Technology & SoftwareAgentic AIPublic CloudGoogle CloudVertex AI Agent BuilderAgent Development Kit (ADK)Imagen

Supermetrics: Helping Marketers Redefine Efficiency with AI-Powered Data Analysis

Supermetrics · Finland

Supermetrics, a Finland-based marketing intelligence platform serving 15,000+ customers across 132 countries, built an AI agent on Google Cloud using Vertex AI Agent Builder and the Agent Development Kit (ADK) that autonomously manages data connections, fixes pipeline errors, and analyzes campaign performance in real time, suggesting new creative options using Imagen. The agent automates the weekly marketing reporting cycle that previously took performance marketers up to four hours, reclaiming over 15 hours per month per marketer for strategy and creative testing. The system uses a central AI agent that interprets natural language requests and delegates tasks to sub-agents, and stores 'core memories' of user preferences for personalized context.

Overview

Supermetrics, a Finland-based marketing intelligence platform serving 15,000+ customers across 132 countries, built an AI agent on Google Cloud using Vertex AI Agent Builder and the Agent Development Kit (ADK) that autonomously manages data connections, fixes pipeline errors, and analyzes campaign performance in real time, suggesting new creative options using Imagen. The agent automates the weekly marketing reporting cycle that previously took performance marketers up to four hours, reclaiming over 15 hours per month per marketer for strategy and creative testing. The system uses a central AI agent that interprets natural language requests and delegates tasks to sub-agents, and stores 'core memories' of user preferences for personalized context.

This entry has 13 published fields tied to exact passages in an immutable source capture.

Inspect the highlighted source

The challenge

Marketers face a paradox of having more data than ever but less time and fewer resources to analyze it; marketing data has grown more than 230% since 2020, yet more than half of marketers admit they can't analyze it thoroughly, resulting in missed insights, slower decisions and growing pressure to deliver results with limited budgets. Supermetrics' own performance marketers spent up to four hours every week manually pulling data, formatting slides, and hunting for the root cause of performance dips.

The solution

Supermetrics built an AI agent on Google Cloud, powered by Vertex AI Agent Builder and the Agent Development Kit (ADK), that autonomously manages data connections, fixes pipeline errors, and analyzes campaign performance in real time, and can suggest new creative options using Imagen. A central AI agent interprets natural language requests and delegates tasks to sub-agents, such as one that queries advertising data and another that analyzes it and surfaces insights; the system stores 'core memories' of each user's preferences, roles, and data needs to build personal context.

Agentic AIGenerative AINatural Language Processing

Reported business value

The AI agent automates the entire weekly marketing reporting cycle, reclaiming over 15 hours per month per marketer for strategy and creative testing, and helps Supermetrics scale to serve more than a million users with clean, actionable data and minimal manual effort. Google Cloud reports the system was 3x faster to build agents with ADK compared to other industry frameworks, with automated error detection and fixes in data pipelines and continuous performance improvement as the system learns and optimizes.

Related entries

Other technology & software entries in the register.

All entries
Technology & SoftwareLarge Language ModelsPublic Cloud

Domyn builds Colosseum 355B, a sovereign AI foundation model, using NVIDIA DGX Cloud

Domyn (formerly iGenius), an Italian AI company serving highly regulated sectors such as financial services and public administration, used NVIDIA DGX Cloud with over 3,000 NVIDIA H100 GPUs to continue-pretrain Colosseum 355B, a 355-billion-parameter foundation LLM. Within one week Domyn had access to the dedicated infrastructure, and within two months completed continued pretraining, achieving 82.04% accuracy on the MMLU benchmark. The model powers Domyn's business intelligence agent, Crystal, a sovereign AI solution deployed on private infrastructure.

96/100HighDomynPrimary source
Technology & SoftwareRecommendation & PersonalizationUnknown

Strava's Athlete Intelligence Translates Workout Data into Simple and Personalized Insights

Strava launched Athlete Intelligence, an AI-powered feature available as a public beta to subscribers, which analyzes and interprets workout data across pace, heart rate, elevation, power, and Relative Effort into simple, personalized insights and guidance. The feature spots 30-day performance trends, detects milestones such as fastest pace or longest distance, and offers tailored feedback for each activity, drawing on more than 10 billion activity uploads on Strava.

88/100HighStravaPrimary source
Technology & SoftwareMachine LearningPublic Cloud

Fifth Dimension unlocks insights and intelligence with Google Cloud

Fifth Dimension, founded in 2023, provides an AI platform combining machine learning, predictive analytics and natural language processing to uncover hidden patterns in real estate data, processing over 1TB of data per month by 2025. Facing scalability and cost problems with its original infrastructure, the company adopted Google Cloud, building its ML stack on Vertex AI (running Google Cloud Gemini and Anthropic Claude models), plus Cloud SQL, Cloud Run and Pub/Sub. This scaled processing capacity 50x to handle document-processing surges, supported 6x global client growth across multiple regions, and decreased infrastructure costs by 30% through serverless architecture. Model deployment time dropped from weeks to days, platform engagement tripled in 2025, and annual recurring revenue grew 6x in the same year.

96/100HighFifth DimensionPrimary source
Technology & SoftwareRetrieval-Augmented GenerationUnknown

Spotlight: Qodo Innovates Efficient Code Search with NVIDIA DGX

Qodo, a multi-agent code integrity platform, built its AI agents on retrieval-augmented generation powered by a state-of-the-art code embedding model trained on NVIDIA DGX. Qodo fine-tuned two embedding models, Qodo-Embed-1-1.5B and Qodo-Embed-1-7B (based on Qwen), achieving state-of-the-art accuracy on the Hugging Face MTEB CoIR leaderboard in their size categories. In a collaboration with NVIDIA, Qodo's code indexer, RAG retriever, and embedding model were substituted into NVIDIA's internal RAG solution (Genie) for searching private code repositories, integrated into NVIDIA's internal Slack system, yielding more detailed and accurate responses to technical questions from expert C++ developers than the original pipeline, evaluated using Ragas-generated synthetic questions against RTXDI, RTXGI and RTXPT SDK repositories.

92/100HighQodoPrimary source

Was this helpful?

Your feedback helps us improve our use case database