Infrastructure for reproducible, benchmarkable quantitative research.
LargeQuant provides a durable system for scientific projects, experiments, datasets, models, execution, reproducibility, benchmark publication and institution-linked provenance.
Scientific output should survive beyond the notebook or individual project.
Research organisations accumulate experiments, datasets, model states, simulation outputs and publications across many teams. Without a durable evidence layer, the connection between a claim and the conditions that produced it can be difficult to reconstruct. LargeQuant gives quantitative research a persistent programme and provenance system.
High-value quantitative workflows.
Reproducible computational research
Bind model protocols, datasets, software identity and outputs into reproducibility packs.
Experiment and observation management
Maintain structured objectives, experiments and measured/computational observations.
Benchmark publication
Create signed scorecards and publish selected benchmark snapshots.
External evidence exchange
Accept institution-signed benchmark submissions through registered public keys.
Research collaboration
Federate provenance between organisations without requiring all private source data to become public.
Scientific computing operations
Connect simulation, HPC and result ingestion to the same research record.
Connect the domain model to the evidence and decision layer.
Quantitative infrastructure around your domain expertise.
Scientific project registry
Objectives, experiments, observations and campaigns.
Dataset lineage
Canonical schema/content lineage and source references.
Execution evidence
Simulation, HPC and external-result ingestion.
Reproducibility packs
Bind evidence to protocols, configuration and software identity.
LQBench
Signed benchmark runs, scorecards and publication.
Institutional provenance
Registered signing keys, external submissions and federated evidence.
Designed to connect to the stack you already operate.
- Research datasets and repositories
- Laboratory information exports
- Simulation / HPC environments
- Scientific model libraries
- Institution identity/signing systems
- Publication and research-data workflows
Built for cross-functional quantitative work.
- Research Computing
- Principal Investigators / Labs
- Research Data Management
- Scientific AI Programmes
- Technology Transfer / Innovation
- Institutional Research Infrastructure
Keep the basis of the decision inspectable.
The same infrastructure can preserve private research inputs while allowing selected benchmark or provenance records to be shared publicly or exchanged with partners in verifiable form.
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