My Ownership
Strategy through launch readiness.
I owned product strategy, roadmap definition, brand direction, information architecture, UX/UI, the design system, and design QA across the evolving product.
An AI-powered financial insights platform that gives founders and early-stage startups access to the kind of intelligence that usually costs a CFO's salary.
AI Summary
The Brief
Resonary was building Impact.io to solve a real gap in the market. Founders and early-stage startups are constantly making high-stakes financial decisions with limited information and no one in their corner who actually knows finance. Hiring a CFO isn't an option at that stage. The goal was to build a product that could fill that gap using AI, delivering valuations, market sizing, forecasting, and industry benchmarks in a way that felt clear and trustworthy rather than overwhelming. I broke the work into discovery, financial inputs, AI outputs, and launch-ready flows, using a shared roadmap to align priorities across brand, product, and development.
My Ownership
I owned product strategy, roadmap definition, brand direction, information architecture, UX/UI, the design system, and design QA across the evolving product.
Collaboration
A shared roadmap aligned priorities across the Resonary team. I used review rounds to resolve flows before high fidelity and daily build reviews to keep implementation close to the product intent.
Core Constraints
The experience had to make complex AI-generated financial analysis understandable and credible for founders without finance expertise, while the product and feature set were still evolving.
Impact.io platform overview: AI-driven financial insights dashboard
Context
Most founders are running on gut instinct and whatever free tools they can stitch together. Proper financial analysis, real valuations, actual market data — that work costs more than most early-stage companies have. The people who need it most are the ones least likely to be able to afford it.
The challenge wasn't just surfacing the data. It was making it feel usable. Financial tools tend to either oversimplify to the point of being useless or pile on so much complexity that you need a finance degree to interpret them. Impact.io needed to land somewhere in the middle, and the UI was the thing that would make or break that.
Product Design
The core product lets users input their business details and immediately get back a valuation, market sizing, and benchmarks against comparable companies in their space. The AI does the heavy lifting behind the scenes. The UI just needs to make the output feel credible and easy to act on.
Brand and product design happened in parallel. The visual identity needed to communicate trust and precision without feeling sterile. The product itself was designed so that someone with no finance background could open it, input their numbers, and walk away with a real understanding of where their business stood.
Step 01
Started with surveys of founders and operators at early-stage companies who were making financial decisions without real support. Mapped what tools they were using, where those tools were falling short, and what would actually get them to switch. Synthesized the findings into the core problem, success criteria, and a prioritized MVP roadmap.
Step 02
Mapped the financial-input and AI-output journeys, then built the information architecture, user flows, and low-fidelity wireframes. I developed the brand alongside the UX so trust, clarity, and hierarchy were part of the product from the start. Multiple review rounds with the Resonary team resolved the flows before high fidelity.
Step 03
Hi-Fi designs built in Figma. User testing revealed friction points in how the AI outputs were being presented, specifically around how confident users felt in the numbers they were seeing. Iterated on data visualization and layout until the outputs felt credible rather than black-box. Delivered full component docs and a design system for handoff.
Step 04
Stayed close to the development builds with daily QA reviews to catch anything that drifted from the specs. Continued designing new features as the product evolved, including expanded valuation tools, market benchmarking, and forecasting capabilities. The product is still actively being built.
Research Synthesis
Surveys and journey mapping showed that existing tools answered isolated questions but did not provide one understandable view of valuation, market size, benchmarks, and financial health.
Testing showed that a result alone was not enough. Founders needed context, confidence cues, and a clear explanation of what influenced the number before they could act on it.
Dense financial outputs increased uncertainty. The product needed progressive detail: a clear takeaway first, supporting inputs next, and deeper analysis when the user wanted it.
Decision-Making
A minimal result screen was simpler, but testing showed it felt black-box. I added supporting context, confidence signals, and clearer data hierarchy so users could judge the result themselves.
Treating brand as a later layer would have separated visual trust from product clarity. I developed both in parallel so tone, hierarchy, and interaction patterns reinforced the same promise.
The roadmap moved from financial inputs to understandable AI outputs and launch-ready flows before expanding valuation, benchmarking, and forecasting. That kept testing focused on the highest-risk experience.
Process Evidence
These slots are reserved for the three process screenshots that will show how research and testing shaped the final experience.
Thin data through compounding value and measurable impact.
Pain points, goals, behaviours, and trust constraints.
Four roles, distinct needs, and points of friction.
Impact.io is approaching public beta after multiple rounds of user
testing and feature expansion. The platform went from a basic
concept to a full product with a brand, a design system, and a
working web app. User testing on the valuation features has been
used to drive each round of refinements, and the feedback has
been strong.
The hardest part of this project was translating what the AI
was actually doing into something a non-technical founder could
trust and act on. Getting that right took iteration, but the
product is in a genuinely good place heading into launch.
