We started in 2010 mapping emerging technology: radars, timelines and scanning tools for companies, governments and multilateral organizations, more than 200 projects in over 25 countries. The method is published and most of the research is open.
When language models got good enough to do structured research, we rebuilt every step around them and turned the method into Signals, a platform our clients run themselves.
Over sixteen years, similar research produced different results in different organizations. The difference was rarely the technology or the information. It was whether the institution could notice the change, agree on what it meant, decide, test a response, and keep what worked.
Why can some institutions perceive change, make sense of it, coordinate around it, experiment and adapt, while others with the same information cannot? We call that adaptive capacity and break it into seven dimensions: sensing, sensemaking, decision, coordination, experimentation, learning and scaling.
The work has three parts. Signals and our open research map what is emerging. Capability benchmarks measure how well a country or an organization can respond. Our services strengthen the dimensions that come out weak. Evidence from each part feeds the model.
Where models agree, a signal is probably solid. Where they disagree, something may be genuinely new. One model's answer is one opinion, and we treat it that way.
Signals, metrics, categories, and sources are captured in a structure you can query later. That is why a question asked in March can be answered again in September without starting over.
The machine handles scale and speed. People frame the question, read the result, and decide what it means. Neither half works alone.
What you get is a system that updates, not a document that ages. Traceable back to sources, and built for teams who need the current view rather than last quarter's.
Europe, Latin America, and the Middle East, through direct engagements and certified partners who deliver in their own regions and languages.
AI makes scanning, synthesis and prototyping cheap enough to run continuously. Intelligence becomes abundant. The constraint moves to the institution: its ability to turn what it knows into coordinated action.
Research should be open. Most of what we produce is public, and partners and clients reuse our tools. Foresight has been expensive and therefore rationed. Our manifesto commits us to changing that.
Michell Zappa (Founder & CEO) has led technology foresight programs since 2010, advising organizations and governments globally.
A small team covering product, research, facilitation, and design, working alongside a network of certified delivery partners around the world.
