Collaborative research management for the computational sciences

Accelerate your research.

Track what's working and isn't with shareable searchable artifacts documenting decisions, data, code, and analysis.

Available to all academic institutions.
Plan
Run
Evaluate
Publish
Trusted by ETH Zurich
The problem

Research forgets the journey.

Researchers publish carefully crafted narratives of successful results. In an agent-mediated world the problem is exacerbated: the lessons learned along the way are completely illegible to agents and other researchers, even within the same research lab.

Build institutional memory that outlasts any one researcher.

Metric ● Status quo ● Methodic
Provenance
Every result traces back to the exact inputs, code, and configuration that produced it.
Reconstructed from memory Recorded by construction
Institutional memory
Every experiment's design, lineage, and outcome is recorded — including the attempts that didn't work.
Spreadsheets, docs, wikis, chat One searchable graph
Onboarding
New collaborators start from everything the group has already established.
Months Days
How it works

Go from idea to shared knowledge.

01
Plan
Frame the question. Record the hypothesis, the inputs, and how the result will be judged.
02
Run
Launch on your machine, your cluster, or managed compute. Code, config, and environment are captured as it runs.
03
Evaluate
Compare against the baseline and the work it descends from. Regressions are recorded as plainly as gains.
04
Publish
Commit the result to the shared graph, artifacts and lineage attached. The next question starts from it.
Experiment graph

Every experiment becomes a node that informs future directions.

Immutable
Once an experiment is committed, its design is frozen. Once it completes, its outputs (inputs, hyperparameters, metrics, and artifacts) are locked.
Graph lineage
Each experiment records the prior work it descends from. Improvements over a baseline are explicit, not narrated after the fact.
Searchable
Find every prior result that touched the same dataset, method, or metric — across teams, across years.
Auditable
Trace any figure or claim in a write-up back through the analysis and the data that produced it.
Run lineage · turbulence-closure 4 runs · 1 regression
r-08c1
BASELINE · 2026-02-14 · 128³ grid
Reference closure, uncalibrated
eval/rollout-skill: 0.612 · parents: ∅
r-12a4
CALIBRATE · 2026-03-02 · parents: r-08c1
Calibrated on the flume corpus (v3)
eval/rollout-skill: 0.741 (+0.129) · referenced by 6 downstream studies
r-19f7
ABLATE · 2026-04-09 · parents: r-12a4
Subgrid stress term removed
eval/rollout-skill: 0.689 (−0.052) — regression vs parent.
r-1bd2
CALIBRATE · 2026-04-21 · parents: r-12a4
Recalibrated across Reynolds regimes
eval/rollout-skill: 0.778 (+0.037) · promoted to group reference.
Example workflow — illustrative until a real pilot is published.
Security & compliance

Built for secure collaboration.

ACCESS
Role-based access control
Org-wide RBAC, IdP-mapped granular roles.
ENCRYPTION
Encrypted at rest and in transit
AES-256 / TLS 1.3, per-tenant keys.
AUDIT
Fully audited actions
Append-only audit log of every action and configuration change.
PROVENANCE
Lineage and auditing
Know the provenance of every artifact and who took each action — agent or human.
FAQ

Frequently asked.

Trackers log metrics from a run. Methodic records the research around it — the hypothesis, the inputs, the code, the artifacts, and the reasoning — so a result can be traced end to end and reused by someone who was not there.

Put your research on the record.