Prototyping & Wireframing
Eight weeks. That's how long the feature took to build. The first user test took 45 minutes. In those 45 minutes, three users confirmed what nobody had wanted to hear: the feature solved the wrong problem. The assumption, unvalidated, unquestioned, built upon, was wrong. Eight weeks of engineering. One architecture decision that can't be reversed without starting over. Not because the team couldn't build. Because nobody had tested the idea before they started.
We build prototypes so your engineers can build with certainty, not optimism.
The problem
Sound familiar?
The costly assumption
Everyone in the room agreed the feature was a good idea. Nobody had asked a real user. Six weeks later, the analytics confirmed it: nobody was using it. The room was wrong. The engineering time is gone.
The Figma telephone game
Design approved in a meeting. Developer interprets the Figma. Stakeholder sees the result. 'That's not what I meant.' Three rounds of revision. Two weeks lost. All preventable with a clickable prototype anyone could test and sign off on.
The scope explosion
What started as 'a simple filter feature' became a four-week project because nobody mapped the edge cases before writing code. Prototyping forces you to confront complexity before it becomes expensive.
The demo with nothing to show
The investor demo is in two weeks. You need to show a working product. You don't have one. A high-fidelity prototype bridges that gap, fast, and lets you gather real feedback before committing to an implementation.
Our approach
Here's how we fix this.
We build prototypes so your engineers can build with certainty, not optimism.
How we deliver
From kickoff to production.
Scope & assumption mapping
Day 1-2We identify the riskiest assumptions in your product concept, the ones most likely to be wrong and most expensive to fix after building. These become the test targets. Prioritized by impact, not by what's easiest to prototype.
User flow design
Day 2-4Map the complete path from user intent to task completion. Every screen, every decision point, every edge case, defined before the first pixel is placed. Gaps in the logic appear here, not after code is written.
Low-fidelity wireframe prototype
Day 3-5Clickable prototype focused entirely on flow and interaction logic. Fast to build. Cheap to change. Easy for users to give honest feedback on without being distracted by visual polish.
High-fidelity interactive prototype
Week 1-2Pixel-perfect prototype with real content, real interactions, and real micro-animations. Indistinguishable from the real product to a test user. Used for final stakeholder sign-off and user validation.
Moderated user testing
Week 25-8 test sessions with real users matching your target persona. Task completion rates, friction points, confusion moments, and confidence scores, documented and analyzed. Go/no-go decisions with evidence, not intuition.
Developer specification & handoff
Week 2-3Annotated Figma file with every interaction, state, animation, and edge case documented. Developers know exactly what to build. No interpretation sessions. No 'that's not what I meant' after code is written.
What you get
Everything you need. Nothing you don't.
Clickable Figma prototype
Test and validate the full experience before writing a single line of code
User testing report
Evidence-based go/no-go on every feature, task completion rates, not opinions
Complete user flow documentation
Every screen, state, and edge case mapped before engineering starts
Annotated design specifications
Developers build exactly what was designed, zero interpretation required
Interaction library
Animations, transitions, and micro-interactions documented and reusable
Assumption validation report
Written record of which assumptions held, which changed, and why, for stakeholder alignment
Proof, not promises
We've done this before.
FlowSync
The situation
FlowSync's product team had approved a 14-week engineering sprint for their most ambitious feature: a visual 'Automation Builder', a drag-and-drop interface for creating workflow automations without code. The feature was central to their enterprise roadmap and had been verbally committed to three anchor customers representing $480K in ARR. Engineering was staffed and ready to begin. In the pre-sprint kickoff, the CTO raised a single concern: 'We are about to build a very complex interaction model based on static Figma mockups nobody has tested with a real user. If we get the UX abstraction wrong, we build the wrong engine, and rearchitecting it costs us 6 weeks we don't have.'
Technical challenge
The automation builder required designing a node-based visual programming interface, a paradigm most of FlowSync's target users (operations managers, RevOps teams, and non-technical business analysts) had never encountered. Two interaction models were in contention: a 'canvas' model where users drag automation nodes onto a free-form workspace (similar to Figma or Miro), and a 'wizard' model offering a step-by-step guided flow builder with contextual suggestions. Both models were technically valid but required fundamentally different state management architectures, the canvas model needed a spatial graph data structure with real-time collaborative conflict resolution, while the wizard model needed a sequential state machine with branching logic. Building the wrong model and discovering the error after engineering was embedded would require discarding 6-8 weeks of core interaction code. The team needed a validated answer before writing a single line of the interaction layer.
What we did
Built two competing medium-fidelity prototypes in Figma within 5 business days: the canvas-based free-form model with 23 interactive states including drag-and-drop, connection drawing, node configuration panels, and zoom/pan behaviors; and the wizard-based sequential model with 31 guided steps including conditional branching, template selection, and a contextual suggestion engine
Recruited 8 participants matching FlowSync's target user profile, operations managers and RevOps professionals at 50-500 person companies with no coding background, for 45-minute moderated usability sessions conducted via Zoom with screen recording and eye-tracking via Maze
Ran identical structured task scenarios with both prototypes: 'Create an automation that sends a Slack notification to the sales channel when a new CRM deal is created with a value over $50,000', measuring time on task, error rate, help-seeking behavior, confidence score (self-reported 1-10), and think-aloud commentary
Canvas model results: 19% task completion (1.5 of 8 users completed without assistance), average 34 minutes on task, 7 of 8 users explicitly asked for help or gave up. Wizard model results: 78% task completion (6.25 of 8 completed independently), average 11 minutes on task, 2 of 8 needed assistance, results were unambiguous with high confidence even at n=8
Delivered production-ready annotated Figma specification for the wizard model with all 31 interaction states documented including error states, loading states, empty states, and edge cases; a component mapping document linking Figma components to existing design system elements in FlowSync's component library; and an engineering decision brief summarizing the user testing results with recommendation and rationale
Results
Validated Development Direction
Estimated Dev Time Saved
Automation Builder Onboarding Time
Feature Adoption (30 days post-launch)
Post-Launch Major Revision Cycles
Anchor Customer ARR Unlocked
Technologies
What impressed us most was their ability to take a complex product vision and validate it as a technology direction before we committed engineering resources. The prototyping approach helped us cut development risk significantly and gave our team full confidence in what we were building.
Tech stack
Built on what works.
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A week of prototyping is worth a month of revision. Let's validate your next feature before the engineers build it.