Data & Analytics

Accelerating AI with modern data and analytics platforms

We modernize data platforms and apply generative AI and agents to turn decisions into competitive advantage.

Challenges

The challenges that most hold back data evolution

  1. Modernizing the data platform

    to support decisions and scale Analytics and AI at lower cost.

  2. Democratizing data and AI

    speeding up time-to-insight across the whole company.

  3. Evolving toward data products

    moving from one-off analyses to continuous delivery.

  4. Applying Advanced Analytics and AI

    with use cases that generate real business value.

  5. Governing data with confidence

    to enable AI at scale, with security and compliance.

How we work

Our approach to Data & Analytics with AI

We combine strategy, data, engineering and AI to drive continuous evolution and real business impact, with more than 300 data and AI specialists.

  • Think Data Driven

    • Strategy

      Data & AI Strategy

      Maturity assessment, governance diagnosis and a strategic roadmap to structure data and AI at scale.

  • Organize, govern and democratize data

    • Platform

      Data Modern Engineering & AI Platforms

      Modernization of data architectures and cloud platforms with continuous engineering squads.

    • Governance

      AI Governance & Trust

      Data and AI governance, quality, compliance, cataloging and security for regulatory compliance at scale.

  • Create value and use insights

    • Intelligence

      Analytics & Decision Intelligence

      Data products, executive dashboards, ML and analytical AI that turn data into business decisions.

    • Experience

      Hyperpersonalization

      Customer intelligence, advanced segmentation, CDP and smart journeys driven by data and AI.

    • Agentic

      AI & Agents

      Generative AI and autonomous agents, from strategy to MLOps and AI lifecycle governance.

Architecture · Our vision

Data platform as the foundation that enables AI

  1. Generative Layer / UI Applications

    Where value meets the user

    The final interface where generative AI takes shape: chatbots, portals, mobile and enterprise integrations, enabling new models of interaction with clients and employees.

  2. Agentic Platform Layer

    The layer that runs intelligence

    Operationalizes intelligent tasks end to end: agent orchestration, systems integration, information and business-rule validation, with human oversight.

  3. AI Governance Layer (GRC)

    Security, trust and accountability

    Policies, controls and mechanisms that ensure applications are secure, scalable and aligned with ethical and regulatory values: compliance, privacy, risk management and human oversight.

  4. Foundational Models

    The architecture's adaptable brain

    Foundational LLMs, open-source or proprietary, for reasoning, language understanding and content generation. The model choice defines cost, accuracy and fit for sensitive data.

  5. Lakehouse (Data Foundation)

    The source of truth that feeds AI

    Ensures AI operates on clean, reliable and well-structured data: ingestion, integration, quality, governance and real-time or batch pipelines. Without robust data, models degrade and produce inconsistent responses.

Hyperpersonalization Hub

AI & Analytics

  • Building predictive models for recommendations
  • Dynamic segmentation and real-time personalization
  • Automated A/B testing and optimization algorithms
  • Performance dashboards and reports
  • Web Analytics
  • Customer 360
  • Models/Segmentation

Engineering and development

  • Personalization implementation on site and app
  • Integrations between Salesforce and Data Lake
  • APIs for data activation and syncing
  • Secure data collection and management, compliant with LGPD
  • Tagging/Web Funnel
  • Site/App/Channel Dev.
  • Google GA4/Amplitude

Strategic design

  • User research and customer journey
  • Data-driven persona creation
  • Definition of flows and personalization strategies
  • Audience Analysis
  • Digital Marketing/SEO
  • Personalization Use Cases

Growth marketing

  • Creating and running hyperpersonalized campaigns
  • Conversion funnel optimization based on behavioral data
  • Using AI to create and test dynamic creatives
  • Personalization in media buying and smart remarketing
  • Marketing Automation
  • A/B Testing
  • Journey Builder

CRM & Salesforce

  • Advanced audience segmentation
  • Campaign automation and customer journeys
  • Message personalization
  • Engagement monitoring and flow optimization
  • CDP/DMP
  • Orchestration (Salesforce Data Cloud / Marketing Engagement / Personalization)

End-to-end personalization

  • AI & Analytics. Predictive models, dynamic segmentation and automated testing.

  • Engineering and development. Personalization on site and app, integrations and LGPD-compliant APIs.

  • Strategic design. Research, personas and data-driven personalization flows.

  • Growth marketing. Hyperpersonalized campaigns, optimized funnels and smart media.

  • CRM & Salesforce. Audience segmentation, automated journeys and engagement.

Data and AI partner ecosystem

See partnerships
  • AWS
  • Salesforce
  • Databricks
  • Microsoft
  • Google Cloud

Ready to turn data into decisions?

Talk to a specialist