The Domain Researcher's Journey

Geologists have data.
And six months from now, a paper.

A biologist, a physician, a geologist, a psychologist, a humanities researcher. They walk in with a hard drive full of legacy data and walk out with a clear mapping of their data and methods to AI, concrete AI/ML implementation proposals, a structured project, and EU alignment by design.

DR

Domain Researcher

Researcher · Postdoc · Professor · PI
I have years of data — no time, no AI know-how.
01Reactivation

Chat intake → One-Pager

The agent asks the right scoping questions for your data, your domain and your goal. Risk and legal bases are processed inside the EU AI Act + GDPR framework from the first turn.

IntakeChat · multimodal
One-PagerRisk-cleared brief
02Structured scope

Project Plaza → Collaboration Match

Your One-Pager is visible to verified AI Researchers in the Project Plaza. They apply at your tiers (research collaboration, MSc, BSc, classroom). You review and accept the match — the Project Room opens.

Project PlazaOne-Pager visible to AIR
TiersResearch · MSc · BSc · Classroom
03Publish

Project Room → Publication

The collaboration unfolds in the Project Room — a shared workspace with downloadable audit trail. Output: a paper, a tool, a methodology.

Project RoomShared workspace
Audit logDPA-ready download
The promise to Domain Researchers

Reactivate, Publish, Secure.

Your data — already collected, often archived — and legacy methods that can be made faster and more precise, reactivated and published in record time, under European data governance.

01 — Reactivation

Dormant data and legacy methodologies become published science.

Dormant data on hard drives. Slow methodologies in lab notebooks. The intake agent reads both — your dataset and your domain expertise — and surfaces what AI can amplify. Archive becomes asset. Manual protocol becomes AI-augmented method.

Erysimum case — 32-marker manual protocol becomes a 5-minute on-device AI-powered pipeline.
02 — Publish

From dataset and method to a structured project. In 10 minutes.

One conversation produces a Technical One-Pager: scope, your methodology mapped to AI counterparts, risk classification, citations, and a portfolio across teaching tiers — research, MSc, BSc, classroom.

Multimodal intake · plain scientific language · zero ML jargon required from you.
03 — EU Data Governance

European alignment from the first conversation — not bolted on.

EU AI Act risk classification, GDPR-by-design, EU data residency, zero retention on LLM processing. EU alignment is the substrate, not a checkbox at the end.

Built in — every One-Pager carries risk class, citations and a GDPR audit trail.
“Domain researchers hold years of carefully collected data and legacy methodologies — slow, manual, often imprecise. Today’s ML and AI tools can reactivate those datasets and turn legacy methods into faster, more precise ones — closing a stronger scientific cycle. <brand/> AI Science Hub is the channel that makes it possible, with EU data governance and security by design.”
— Cristobal Bragagnolo, Founder · UGR / OPIT
The Domain Researcher Magic Moment

A consultancy-grade intake.
In 10 minutes.

An AI Consultancy Agent in one chat. From your photos, CSVs and answers, it elaborates a Technical One-Pager when you approve the methods. Accessible, multilingual, multimodal.

01

Multimodal & multilingual

Drop a photo, a CSV or a paragraph in Spanish, English, Italian, French or German. The agent grounds proposals in ground-truth data.

02

Methods across the spectrum

Classical statistics, standard ML, frontier disruptive options. The agent proposes, you approve, modify or reject — in plain language.

03

EU Act-Align checked live

An EU Act + GDPR engine over EUR-Lex returns risk classification with article-level citations before any method enters the One-Pager.

scheria.eu/intake
Live
Type your reply…
ONE-PAGER Projects

A structured One-Pager. Every project. Every time.

The output isn't a chat log — it's a publishable One-Pager Project. Created with the Domain Researcher, ready for the AI Researcher.

SCH-0273·Computer Vision·Plant phenotyping

On-device CNN for automated landmark detection in Erysimum morphometrics

A dataset of 32,000 landmarks over images of Erysimum flowers, manually annotated in 32 morphometric points around the calyx. The proposed method replaces a 3-day manual annotation pipeline with a 5-minute on-device CNN, enabling field-side morphometric work for ecologists.

Data type
RGB flower images · 32,000 landmarks (32 points / image)
Method direction
Lightweight on-device CNN
Domain
Ecology · Geometric morphometrics
Researcher
John Doe
Expected output
Q1 publication + open-source toolkit
Personal data
None · plant imagery only
Teaching-tier portfolio
Research collaborationOpen
MSc thesisOpen
BSc thesisOpen
Classroom exerciseOpen
EU AI Act · Limited risk

No personal data · GDPR-by-design. Downloadable audit trail.

Picked up by
PhD candidates
Research collaboration
Picked up by
MSc thesis students
MSc · EU partner universities
Picked up by
BSc thesis students
BSc · EU partner universities
Picked up by
Classroom cohorts
Classroom tier
Trust Pillars

European Data Governance. By design.

Trust is not a section in our terms of service. It is the foundation every conversation, every match, every export sits on.

EU data residency

Your data does not leave the European Union — at rest, in motion, or in transit through model inference.

Zero retention on LLM processing

All LLM and embedding providers operate under no-train, no-retain agreements. Disclosed on the first turn of every intake conversation.

EU AI Act · Limited risk

Scheria itself is classified as limited-risk under Article 50. Each One-Pager carries its own classification with article-level citations queried in real time from EUR-Lex.

Auditable by design

SSO-ready for university IDP integration. Per-project audit log, downloadable, ready for institutional DPA review.

Scheria - AI Science Hub