What is emerging globally?
Which technological and innovation trends are gaining momentum across the world — before they become headlines?
How we turn the noise of global research into actionable foresight.
The Trend Radar combines AI-driven analysis of scientific literature with structured expert curation to identify, evaluate and visualise the technologies that will shape tomorrow and to translate them into strategic recommendations for today.
The problem we solve
Three questions every strategy team has to answer.
The Trend Radar is built around the questions that decide whether an organisation leads or follows.
What is relevant for us?
Out of that global picture, which trends actually matter for our context, our markets and our capabilities?
How do we act early?
How can we use these trends now to stay competitive, defend market position, or build a lasting edge ahead of time?
Our approach
AI-driven trend forecasting, grounded in expert judgement.
We continuously analyse a large corpus of scientific literature and innovation signals using modern natural language processing and machine learning. The system surfaces emerging themes; our domain experts then evaluate, contextualise and translate them into strategic recommendations.
Machine reading at scale
Transformer-based language models read and represent thousands of research abstracts, capturing the meaning of text rather than just keywords. This lets the system spot themes that traditional keyword search misses entirely.
Unsupervised theme discovery
Modern topic-modelling techniques cluster semantically similar documents into coherent themes, tracking how each theme evolves over time. The result is a living map of where research attention is concentrating.
Strategic evaluation
Discovered themes are assessed against multiple readiness dimensions — including technological maturity — and connected to industry-specific implications. This is where data becomes decision-relevant.
Expert curation
A human-in-the-loop layer ensures that what reaches the radar is not only statistically significant but also strategically meaningful. Our researchers validate, prune and contextualise every trend we publish.
A note on the inner workings. The specific models, parameters, prompts and pipeline configurations behind the Trend Radar are proprietary to Fraunhofer ISI’s Joint Innovation Hub. The page above gives a faithful high-level overview; the underlying methodology is documented internally and partially in the peer-reviewed publications listed below.
From data to insight
A five-stage pipeline.
Each stage feeds the next and is continuously refined as new data arrives.
Stage 01
Source & ingest
Curated scientific and innovation sources are continuously ingested into the platform.
Stage 02
Clean & represent
Text is cleaned and converted into rich semantic representations suitable for downstream analysis.
Stage 03
Discover themes
Unsupervised models cluster the corpus into coherent, interpretable themes.
Stage 04
Evaluate & rank
Themes are assessed for momentum, readiness and strategic relevance to the focus domain.
Stage 05
Curate & visualise
Experts validate the output and publish trends to the radar with detailed analyses and recommendations.
What the radar delivers
Foresight you can put to work.
Interactive trend radar
A visual map of emerging trends positioned by maturity and impact, with explorable connections between themes.
Detailed trend analyses
Deep-dive briefs on each trend — signals, evidence, key actors, and the “so what” for your domain.
Strategic recommendations
Industry-specific implications and recommended actions tailored to your strategic context.
Transparency & sources
Citations and source links throughout, so every claim on the radar can be traced back to evidence.
Research foundation
Selected publications.
The methodology is grounded in peer-reviewed research conducted at Fraunhofer ISI and with academic partners.
Multi-agent Retrieval-Augmented Generation for Enhancing Answer Generation and Knowledge Retrieval
Predicting Tech Readiness through Bibliometric Analysis using Unsupervised Machine Learning
Artificial Intelligence Driven Trend Forecasting: Integrating BERT Topic Modelling and Generative Artificial Intelligence for Semantic Insights
Want to see it on your own data?
Talk to the Joint Innovation Hub team about applying the Trend Radar methodology to your strategic focus area.