Constructor Research brings the whole research cycle into one workspace: exploring the literature, forming hypotheses, and running experiments on ready-to-use compute and HPC, with secure storage, reproducible environments, and collaboration for teams in academia and industry. Because Research is part of the Constructor platform, it shares accounts and data with Learn, Assess, Groups, and the rest of your stack.
8,000+
research papers indexed in the Hypothesis beta
(NeurIPS & ICML 2025)
200+
AI models available
with guardrails and access rights
Multi-cloud + HPC
GPU on demand,
no setup
40,000+
GPU-hours run on A100 and H100
at Constructor University in 12 months
Everything a research team needs to compute, collaborate, and reason over the literature, without stitching tools together.
Search papers by idea, method, claim, and result, not just keywords. Constructor Hypothesis turns the literature into a knowledge graph you can navigate to find evidence, contradictions, and gaps.
Cloud, HPC and GPU on demand, with no waiting on IT. Templates take the repetitive setup out of runs, and the setup is saved so anyone can rerun it.
Define a run once, vary the settings and compare the runs in one report. Each run keeps an audit record: parameters, simulator, result. Today it covers quantum circuits and quantum ML.
Share access and pin environments so collaborators get the same result on the same data. Versioning across experiments and generated content keeps work traceable.
Share data, algorithms, and results with your team and external partners for immediate feedback, with scoped access so collaborators see only what they should.
Access controls and encryption protect sensitive work. For IP-concerned teams, local indexing and text generation can run inside your own cluster.
A Research Assistant that runs quick checks against existing data and computational methods, and helps plan and troubleshoot experiments, tuned for science rather than generic code completion.
Connect Overleaf, Mathematica, Matlab, and reference libraries like Zotero, so Research fits your workflow instead of replacing it.
Reach your Hypothesis collections from Claude, Cursor, ChatGPT or your own agents, so discovery becomes part of daily work.
See across a field from a single question. Hypothesis turns papers, code, datasets, and results into a navigable knowledge graph of claims, methods, and evidence, so you move from a question to the most relevant work, the hidden connections, and the unresolved gaps, in one flow.
Index your library into the same graph as the built-in corpus and see connections across both.
Surface open questions, thin evidence, and contradictions to ground new hypotheses.
Pressure-test a hypothesis and get a validation plan with datasets, baselines, and metrics.
Reach indexed collections from MCP-compatible tools like Claude, Cursor, and ChatGPT.
"The most valuable signal in science is a quiet contradiction between two results that are both solid. Hypothesis finds those, attributes them to specific claims and papers, and proposes what could explain both."
One context throughout: the collection from step one feeds the run in step three.
Compute, HPC, and GPU ready in the cloud, no manual server or software setup.
Connect datasets, code, and reference libraries. Index your own papers alongside the built-in corpus.
Search the literature by method and claim with Hypothesis, then draft evidence-grounded hypotheses.
Use templates and workflows on scalable GPU and HPC compute, with a pinned environment for every run.
Share access, results, and pinned environments so teammates reproduce the same outcome.
Track versions and export traceable code, data, and results for review and publication.
Free notebooks, national HPC allocations, cloud ML platforms, and AI literature tools each serve researchers well. Constructor Research brings compute, HPC and multi-cloud orchestration, reproducible environments, and deployable apps into one workspace, with science-focused AI in beta and more on the way.
Constructor Research is featured among the best data science platforms on The Interregnum.
Bash / ssh setup with IT
Manually handle HPC and GPUs
Manual software install and versioning
Complex manual integration
Keyword search across scattered PDFs
Ready to use in the cloud
On-demand, with no setup
Pre-configured and automatic
Pre-integrated and ready to use
Semantic search and a knowledge graph (Hypothesis)
Other research tools means notebook platforms, university and national HPC services, cloud ML platforms, and AI literature tools. Capabilities vary by product. Based on public product documentation.
Scroll horizontally to compare all columns.
| Capability | Constructor Research | Other research tools |
|---|---|---|
AI and discovery | ||
Literature search by idea, method, and claim |  Hypothesis (beta), with a claims and evidence graph | Separate AI literature tools; citation maps common |
Literature coverage | 8,000+ papers in beta, plus your own | Dedicated tools index over 100 million papers |
AI assistant, agents, and MCP | MCP server for Hypothesis; Research Assistant coming soon | Coding agents and MCP available in several today |
Compute and infrastructure | ||
On-demand cloud and GPU | Ready to use, no setup | Common in hosted notebooks and cloud ML |
HPC and your own hardware | Orchestrated from the same workspace | Strong in HPC portals; self-hosted, needs IT |
Multi-cloud orchestration | Supported, set up with our team | Uncommon; most tie you to one cloud |
Collaboration and reproducibility | ||
Reproducible environments | Templates and pinned environments | Common, often via containers or images |
Real-time co-editing | Scoped sharing; no live co-editing | Available in several notebook tools |
Deployable research apps | Multi-service apps with built-in image registry | Usually a separate product or add-on |
Deployment and data control | ||
Deployment options | Cloud, private cloud, on-premise, or air-gapped | Hosted only, or self-hosted with IT effort |
AI inside your own infrastructure | Indexing and text generation in your cluster | Mostly vendor-hosted; self-hosting needs IT work |
Access and value | ||
Free start for individuals | Hypothesis beta free to try | Common: free tiers and education plans |
Free academic compute | Can connect HPC you already use | Free national allocations for eligible researchers |
Wider platform included | Learning, assessment, and more included | Usually separate products |
Physicists, biochemistry and bio-material engineers, nanotechnology and polymer scientists running heavy computation and machine intelligence over shared datasets.
Biologists, genetics and microbiology engineers, biotechnology and bioinformatics scientists who need reproducible pipelines and secure data handling.
Computer scientists, data analysts, and AI, robotics, and cybersecurity engineers who want compute, MCP, and agent workflows without infrastructure overhead.
PIs shaping questions and picking defensible methods, and lab or R&D leads who need a portfolio view of topics, bets, and risks across teams.
Early-career researchers ramping fast on a topic and information specialists standardizing sources, provenance, and retraction awareness.
Enterprise R&D groups that need IP-safe deployment, local indexing inside their own cluster, and results they can hand to the business.
A Nobel laureate's research group runs its science on Constructor Research, from shared data to published, reproducible results.
Laureate-led research group on the platform
Computational Materials paper published with code on Constructor
Platform replacing scattered servers, IDEs, and storage
"We use Constructor Research to unify data produced by different research groups, run machine intelligence on the dataset, and accelerate our research as a result."
"With Constructor, I have everything all in one: a cluster with resources, an IDE, and Constructor Model to store data and results. I especially like the availability of computational resources and how easy the products are to use."
"Sparse representation for machine learning the properties of defects in 2D materials", published in npj Computational Materials, with code and trained model weights hosted on Constructor.
"Hypothesis maps the literature by revealing claims, contradictions, and methods, helping understanding and accelerating work."
What you buy
On-demand compute, HPC, GPU, and multi-cloud orchestration
Automation, templates, and reproducible environments
Collaboration and instant sharing with scoped access
Science-focused AI: Hypothesis MCP server, Research Assistant coming soon
Literature exploration and knowledge graph via Hypothesis
Deployable research apps, container registry, GitHub integration
Included with Research
The learning platform: deliver courses, track completion and issue certificates
Assessment, question banks and grading
Secure exams and proctoring
Live classes and group collaboration
Hands-on practice and virtual labs
Course authoring
Scheduling and calendars
Research fits the tools and hardware you already run. Connect your stack, or go deeper with the open API.
Overleaf, Mathematica, Matlab (coming soon)
Zotero reference libraries (coming soon)
Notion, Authorea, SciNote (coming soon)
Publisher indices: Crossref, PubMed
GitHub / Git, S3 storage
Constructor Groups transcripts as project context
Cloud, private cloud, on-premise
HPC and GPU, multi-cloud orchestration
Air-gapped and IP-safe installation
Local indexing and text generation in your cluster
MCP server for agent workflows
Integrated IDEs: Jupyter, VS Code
Container build and image registry
Open API and custom workflow automation
Single sign-on via Constructor Platform
Research data needs protection you can defend, and control you can prove. Your work stays yours.
Join a growing network of resellers, integrators, and solution providers who are bringing Constructor Research to universities, research institutes, and organizations around the world. Whether you're an edtech distributor, a research-infrastructure integrator, an HPC or cloud provider, or a regional training company, we offer flexible partnership models designed to create shared value.
Competitive margins and co-selling support on every deal you bring in.
Training, demo environments, co-branded materials, and a dedicated Partner Content Hub.
Joint campaigns, lead sharing, and visibility in our Partner Locator.
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