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Halo | Project

Three minutes from research to a commercial-ready listing

Shipped 2025
0→1 product design
Marketplace
Senior product designer
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Summary
Impact
Context
Challenge
Approach
Solution
Outcomes

;tldr

Summary

I designed Partnering Listings, Halo's self-serve way for researchers to publish commercial-ready IP in about three minutes. The model became the structured foundation for Discover matchmaking, seeded 3,600+ proprietary listings through automated conversion, and eventually became a paid premium tier.

About the platform

Halo is an AI-powered networking platform that connects corporate R&D teams with academic scientists, startups, and innovators to collaborate on scientific research.

The Discover feed surfaces solution-level capabilities, what a provider can actually do to solve a technical problem, personalized to each R&D team and continuously updated. Listings are the proprietary supply that makes that feed worth using.

Problem

Industry can't tell what a researcher is working on now, so real opportunities stay hidden, and the usual paths, slow RFPs and cold outreach, are a grind for both sides. The deeper problem was Halo's own: without structured supply, Discover couldn't reliably match demand to the right innovators. Listings were the supply layer the marketplace was missing.

Solution

Self-serve listings a researcher can publish in about three minutes, straight from their profile. On the other side, industry sponsors get a proprietary view of what researchers are ready to partner on right now, with structured signals they can't find elsewhere, inside the platform it already uses.

My role

I led product design end to end, from research and PRD through UI/UX flows and prototype testing. I reported to the head of product and presented the final options to stakeholders, who made the call. Listings shipped 0→1, added 3,600+ proprietary opportunities, became the structured backbone of Discover matchmaking, and grew into a paid premium tier.

Impact

Growth

3,600+

marketplace opportunities, from converting existing proposals

Speed

~3 min

to a first listing

Laptop screen showing a form to add a first partnering listing with an Add listing button.
Laptop screen showing a form to add a first partnering listing with an Add listing button.

Three steps, three minutes

A researcher turns their work into a discoverable listing straight from their profile.

3 min read

Deep dive

The full walkthrough, from the marketplace problem to the product model, the tradeoff that shaped it, and what that model unlocked.

Context

Three considerations set the guardrails

Researchers already had valuable proposals, existing RFPs could seed supply, and more listings would strengthen Discover. Three considerations set the guardrails.

1

Scientific accuracy is non-negotiable.

2

Ownership can span institutions, organizations, and principal investigators.

3

Publish in minutes, while protecting confidential IP.

Challenge

The barrier was never demand, it was effort

Industry decision-makers can't tell what a researcher is working on now. Publications go stale, research is long-form, and researchers rarely have marketing support. The usual paths to a partner, a drawn-out RFP or cold outreach, are a grind with no guarantee anyone is listening.

The design problem was a tension. More information makes a listing more useful for matchmaking. More effort makes it less likely a researcher ever creates one. The real question: how do you turn highly specific scientific work into a structured marketplace signal without asking researchers to become marketers? That set the goal, publish in about three minutes.

Why a proprietary solution feed matters

The design problem was a tension. More information makes a listing more useful for matchmaking. More effort makes it less likely a researcher ever creates one. The real question: how do you turn highly specific scientific work into a structured marketplace signal without asking researchers to become marketers? That set the goal, publish in about three minutes.

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The barrier was never demand. It was that turning a researcher's work into something discoverable took more effort than most would ever spend.

The primary challenge

For my solution, the guy at the bottom might be at the top. One guy's trash is another man's treasure."

Senior Director of R&D

R&D technical experts care about the solution first, as long as it solves the problem.

‍

R&D technical experts spend about 5%-10% of their time passively scouting/actively searching for external solutions or partners

Approach

The three decisions that defined the product

The fastest way to real supply was to fit listings into what innovators and industry already did, not invent new behavior. Three decisions defined the product.

01.

Define the listing

A listing isn't a brochure, it's a structured signal for matchmaking. The hard part was a tension: it had to be open-ended enough to hold anything a researcher offers, a product, a method, a service, while still capturing enough structure for the feed to match on.

Too rigid and most of the supply wouldn't fit, too loose and Discover couldn't match. We also simplified ownership, so the organization owns the page and the principal investigator is the contact.

Testing showed "Partnering Listings" wasn't how users described it, so the user-facing name became Solutions & Services, with the product model unchanged.

02.

Reduce the activation barrier

More information makes a listing more useful; more effort makes it less likely to get created. That tension set the three-minute goal. Three-step self-serve creation, straight from a researcher's profile, became the minimum viable behavior.

03.

Preserve scientific trust

We chose manual researcher input over AI-generated content for the MVP. AI generation was the ambitious path, but for a scientific audience an inaccurate listing costs more than a slow one, so automation was deferred until the behavior was proven.

Trust first, automation later. For a scientific audience, a wrong listing costs more than a slow one.

Deferred designs

We explored several lower-effort ways to create a listing before choosing structured manual input, which is how we knew what we were trading off.

Publication-to-listing pipeline

Auto-generate a full listing straight from a researcher's publications, with no manual input at all. However, this would likely publish a claim the researcher hadn't actually made.

Embedded AI assist

Rewrite academic language with commercial framing inside the creation flow.

Upload a document

Let a researcher drop in an existing document, a capability statement or a spec sheet, and turn it into a listing instead of filling fields from scratch.

‍

Solution

A marketplace supply system, not a form

We chose manual researcher input over AI-generated content for the MVP, to validate that researchers would create listings themselves and learn what makes a listing useful.

Feature

Three-step self-serve publishing

Researchers create a publishable listing in three steps, straight from their profile. Fast to validate, and fast to learn from.

Feature

Tied to the principal investigator

Listings sit on the PI's profile, so industry contacts the person closest to the work directly. Institution → researcher → listing → industry, instead of routing through institutional channels.

Feature

RFP conversion to seed supply

Rather than wait for listings from scratch, Halo converts existing RFPs into listings researchers just approve, growing inventory while keeping ownership and accuracy.

Tradeoff: We prioritized speed to learning over automation. The first version optimized for validating the marketplace behavior, not the final creation experience.

Outcomes

Partnering Listings became Halo's proprietary supply of commercial-ready IP

The model did more than launch. It became supply the whole marketplace runs on, and the value compounded from there.

3,600+ new marketplace opportunities

Converting existing proposals produced 3,600+ opportunities that weren't available elsewhere.

The foundation for Discover

Those structured signals became what Discover matches on. Because the supply is proprietary and on-network, it surfaces novel technologies a competitor's public tools can't, an edge that matters in R&D.

A paid premium tier

Richer content and featured placement gave innovators a way to stand out, and institutions pay for it.

A roadmap-defining capability

Listings shifted Halo's roadmap toward expanding supply: facilities and lab listings, and admin-assisted creation.

Blue stylized opening and closing quotation marks on a white background.

Listing on Halo was very straightforward and intuitive, and the process required minimal time while still allowing us to clearly communicate our value proposition. The visibility was excellent, and we noticed meaningful inbound interest shortly after publishing, including early-stage conversations that would have been difficult to generate through our usual channels.

Close up portrait of Mariano Oto

Mariano Oto

CEO, Nucaps

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