An AI research extension for knowledge discovery
We are building SENION as an AI research extension for the AI assistant you already use.
Explore connections across sources and time, develop new questions and take ideas further. SENION is designed to bring an independently observed knowledge landscape into your work with your chosen AI.
COMING SOON
01 / THE KNOWLEDGE ECOSYSTEM
Research develops. Technologies take shape. Institutions respond. Across the internet, ideas meet, diverge and reappear in different contexts.
A paper tells one part of a story. Its relationships to other work, the timing of a technical advance, or a gap between discussion and action opens another. This changing knowledge ecosystem is the starting point for SENION.
What is knowledge discovery? ↗
EXPLORE THE CONCEPT
A technology advisor asks how AI can inspect manufactured parts on site. A research finding, a software release and a factory constraint take the investigation in an unexpected direction.
01 / A PROMISING OBSERVATION
A research note describes defect detection from a small set of examples. An advisor sees a starting point for inspecting short production runs, where labelled defects are scarce.
“The method learns from a small set of defect examples. The study uses fixed lighting; changing production conditions were not tested.”
The research observation and its test boundaries, preserved by EUCLID and made accessible through SENION.
Where would learning from few examples be valuable — and what else must work before we can use it?
02 / EUCLID
EUCLID is the structural observatory beneath SENION. It observes defined parts of the external information world and preserves source states, relationships and their development over time — independently of your current question.
What persists? What drifts apart? Where do new constellations form? EUCLID keeps these structural observations available, with their sources, time boundaries and visible gaps. Their meaning remains open to investigation.
EUCLID describes observed structure. SENION makes it accessible. Meaning and judgment belong to the people and AI doing the investigation.
03 / SENION
We are building SENION to bring an independently observed knowledge landscape into the AI workspace you already use.
What is an AI research extension? ↗
Supported assistants, available capabilities and setup requirements will be published after validation.
Let’s compare the research conditions with the constraints on the factory floor.
THREE OBSERVATIONS, ONE NEW QUESTION
Few examples. Fixed lighting.
Local execution is possible.
Frequent changes. Little time to recalibrate.
A shared inspection station could be worth exploring. What would we need to test before taking that idea further?
04 / HUMAN + AI
You bring experience, curiosity and a sense of what matters. Your chosen AI helps you compare observations, explore explanations and work through possibilities.
We are building SENION to give that collaboration more to work with: an observed knowledge landscape beyond your conversation, where relationships across sources and time can become starting points for your own ideas.
See a familiar problem through an unfamiliar connection.
A research finding, a practical limitation and a development in another field may look unrelated when viewed separately. Explore them together with your AI, tracing the available observations and how they relate over time.
Your experience can make a connection relevant in a way no source states explicitly — opening a new question, a possible application or a direction you had not considered.
Find out what makes a promising connection worth pursuing.
Work with your AI to compare explanations, examine the underlying observations and identify what would support or weaken an idea. Bring your practical knowledge into the investigation: which conditions matter, what has been overlooked, and where might an analogy break down?
The result may be a stronger hypothesis, a useful limit — or a better question than the one you started with.
Give an emerging idea something to grow from.
Develop a possibility into a concept you can explain, a hypothesis you can investigate or a next step you can test. Return to the observations behind it as new evidence appears, and explore how a change in one assumption opens a different approach.
The aim is not simply to retain what you already know. It is to build on it — turning inspiration into work that can lead to new understanding, practical applications and innovation.
05 / RESONANCE DOMAINS
Professional research needs subject-specific context. We call these perspectives resonance domains: observations of what is being built, enacted or tested in a field. These are the first domains shaping our product vision.
What is being discussed?
What is actually happening?
What changes elsewhere — or does not?
Where is attention turning into actual adoption? Bring research into relation with repositories, packages, patents and adoption signals. Investigate where technical activity supports a new direction — and where enthusiasm runs ahead of use.
When does a policy debate become an operational reality? Follow proposals, consultations, enactment and enforcement. Examine how public discussion relates to the actual regulatory process and the responses it sets in motion.
Which promising findings inspire work that holds up? Connect publications and citations with trials, funding and replication. Explore where an idea attracts follow-up research, where results diverge and what remains untested.
Each domain brings its own evidence and professional responsibility for interpretation. Shared observations connect the inquiry; they do not make EUCLID or SENION the authority on what a field should conclude.
THE RESEARCH BEHIND SENION
A finding in one field. A difficulty in another. A question that brings them together. Seen in relation, they may reveal a possibility that none makes visible alone.
How does cross-domain innovation work? ↗
EUCLID explores the internet as an evolving knowledge ecosystem. Signals gather momentum or fade. Relationships take shape, persist or dissolve. Some patterns become established; others disappear before we understand what they might mean.
Our research looks beyond individual contributions to what happens between them — across sources, perspectives and time. A disagreement can reveal an overlooked assumption. A quiet observation can become significant in a new context. What matters to a future question may not yet look important today.
EUCLID provides the observational foundation for this work: a defined view of the sources it follows, their structural relationships and changes over time. We are building SENION so you and your chosen AI can explore that landscape — and discover questions, connections and possibilities beyond your starting point.
Our approach is to cultivate, not prescribe: enough structure to follow a connection, enough openness to see where it leads.
To create the conditions in which understanding can deepen, ideas can take shape and innovation can begin — without deciding in advance what must emerge.
LET’S TALK
For strategists, researchers, innovators, consultants and policy professionals already working deeply with AI: which developments matter to your work, and which connections are still hard to investigate?
Share an ambitious research question or a field you know well. Let’s explore what a wider observation foundation would make possible for your work.
FOR INVESTORS
We welcome conversations with venture capital investors, business angels and others interested in the future of human + AI discovery.
If you share our interest in opening new paths from knowledge to innovation, let’s talk about the vision behind EUCLID and SENION, our direction and how you could help shape what comes next.