (34%) felt like they were being "peeked over" or "watched every step," reflecting unease with the pervasive tracking practices.

• Violation of Boundaries in Identity Ads
  Ads that targeted sensitive topics like health, finances, or relationships led to strong negative reactions, with 62% of respondents expressing disapproval. 21% described feeling "violated," while 41% found these ads "annoying."

• Consumer Confusion and Frustration
  20% of respondents reported encountering poorly targeted ads every day, with 51% saying they experience such frustration occasionally. Only 9% felt the ads they saw were always on point.

• If Identity Ads Were a Person
  Consumers largely viewed identity-targeted ads unfavorably when asked to describe them as people. 43% compared them to a "nosy neighbor," and 26% described them as "the stalker hiding in the bushes." Only 14% viewed them as "the life of the party."

The Digital Advertising Pulse Check underscores the growing discomfort consumers have with data-heavy, identity-targeted ads. GumGum’s initiative aims to help brands understand the fine line between relevance and intrusion, suggesting that other forms of advertising may offer more comfortable and effective ways to engage audiences.

Data Preprocessing and Normalization

Data quality plays a crucial role in model effectiveness, and HOLO begins by applying normalization techniques to preprocess behavioral data. Normalization scales the data to a specific range, typically between 0 and 1 or -1 and 1, ensuring that features with different dimensions and numerical ranges can be compared and analyzed on the same scale. This step eliminates the dimensional influence between features, improving model training efficiency and laying a solid foundation for feature extraction.

Stacked Sparse Autoencoders and DeepSeek Model Optimization

Once data is preprocessed, it is input into HOLO’s stacked sparse autoencoder model. This deep learning architecture, composed of multiple autoencoder layers, extracts features at varying levels of complexity. By integrating the DeepSeek model, HOLO dynamically adjusts sparsity constraints to ensure the learned features are sparse, thus capturing the most important data patterns while reducing redundant features.

Layered Training and Feature Representation

HOLO optimizes the stacked sparse autoencoder using a greedy, layer-wise training approach. In this method, the model first trains lower layers to learn basic features and uses the output from one layer as input for the next, progressively extracting deeper and more complex features. The sparsity constraint ensures that only a small number of neurons are activated in each layer, enabling more compact and effective feature representation.

Denoising and Dropout Techniques

HOLO’s training strategy also includes denoising and the application of Dropout. Denoising involves adding random noise to input data during training, challenging the model to reconstruct the original data and thereby improving robustness in noisy real-world environments. Dropout, on the other hand, randomly drops neurons during training to prevent overfitting, ensuring that the model generalizes better when encountering unseen data.

Distributed Computing and Efficient Training

The DeepSeek model also leverages a distributed computing framework, allowing training tasks to be parallelized across multiple computational nodes. This approach accelerates training time, improving overall efficiency. By incorporating pretraining and fine-tuning strategies, the DeepSeek model ensures faster convergence and enhanced model performance.HOLO’s use of the DeepSeek model to optimize stacked sparse autoencoders injects new energy into the field of anomaly detection. With improvements in training efficiency, robustness, and feature extraction, the model offers a powerful solution for real-world applications that demand high accuracy and resilience in noisy environments.

In today’s fast-paced digital world, businesses need smarter ways to connect with their audience online. World Digital, a leader in digital marketing solutions, is transforming how brands engage with customers through innovative, data-driven strategies designed to maximize social media success.

Revolutionizing Brand Engagement

As social media platforms evolve, traditional marketing strategies are no longer sufficient. World Digital is leading the charge with a new approach that blends real-time data insights, audience behavior tracking, and personalized content strategies to help businesses enhance brand visibility and engagement. The company's focus on data-driven engagement ensures that brands can connect with their target audience more effectively than ever before.

Helping Businesses Build Stronger Connections

World Digital goes beyond just content posting—they focus on fostering meaningful interactions. By analyzing customer engagement patterns, the company creates tailored marketing campaigns that not only increase user participation but also boost brand loyalty and deliver measurable results. “Success in digital marketing is no longer about guesswork,” said a spokesperson from World Digital. “Our strategies help businesses make informed decisions, ensuring their message reaches the right audience at the right time.”

What Makes World Digital’s Strategy Different?

World Digital's approach stands out because it focuses on the following key elements:

• Smart Content Creation: Crafting customized posts based on audience preferences to drive higher engagement.
• Advanced Audience Insights: Using real-time data to determine what works and continuously refine campaigns.
• Optimized Ad Campaigns: Ensuring content reaches the right people at the right time for maximum impact.
• Performance Tracking & Adjustments: Constantly analyzing campaign performance and fine-tuning strategies for better results.

Adapting to a Digital-First World

In a digital-first world, staying ahead of trends is crucial for brands to remain competitive. World Digital’s strategies are designed to help businesses do more than just keep up—they enable brands to stand out. By leveraging AI-powered insights and creative content strategies, businesses can increase customer engagement, improve visibility, and drive real growth. In a time when more brands are shifting their focus online, adopting data-driven techniques is no longer optional—it’s a necessity.

World Digital is making it easier for brands to navigate the complexities of digital marketing. Through smarter, data-driven engagement strategies, the company helps businesses make informed decisions and achieve long-term success in the ever-evolving digital landscape.

Icertis, the global leader in AI-powered contract intelligence, has announced the integration of its contract intelligence platform with DeepSeek R1, a key milestone in its OmniModel™ strategy. This integration is designed to offer businesses more flexibility in leveraging AI models to solve complex contracting challenges while optimizing both outcomes and costs.

Transforming Contracting with AI Integration

By integrating DeepSeek’s sophisticated AI algorithms into the Icertis platform, enterprises can enhance contract performance and decision-making. This integration empowers organizations to gain deeper insights into their contract data, streamline operations, mitigate risks, and optimize revenue recovery. It provides greater cost control over AI implementations, ensuring that businesses can confidently navigate the rapidly evolving AI landscape.

The Icertis OmniModel™ Strategy

The integration of DeepSeek R1 reflects Icertis’ commitment to providing its customers with the freedom to choose the best AI models for their contracting needs. Sudarshan Chitre, Senior Vice President of Artificial Intelligence at Icertis, emphasized the importance of adaptability in AI platforms for large enterprises: “Our integration with DeepSeek exemplifies our OmniModel strategy, helping customers capitalize on the latest advancements in AI while ensuring long-term value and scalability in their contract intelligence efforts.”

Leading the Future of Contracting with AI

Icertis continues to push the boundaries of AI innovation in enterprise contracting. The company was the first to introduce a genAI-powered Copilot for enterprise contracting and is now focused on the future of AI agents and agentic workflows. Icertis aims to redefine contracts as strategic assets for growth, positioning businesses to take full advantage of AI-driven insights.

Fostering Strategic AI Partnerships

The partnership with DeepSeek, along with strategic collaborations with companies like Harvey, demonstrates Icertis’ dedication to driving AI-powered transformation. By leveraging emerging AI technologies, Icertis enables enterprises to gain competitive advantages and maximize their AI investment. As AI spending is expected to reach $337 billion by 2025, Icertis is well-positioned to lead the charge in AI-powered contract intelligence.

Optimizing Business Relationships

Icertis’ platform, combined with DeepSeek’s AI capabilities, helps businesses harness the full potential of their contracts. This integration allows enterprises to optimize commercial agreements, improve margins, and gain insights into every business transaction, ultimately increasing operational efficiency and revenue.

With its OmniModel strategy, Icertis is reshaping how businesses approach contract intelligence, providing them with the tools to streamline operations and maximize the value of every business relationship. By integrating with DeepSeek, Icertis strengthens its position as a leader in AI-driven contracting solutions, offering enterprises the future-proof flexibility needed to stay competitive.