Huge news coming your way!

We are thrilled to share that our startup is one of the few selected for the ALPHA program at WebSummit Rio 2025!

The Web Summit’s ALPHA program offers early-stage startups opportunities for growth, visibility and networking. Selected startups can showcase their products, connect with investors, strategic partners and industry leaders, in addition to attend exclusive talks and events.

We will have an exclusive exhibition space and participate in all in-event activities: the PITCH competition, Startup Showcase, Masterclasses, Roundtables, Mentor Hours and Investor meetings.

Being at WebSummit is about collaborating, learning and, above all, driving our mission to turn business ambitions into tangible achievements and unlimited growth. This is a major milestone in our journey and an incredible opportunity to connect with the most innovative minds in the tech world, as we showcase our vision for the future of AI in fueling exponential business expansion.

We are ready to be the transformative force in the market and can’t wait to share this with the international community.

Visit us at our exclusive exhibition space and discover how we are shaping the future of AI. Don’t miss the chance to be part of this journey. See you at WebSummit Rio!

Read more in our page on LinkedIn.

In today’s landscape, where personalization and artificial intelligence (AI) are critical for business success, understanding user behavior is essential. In the race to provide more convenience, efficiency and opportunities, three key dimensions shape behavioral modeling: characteristics, actions and time. Together, they enable precise recommendations and personalized experiences, driving value for both customers and companies. The impact goes beyond user satisfaction—it directly influences revenue growth, engagement, retention and brand strength.

1. Characteristics: Defining the Individual and Items

The first dimension encompasses user attributes and the features of the items they interact with. In e-commerce, this includes purchase history, brand or category preferences and product attributes such as price and popularity. In streaming services, favorite genres or preferred artists play a crucial role in content recommendations.

This combination allows AI systems to identify patterns and provide suggestions beyond the obvious. For example, a customer purchasing a smartphone may receive recommendations for complementary accessories like cases or chargers. This level of personalization not only increases average order value but also enhances brand perception by demonstrating an understanding of the customer’s needs.

2. Actions: What the Individual Does

The second dimension involves user actions, which reflect their interests and intentions. Browsing behavior, clicks, purchases and cart abandonment provide valuable insights into what a user is looking for. On content platforms, metrics such as time spent on an article or skipping a movie help refine recommendations in real-time.

In B2B, for instance, a pharmacy’s purchase history can indicate a need to recommend flu medicine during colder seasons, aligning with consumer demand. By proactively responding to these insights, businesses not only boost engagement but also strengthen customer loyalty by becoming trusted partners that understand their clients’ needs.

3. Time: When Behavior Occurs

The third dimension, time, is crucial for maintaining the relevance of recommendations. Recent behaviors carry more weight and AI systems must prioritize them. Additionally, factors like seasonality and consumption cycles influence purchasing decisions. In e-commerce, key periods such as Christmas or seasonal promotions require quick adjustments to highlight high-demand products.

In streaming services, timing also plays a role. Relaxing playlists at night or lighthearted movies on weekends are examples of how temporal context enhances user experience. Delivering recommendations at the right moment increases engagement and retention—critical factors for revenue growth.

Integrating the Three Dimensions

When combined, these three dimensions create highly personalized recommendations. In a B2B marketplace, for example, understanding customer characteristics (purchase patterns), actions (products bought) and time (replenishment cycles) enables businesses to suggest complementary products or seasonal offers. This approach not only boosts sales volume but also strengthens customer relationships by demonstrating a deep understanding of their business needs.

The Role of AI and Continuous Learning

AI plays a fundamental role in dynamically integrating these dimensions. Machine learning systems continuously refine recommendations based on user interactions, anticipating future needs. This capability allows businesses not only to meet expectations but also to surprise users with exploratory suggestions, such as niche content or products outside their usual preferences.

This continuous adaptation and innovation provide a competitive edge, enhancing customer loyalty and positioning the brand as a leader in personalization. Furthermore, by delivering unique experiences, businesses can increase customer lifetime value (LTV), driving long-term revenue growth.

We’re thrilled to announce our acceptance into the Google Cloud for Startups Program!

This incredible opportunity includes an initial USD 25,000 in Google Cloud credits, allowing us to further develop and scale our platform. Through this program, we’ll gain access to Google’s extensive resources — from technical support to co-marketing and networking within the Google Cloud Startup Community.

This partnership is a powerful step forward, as we continue to scale our platform, invest in strategic new partnerships, and, above all, enhance the results our clients achieve through our solutions. These results are the most critical element of our journey, and this collaboration ensures that they grow even stronger and more impactful. With Google Cloud by our side, we’re excited to build even greater success stories, driving robust and sustainable growth.

Data is relentless: if it does not generate revenue, it inevitably incurs costs.

Data and artificial intelligence (AI) are transforming business operations, creating tangible opportunities for growth and efficiency. This article explains how to practically extract value from data, regardless of the maturity of your strategy.

BALANCING GROWTH AND SUSTAINABILITY

According to McKinsey & Company, companies aiming for accelerated growth must develop a robust data strategy. While the process of designing and implementing this strategy may be complex, it can be built incrementally, capturing value in small steps.

To develop a data strategy that keeps your business competitive, focus on these four pillars:

1. Data capture and integration
Efficiently integrating operational data from channels, products, and external sources is essential. If your company or department is not doing this well, start with small pilot projects to test new data capture and integration methods. These initial steps allow for constant innovation and quick adaptation to market changes, fostering incremental growth.

“If you are collecting data that is not immediately used to capture business value, stop. That data might be useless! Data that does not feed into analytics, predictive models, or key decision-support indicators is garbage. Do not waste time managing and updating data that serves no purpose.”

2. Actionable insights
Convert data into actionable insights, integrating them into both operational and strategic decisions. Start with specific analyses that deliver immediate impact, gradually expanding into a continuous process that spans the entire organization. This ensures data-driven decisions are constantly improving processes.

“What customer behaviors did you identify last month, and how have they impacted your predictive models, KPIs, or internal processes? Start with a small initiative, learn from it, build an isolated process, and then scale it up.”

3. Strategic partnerships
Collaborating with technology and business partners enriches your data ecosystem. Establish partnerships in stages, starting with smaller collaborations and gradually expanding your data utilization capacity. This enhances the value of collected data and improves service offerings.

“Which partners are helping you identify growth opportunities for your business? SaaS solutions offer low-friction experimentation and rapid impact realization. If you are not leveraging specialized partners to move quickly, you are likely giving your competitors a head start.”

4. Operational efficiency
Foster a culture of efficiency that values resource optimization and adaptability. Encourage a collaborative and continuous learning work environment from the start. Focus on results-driven management and creating an atmosphere that encourages productive behavior and drives success. People’s behaviors are shaped by the results they achieve and the environment in which they operate.

“Stuck in the hire-or-build dilemma? Do both! Work with partners to validate gains, and then internalize only what is essential. Many companies try to build expert teams without knowing which applications will deliver results, and without the appeal to attract and retain talent. Be strategic: validate first, internalize later, and only what makes sense.”