There's a gap inside most institutions between the research being done and the research being seen. We’ve talked about this before: today’s public-research ecosystem operates on an attention economy, and it's a very real problem with very real costs. Those costs—narrower funding pipelines, missed collaborations, opportunities that never reach the right researchers—are diffuse and difficult to measure. And when costs are hard to see, institutions learn to absorb them as normal.

That normalization is the actual obstacle. Research infrastructure should reduce friction, not reinforce it. Our 90-day pilot is an evaluation of our infrastructure that does exactly that, with ten of your own researchers, and concrete outputs your team can measure, see, and use.

Pilot overview

Ten OS Research Hubs. Three rounds of OS Match. $5,000, applied in full toward an institutional license.

Research Hubs: what you get and what it delivers

A Research Hub is a single, current, public account of a researcher's work — one URL, built automatically from where their work already lives. AI-generated, validated by the researcher, and evergreen. 

Each Hub contains:

• Identity and affiliations. Name, photo, title, affiliations, contact, and more. 
• Primary research areas. Labels naming what the researcher actually works on.
• Targeted tags. Granular methodological and substantive labels. 
• Authoritative links. ORCID, Google Scholar, PubMed, GitHub, and more. 
• Collaboration interests. Study-design and partner types, collaboration models.
• Methods and tools. Methods, frameworks, approaches.
• Funding alignment. Open Funder types and real-world applications of the work.

What that produces:

• Visibility. Research is accurate, comprehensive, and discoverable.
• Equal coverage. Every researcher is represented at the same standard.
• Continuous currency. Faculty pages remain updated and reliable.
• Reduced upkeep. Nothing to maintain. No systems to learn.

OS Match: what you get and what it delivers

OS Match shifts funding-alert workflows from what exists to what actually fits. AI reads both the full funding landscape and the researcher’s validated Hub, then delivers a monthly report of up to 15 ranked, fit-matched opportunities. 

How it works:

• Scans every funding source. Governmental and non-governmental.
• Reads researcher Hubs. Their validated body of work, not keywords.
• Intelligently matches. Filters out low-fit results, surfaces high-confidence ones.
• Decision-ready delivery. Structured to evaluate and pursue every opportunity.

What that produces:

• Better, broader opportunities. Up to 450 from diversified, non-obvious sources.
• Reclaimed time. Decision-grade funding recommendations, ready for evaluation.
• A side-by-side reality check. Against your existing funding-discovery layer. 

What you see that you couldn’t before

Across 90 days, you get a record of what the infrastructure produces, how engagement distributes, and where the visibility gap closes.

Things that become measurable:

• Match quality. The distribution of opportunities pursued, adjacent, or missed.
• Engagement feedback. Which researchers engaged and what researchers found useful. 
• Coverage of the visibility gap. A look at how Hubs level the field across ten researchers.
• Time saved. Time reclaimed from upkeep, maintenance, and funding searches.

What you carry forward

• If you proceed: the $5,000 applies in full toward your institutional license. Both products scale without significant lift — no new systems for faculty, no new processes for admin.
• If you don't: You keep the data. Visibility insights, match-quality evidence, and engagement signal across ten faculty.

Joining the pilot ahead of our July launch

OS Research Hubs and OS Match become publicly available in July. The pilot is the window for evaluating them on your own faculty first.

Start your pilot →

Talk with our team →