Global reach. Brighter discoveries.

Researchers connecting to GRAD from around the world

GRAD's community is growing across countries worldwide.

GRAD helps researchers collaborate, share knowledge and create impact beyond borders.

Global community
Meaningful collaborations
Real-world impact

Trusted by researchers worldwide

Join a growing community of global researchers

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Researchers

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Countries

Bigger impact together

Meet GRAD

Researchers everywhere. One research group.

Geospatial, remote sensing, AI and data analytics: people from around the world, growing ideas together.

The GRAD story in 10 seconds · tap the video to pause · sound is off until you turn it on

Inside the workspace

Your research. Guided, not replaced.

Write in a live LaTeX manuscript while your AI peer checks claims against the literature and flags what deserves a second look.

Urban heat islands · manuscript.tex

Live LaTeX 3 editing
  1. 1\section{Results}
  2. 2Land surface temperature (LST) from Landsat 8 TIRS
  3. 3rose by 2.4\,\textdegree C across built-up zones
  4. 4between 2014 and 2024~\cite{ref1}.
  5. 5
  6. 6\begin{equation}
  7. 7 NDVI = \frac{NIR - Red}{NIR + Red}
  8. 8\end{equation}
AI peer
Do other studies agree with the 2.4 °C rise?
Three recent papers report conflicting effect sizes (1.1–3.0 °C). The spread tracks the sensor: MODIS-based studies come in lower than Landsat ones.
Source 1 Source 2 Source 3
Suggestion: add a sensor-comparison note to Results.
ReviewDismiss

Our philosophy

A peer with deep knowledge — not a replacement

We built GRAD around one belief: the researcher does the research. AI's job is to widen what you can see, not to make the call for you.

You lead the investigation

Every research question, hypothesis, and conclusion is driven by you and your team. The platform organizes the work — it doesn't do the thinking for you.

AI is a peer, not autopilot

Your AI collaborator reads the literature, flags gaps, and suggests directions with the depth of a well-read colleague — you decide what to pursue.

Every claim stays grounded

Suggestions are traceable to sources and experiment data. Nothing enters your paper without a human reviewing and approving it first.

Features

Everything your research team needs, in one place

From first literature scan to a submitted paper, with your team and your AI peer working from the same shared context.

Visual knowledge graph

See how literature, datasets, experiments, and drafts connect, so the shape of the research is never lost in the details.

Master knowledge base

Ingest papers, datasets, and notes into one searchable, citation-grounded knowledge graph your whole team shares.

AI research copilot

Ask questions, get literature-grounded answers and next-step suggestions — always with sources attached, never a black box.

RunSync Launchpad

Launch it. Run it. Sync it. AI writes a ready-to-run notebook — run it on your own compute and sync results, metrics, and artifacts straight into the project record.

Live LaTeX authoring

Co-write papers in a real-time collaborative editor with LaTeX compilation, so drafts and PDFs stay in sync as you type.

Role-based review workflow

Domain leads approve work in their area, the project lead sees everything — so nothing ships without the right human sign-off.

How it works

How a project moves through GRAD

A simple flow that keeps humans deciding, and AI helping, at every stage.

  1. Ingest

    Bring in papers, datasets, and prior work. The platform builds your shared knowledge base automatically.

  2. Investigate

    Explore with your AI peer — ask questions, surface gaps, and map out hypotheses grounded in real sources.

  3. Experiment

    Run experiments on your own compute with the RunSync Launchpad and sync results back into the project for the team to review.

  4. Author & approve

    Draft together in the live editor, route sections through domain-lead review, and publish with confidence.

Step 01 of 04

Ingest

  • Upload PDFs, DOIs and datasets
  • Citations extracted and linked
  • One shared, searchable knowledge base

Built for how research teams actually work

A research lead sees the whole picture. Domain leads own their slice of the work — literature, data, experiments, or writing — and approve what enters the record. Every contribution is visible to the people who need to see it, and no one else.

Set up your team

Research Lead

Full visibility, final approval authority.

What they see

  • Every module, task and draft across the project
  • Approval queue from all domain leads
  • Team activity and contribution assessment

Do the research. Let your AI peer help you see further.

Bring your team, your literature, and your data — GRAD keeps it all connected while you stay in the driver's seat.