Research is evolving. Your infrastructure should, too.
Bench removes the overhead between data and discovery — so your labs spend more time on science and less on the tools meant to support it.
Straightforward Pricing. Real Cost Offset.
One line item. Replaces many.
Bench works on a simple model. The platform itself — ELN, project management, literature library, inventory, notes — is free to deploy for every researcher at your institution. AI capabilities (hypothesis generation, data analysis, manuscript assistance, scheduled research tasks) are powered by credits.
How it works:
- Minimum credit purchase of $250 per researcher per year, institution-wide
- Credits are consumed as researchers use AI features — analysis runs, literature scans, ARC queries
- Unused credits roll over — no end-of-year cliff
- One agreement covers the full institution, all departments, all labs, all researchers
| What we replace | Cost |
|---|---|
| ELN | $300–$1,000 |
| Reference manager | $150–$300 |
| LLM subscriptions (ChatGPT, Claude) | $240–$2,400+ |
| Bioinformatics outsourcing | $2,000–$10,000+ |
| Heureka total | $250 |
For most institutions, the credit allocation costs less than the ELN it replaces — before even counting the AI research capabilities.
More Output Per Research Dollar
Your grants aren’t the bottleneck. Your infrastructure is.
The time between data and publication is longer than it needs to be. Bench compresses it — for every lab, at every stage.
- Researchers go from results to manuscript faster with AI-assisted analysis, interpretation, and drafting
- Graduate students work more independently, reducing PI time spent on routine guidance
- Automated literature scans, scheduled analyses, and structured project outputs mean less time on overhead, more time on science
- Cleaner, more reproducible data packages make grant renewals stronger
More papers per grant. Higher quality submissions. Faster time to publication. Dedicated onboarding sessions ensure labs are productive from day one.
Science has a reproducibility problem. Bench offers a solution.
Manage models, code, and data all in one place.
The reproducibility crisis isn’t abstract — it costs institutions credibility, complicates grant renewals, and undermines the scientific record. A significant portion of the problem is infrastructure: analyses run in ad-hoc environments, undocumented decisions, figures generated and lost, code that lived on a postdoc’s laptop.
Bench makes reproducibility the default, not an afterthought.
- Every analysis generates a full report package — code, data inputs, figures, methods, and interpretive outputs bundled together automatically
- Researchers can reproduce any result from any point in a project’s history without complex reconstructions
- Standardized workflows and documented decision points mean another lab — or a grant reviewer — can follow exactly what was done and why
- Structured outputs make data sharing, supplementary materials, and open science compliance straightforward
- Reproducibility packages can be attached directly to manuscript submissions or grant reports
When a funding agency asks for the underlying data and analysis, your researchers have it — organized, documented, and ready.
Make discoveries you can share. Make discoveries that matter.
Not a black box. Every step, visible.
The legitimate concern about AI in research isn’t that it’s wrong — it’s that you can’t see why it said what it said. Most AI tools give you an answer. Bench shows you the reasoning.
- ARC displays step-by-step instructions for every analysis and recommendation — researchers see exactly what was run, in what order, and on what data
- Data artifacts are fully visible at each stage — inputs, intermediate outputs, and final results are inspectable and downloadable
- Hypothesis generation and interpretation outputs include confidence levels, supporting evidence, and explicit alternative explanations
- No hidden inference chains — if a researcher can’t follow the logic, reviewers can’t either
- Administrators and PIs can audit any analysis their team ran — what was queried, what data was used, what the model returned
This matters for grant reporting, institutional review, and the basic scientific standard that a finding should be explainable by the person presenting it.
Deploy in Days. Supported From Day One.
Fast to deploy. Never left to figure it out alone.
Bench installs locally in minutes with no complex IT infrastructure. But fast deployment is only useful if your researchers actually use it — which is why onboarding and ongoing support are built into every institutional partnership.
- Institution-wide rollout with customizable features for each organization
- Single agreement covers all departments and research groups
- Researchers are active on day one — no training program required to get started
- Onboarding sessions for department leads and lab managers at launch
- Dedicated support calls for any lab or department that needs hands-on help
- Demo sessions available on request for new departments, new faculty, or administrative stakeholders who want a walkthrough
You’re not buying software and being handed documentation. You’re starting a true research partnership.
Security Built for Research Institutions
Local-first. Audit-ready. Compliant by design.
Research data — especially pre-publication findings, clinical datasets, and proprietary assay results — should live where you want it. Bench offers both local and cloud solutions.
- Local-first architecture means sensitive data stays on researcher workstations by default
- Secure institutional cloud workspace available with access controls and audit logging
- We do not train on user data
- Designed to support IRB, HIPAA, and institutional data governance requirements
- Compliance reporting and data provenance documentation built in for enterprise accounts
Your researchers get the tools they need. Your institution keeps control of the data.
Built to Fit Your Institution
Configurable from day one. Scalable as you grow.
Every institution has different departments, compliance requirements, and ways of working. Bench enterprise adapts — and when it doesn’t do something you need, we build it.
- White labeling: Deploy under your institution’s brand
- Custom workflows: Configure for organization-specific research processes
- Compliance reporting: Grant reporting, documentation, and institutional review outputs
- Admin dashboards: Visibility into research activity and platform usage across labs
- Feature requests: Direct line to our product team — institutional partners shape the roadmap
- Bespoke development: For unique infrastructure or workflow requirements, we scope and build to spec
- Integrations: Connect with existing institutional systems, core facility platforms, and data repositories
If it matters to your institution, it matters to us.
Turn Your Data Backlog Into Institutional Assets
Your labs have been generating data for decades. Most of it is underutilized.
Experimental datasets sitting in institutional repositories — sequencing runs, proteomics, historical assay data — represent accumulated scientific value that rarely gets fully extracted. Bench changes that.
- Custom AI models can be trained on your institution’s historical datasets
- Surface cross-lab connections, unpublished findings, and IP candidates from data you already own
- Identify and prioritize high-value research assets before they leave with a departing PI
- Enterprise data audit available — we help you understand what you have before deciding what to build on it
Become the Institution That Leads Research AI
AI adoption in research isn’t coming. It’s here. The question is whether your institution shapes it or reacts to it.
The universities that invest in research AI infrastructure now will operate differently in five years — more productive labs, stronger grant portfolios, and the ability to attract researchers who expect modern tools.
Heureka is a platform for institutional AI leadership:
- Develop an institutional AI research policy in partnership with Heureka — we’ve worked across research contexts and can help you get ahead of the governance questions before they become problems
- Build toward autonomous research capacity — as Heureka connects to core facilities, sequencing pipelines, and publishing platforms, it becomes the infrastructure for research divisions that run continuously
- Purpose-built foundation models for specific disease areas, tissue types, and institutional research priorities — developed in partnership with your scientific leadership
- Position your institution as an AI research leader to prospective faculty, grant agencies, and industry partners
- Empower researchers with your AI investment — not just for efficiency, but equity and accessibility as well
This is infrastructure for where research is going. The institutions building it now will define what that looks like.
Schedule a Briefing
30 minutes with our team. We’ll walk through deployment scope, show the cost offset model for your institution’s size, and answer questions about security, customization, and support.