MARKETING AGENTS

From Manual Marketing to AI-Driven Growth

We partnered with a global brand to replace slow, fragmented workflows with an AI platform that analyzes engagement in real time, predicts performance, and unlocks faster, smarter campaign execution across markets.

Background

We built an AI platform to help brands analyze real-time engagement, measure influence, and optimize campaigns. Using natural language processing and predictive analytics, the tool drives deeper insights and stronger ROI.

Challenge

A global brand’s marketing team was bogged down in repetitive, low-value tasks, spending hours reviewing reports, building plans from historical data, and coordinating influencers across 12 countries, 4 currencies, and 5 platforms. This fragmented process slowed execution and blocked strategic focus.

Solution

To solve the operational bottlenecks and unlock scale, we designed a fully automated AI-driven operating layer that centralized data, replaced manual planning, and coordinated global execution in real time.

What we did:

Standardized data across all markets

AI agents to analyze reports and generate forward-looking plans

Communication agents to engage suppliers and talent via email, Instagram, TikTok, and WhatsApp

Automated campaign briefs with minimal human input

Technologies

To power intelligent planning, prediction, and communication at scale, we combined advanced AI models with cloud-native infrastructure and real-time integrations.

NLP for influencer communications, briefs, and content

Predictive analytics (Python, TensorFlow, scikit-learn) to forecast budgets and outcomes

Multi-agent frameworks (LangChain, custom orchestration) for planning and communication

Cloud pipelines (AWS Lambda, BigQuery) to unify inputs across 12 markets and 5 platforms

Conversational AI with WhatsApp Business API, Instagram Graph API, and TikTok integrations

Computer monitor displaying a dashboard with system performance graphs, active alerts, and data validation checks, with a glowing security lock icon overlay.

Impact

The shift from manual execution to an AI-powered operating model delivered immediate, measurable improvements across strategy, productivity, and cost efficiency.

Accuracy

Campaigns moved from instinct to data-driven strategy

Efficiency

Each team member saved 15 hours weekly for higher-value work

Cost savings

Acquisition costs dropped 12.7% through smarter targeting

Questions & Answers

Strong decisions start with clarity. These Q&As give you a quick understanding of how we work, what to expect, and how we help you succeed with AI.

Why do I need a data foundation before investing in AI?

AI relies entirely on the quality of your data. Without consistent, clean, and connected data, AI models produce unreliable outputs. A data foundation ensures your data is accurate, trustworthy, and structured in a way that supports scalable AI.

How long does it take to build a data foundation?

Timelines vary depending on your current maturity, number of data sources, and governance needs. Most organisations see a functional foundation in 6–12 weeks, with continuous improvement over time.

Do we need a cloud data warehouse to get started?

Not always, but it’s strongly recommended. Cloud platforms simplify integrations, improve scalability, and lower operational costs. We work with your existing tools if needed, but a modern cloud warehouse unlocks far more potential.

What does “data governance” actually include?

Governance covers everything from ownership and access control to data quality rules, cataloging, lineage, and compliance. It ensures your data stays reliable, auditable, and secure — essential for any AI system.

How do you connect all our existing data sources?

We assess each system, map its structure, and build automated pipelines that clean, transform, and centralise your data. This eliminates manual extraction and creates a single, consistent source of truth across the organisation.

Let’s talk about your AI use case

Have a business challenge in mind? We’ll help you assess feasibility, define the right approach, and build a clear path to execution.