About Envisioning

We did not set out to change foresight, but rather to improve our own work.

We have long believed in combining data visualization with a methodological approach to research, and have built foresight, innovation scanning and signal collection tools with all types of organizations.

When large language models became capable of structured research tasks, we didn't bolt AI onto an old process. We rebuilt every step around multi-model orchestration, semantic data structures, and continuous delivery. The result is higher-quality intelligence produced faster, with outputs that behave like infrastructure: reusable, generative systems teams can keep running, rather than one-off documents.

Traditional foresight projects often:

• move slowly relative to strategy timelines;
• cost too much to run continuously;
• deliver insights that are hard to operationalize;
• leave teams with reports instead of durable research assets.

Envisioning exists to close that gap by turning foresight into an ongoing capability: structured sensing, synthesis, and decision support that can be refreshed as the world changes, not just for the largest institutions. We want research to generate options and strategic agency, not just reports.

• Multi-model orchestration: We run parallel model workflows and track convergence and divergence across outputs to improve robustness and reduce single-model bias;
• Semantic structure first: Signals, metrics, and categories and evidence are captured as reusable data, so research compounds over time and can be recombined for new questions;
• Centaur operating model: AI handles scale, speed, and synthesis; humans provide framing, interpretation, and strategic judgment;
• Continuous delivery: Intelligence is delivered as an evolving system with updates, traceability, and reusability, designed for teams that need the latest view, not a snapshot;
• Global perspective: We work across Europe, Latin America, and the Middle East through direct engagements and partner-led delivery.

AI changes the economics of research. It makes scale, speed, and synthesis cheap enough to run continuously. That shifts human work toward what matters most: framing the right questions, interpreting results, and making decisions with context.

We also believe research should be open where possible. Much of what we produce is public, and our tools are designed to be reused, extended, and shared across organizations and partners. In that sense, our work is aimed at a more democratic, increasingly post-scarcity model of intelligence distribution, in line with our manifesto commitments.

Michell Zappa (Founder & CEO) has led technology foresight programs since 2010, advising organizations and governments globally.

• Thomaz Rezende, Partner and Head of Design;
• Fabio Andrade, Partner and Head of Development;
• Daiane Cavalheiro, Operations Manager;
• Rodrigo Turra, Lead Researcher.

Envisioning operates as an interdisciplinary team spanning product, research, facilitation, and design, supported by a growing global network of certified delivery partners.