da.tes · UX/UI Design
From 824 to 2,000+ startups nationwide: redesigning the platform that became CESAR's official investment tool
- UX/UI Design
- Platform Redesign
- AI-Powered Matching
- Two-Sided Marketplace
Context
da.tes is a platform built by CESAR connecting startups with investors and corporations, using smart matching to generate personalized recommendations based on profile, business interests, and goals.
My role
UX/UI Designer, responsible for research, information architecture, and prototyping, within a 2-person design team.
Objective
A responsive redesign that attracts new users organically and delivers immediate value post-registration, for two very different audiences at once: startups looking for capital, and investors looking for deal flow.
Company & User
The business problem
A two-sided marketplace only works if both sides get value fast. If startups feel the platform doesn't understand their pitch, or investors feel matches are irrelevant, the whole loop breaks before it starts. Organic growth depends on immediate, visible value right after registration, not eventually.
User needs
- Startups struggled to secure connections and present their business to investors in a way that got noticed
- Investors needed an efficient way to find relevant startups without wading through noise
What success looked like
Fully completed profiles on both sides, a landing page that communicates the platform's value proposition clearly, and an onboarding flow simple enough that neither audience abandons it halfway through.
Process
Stakeholder interviews
Ran in-depth interviews with both startups and investors before the Design Sprint, mapping needs and pain points separately for each group. This is what shaped which features got prioritized in the redesign.
Design Sprint and prototyping
Built mid-fidelity prototypes for both the startup and investor flows to test initial hypotheses.
What testing validated
- Landing page redesign — clearer communication of the platform's value proposition
- Onboarding flow — redesigned to make functionality legible from the first interaction
- UX writing adjustments — clearer instructions and tooltips across the platform
- Profile and registration fields — enhanced for both startups and investors, to improve match quality
- Opportunity listings — restructured information (challenges, investor profiles) to be more engaging
AI-powered matching
Beyond the interface redesign, the platform's core matching logic runs on a predictive model that scores startup-investor compatibility based on stage, sector, traction, and history, not just keyword overlap. Getting this right meant working closely with the technical team to translate qualitative interview insights (what actually makes a match "feel right" to both sides) into the scoring criteria the model uses.
Results & Impact
- From 824 startups (year one) to 2,000+ registered nationwide across Brazil
- Lean MVP validated with 103 startups and 33+ matches before scaling
- The prototype became CESAR's official investment platform, not just a design exercise that shipped and got shelved
- R$8 million in projects channeled through the platform
- Two distinct, mapped user journeys (6 steps each) for startups and investors, from landing page to closed opportunity
- A live, responsive platform, still running at dates.cesar.org.br
Closure & Relevance
Designing for a two-sided marketplace means every decision has to work twice, for two audiences with different incentives and different anxieties, without making either one feel like an afterthought. The hardest part wasn't the interface. It was holding both user journeys in mind at once without collapsing them into one generic flow.
Why this matters for Product Design and UX Research roles
This case shows research directly shaping product decisions, including AI-driven ones (the matching model's scoring criteria came from qualitative interview insights, not just engineering assumptions), and design for a genuinely dual-sided problem, which is a common pattern in marketplace and platform products. It's also proof that the work didn't stay a prototype: it became the client's actual operating infrastructure.
Product Management lens
This project required translating a business growth objective (organic acquisition, post-registration activation) into testable product hypotheses, prioritizing which of five candidate improvements to ship first based on user testing evidence, not opinion, and aligning with the technical team on how a business need (better, more trustworthy matches) became a concrete technical spec (the AI scoring model's criteria). The platform's adoption as CESAR's official investment tool, with R$8M in projects running through it, is the kind of outcome that only happens when product decisions stay tied to business impact, not just usability.