Cases

Proof work should change what a team decides next.

A portfolio spanning product strategy, architecture, MVP delivery, AI and data systems, infrastructure, team building, and technical transformation.

Use the catalog to browse by industry or by the problem we solved. Some work can be named publicly; some is anonymized. In every case, activity matters less than the capability or decision the work made possible.

How to read the evidence

These cases are not all the same kind of proof. Some show early demand signal. Some show prototype-level workflow proof. Some show pilot or implementation evidence.

We label the evidence level because a good validation case should make the next decision clearer without pretending the next stage has already been proven.

Evidence levelWhat it means
Early validationInterviews, landing pages, applications, outbound, or early demand behavior.
Prototype interactionUsers interact with a narrow MVP, AI flow, demo, or application surface.
Prototype proofA functional prototype proves workflow feasibility under controlled conditions.
Pilot proofReal users or teams use the workflow with success criteria.
Production proofRepeated operational use with measured business impact.

Case study catalog

Twenty-four short cases from the team's product and technology history, including architecture design, MVP delivery, AI and data platforms, demand and acquisition testing, infrastructure, team formation, marketplaces, smart-city systems, and enterprise modernisation.

Eleven catalog cases have full write-ups across eight pages and are listed first, marked Full case. Four paid-acquisition cases share one benchmark page. Filter to the full write-ups with the *Full case* chip, or browse everything by industry and problem type.

Browse the portfolio

Choose an industry, a problem type, or narrow to the cases written up in full.

Industry

Problem solved

Showing 24 of 24 cases

Generated illustration of creator revenue data flowing through underwriting and risk controls
Generated illustration
01Fintech & CryptoProof EngineFull case

Revenue-based capital platform for creators

Testing whether creators and capital providers would engage with a revenue-backed financing product.

  • Product & MVP
  • Platforms & Marketplaces
  • Data, AI & Automation

The team needed evidence from both sides of a financing marketplace before building a broad creator platform.

Mapped segments, tested four offer framings, built an application-style MVP, and ran creator and capital-side conversations.

Narrowed the opportunity to creators with measurable recurring income and defined underwriting as the next proof gate.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Generated illustration of a narrow AI workflow with exception and human-review paths
Generated illustration
03AI & DataProof EngineFull case

AI workflow automation prototype

Proving one high-value operational workflow before expanding into a broad automation platform.

  • Product & MVP
  • Data, AI & Automation
  • Architecture & Reengineering

General interest in automation obscured which workflow was urgent enough to adopt and pay for.

Mapped operational pain, selected a narrow workflow, built a human-reviewed functional prototype, and tested positioning by segment.

Proved workflow feasibility and clarified the segment, leaving a live-team pilot as the next evidence gate.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Generated illustration of applicant flow narrowing into a qualified accelerator cohort
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05Venture & Startup Programs2025–2026Full case

Founder acquisition for a startup accelerator

Meta Ads · USA & EU · B2B

Paid acquisition of non-technical founders for an accelerator, tested down to half the starting lead cost.

  • $7.89Cost per lead · 74 leads
  • Cheaper lead vs. first tests
  • Demand & Acquisition

The program needed applications from founders it could actually accept, and the early creative rounds were buying leads at roughly twice the cost the economics allowed.

Ran Meta as the only channel across two audience sets — seed-accelerator intent and broader startup-company intent — and tested creatives, headlines, and offer angles until one held: address non-technical founders directly and promise they can stay on vision and fundraising while the program handles the rest.

74 website leads at $7.89 each on $583.97 of spend, with cost per lead halved over the test cycle. The seed-accelerator audience delivered leads at $6.48 against $10.09 for the broader startup audience, which decided where the budget belonged.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Generated illustration of search intent routed into two competing ad groups
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07Health & Telemedicine2025–2026Full case

Clinic acquisition for a telemedicine platform

Google Ads · EU · B2B

Search-driven pipeline for a telemedicine platform sold to clinics, where one deal is worth €15,000.

  • €288.87Cost per conversion · 20 total
  • €15,000Average deal size
  • Demand & Acquisition

Demand had to be captured from clinics already looking for a telemedicine solution, which made search intent — not audience targeting — the thing to get right.

Built the keyword set from scratch, wrote the ads, and ran continuous keyword and campaign optimisation across two ad groups: one on telemedicine intent, one on broader digital-health wording.

20 conversions at €288.87 from €5,777 of spend at a 5.2% click-through rate. Telemedicine intent converted at €237.12 against €366.49 for digital health, and against a €15,000 average deal both stayed far inside what the business could pay.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Chefmates mobile cookbook product screens
Original product design
09Consumer & HospitalityProduct historyFull case

Chefmates mobile cookbook

A content-rich cookbook redesigned around how people move from discovery to cooking.

  • Product & MVP
  • Platforms & Marketplaces

Recipes from established authors and food blogs needed one simple mobile journey rather than a dense catalog.

Designed the product concept, UX architecture, discovery filters, favorites, shopping lists, and step-by-step cooking flow.

Produced an end-to-end mobile product experience spanning inspiration, planning, and kitchen use.

PublicExperience represented by the Proof Engine team
Read the full case
Henry app screens: story timeline, participant list, join-to-story, and story editor
Original product design
11Media & MarketplacesProduct historyFull case

Henry collaborative storytelling

A social product where groups create one shared multimedia story.

  • Product & MVP
  • Platforms & Marketplaces

Photos, video, music, and 360° media needed creation mechanics built around group authorship rather than solo posting.

Defined the product strategy, creator UX, invitations, collaborative editing, media tools, and publishing mechanics.

Delivered a coherent social-product concept for creating and publishing stories together.

PublicExperience represented by the Proof Engine team
Read the full case
Smart-battery hardware installed on a connected service cart
Project archive
15Smart Cities & IoT2022–2025

Smart-battery platform for medical equipment

A modular battery and charging system designed to keep mobile medical equipment powered and observable.

  • Architecture & Reengineering
  • Teams & Delivery
  • IoT & Computer Vision

Medical carts needed safe hot-swappable power across multiple voltage outputs, while batteries and charging stations also needed remote monitoring.

Advised on product architecture across smart BMS, protection, hot-swap, 3–70 V and USB-C outputs, charging stations, and Wi-Fi/cloud monitoring; supported the roadmap and engineering hiring.

Connected the requirements for 36 V, 680 Wh batteries and one-, two-, and four-battery charging stations in one implementable hardware/software roadmap.

PublicExperience represented by the Proof Engine team
Original empathy-detection computer-vision architecture diagram
Original project material
17AI & Data2019

Customer empathy detection

A self-funded computer-vision concept for estimating customer emotional response in offline retail.

  • Product & MVP
  • Data, AI & Automation
  • IoT & Computer Vision

Turn an ambiguous human signal into a testable face-and-video analysis workflow without claiming a validated empathy model.

Designed a webcam-based capture and ML/CV analysis architecture for retail interactions and documented potential store, bank, and call-center scenarios.

Produced a presentation-ready architecture and proof concept; no trained or deployed production model was claimed.

PublicExperience represented by the Proof Engine team
Frame from the original Wapl Rune location-based game trailer
Original trailer frame
19Media & Marketplaces2017–2022

Wapl Rune location-based AR game

A working location-based AR game built around shared quests, points of interest, and collective mechanics.

  • Product & MVP
  • Architecture & Reengineering
  • Scale & Infrastructure

Location-aware play, AR/VR, collective mechanics, and branching quest progression had to work as one coherent mobile system.

Designed location-bound quest flows with POIs and check-ins, resources, battles, sequential and branching steps, quest chains, and rewards.

Reached a working closed beta with more than 100 testers in December 2020; a later public release was planned but is not independently confirmed.

PublicExperience represented by the Proof Engine team
Original NOMP mining-pool statistics dashboard
Original project material
21Fintech & Crypto2018

NOMP multi-currency mining pool

An open-source-based mining pool redesigned to support several major currencies at device scale.

  • Architecture & Reengineering
  • Scale & Infrastructure

The pool needed a reliable internal redesign across Dash, BTC-GPU, Ethereum, Litecoin, and other currencies.

Reworked the NOMP-based platform and its operational architecture for multi-currency mining workloads.

Supported more than 5,000 connected mining devices across a multi-currency pool.

PublicExperience represented by the Proof Engine team
Original Telecan LPWAN metering devices and analytics interface
Original project material
23Smart Cities & IoT2017

Telecan LPWAN metering platform

A Lumiot LPWAN platform for autonomous collection and cloud analysis of electricity, heat, and water-meter data.

  • Architecture & Reengineering
  • Data, AI & Automation
  • IoT & Computer Vision

Electricity, heat, and water readings had to be collected, stored, and analyzed without frequent field maintenance.

Designed the system across low-power sensors, Lumiot base stations, GSM-connected gateways, cloud device management, data collection, and visualization; LoRa support was planned.

Specified up to 2,000 devices within a 4 km radius per base station and a sensor design rated for 14 years on a single AAA battery.

PublicExperience represented by the Proof Engine team
Generated illustration of an AI qualification flow producing a structured sales handoff
Generated illustration
02AI & DataProof EngineFull case

AI sales qualification assistant

A focused AI qualification workflow tested before committing to a broad sales-automation platform.

  • Product & MVP
  • Data, AI & Automation
  • Platforms & Marketplaces

Prospects had to trust the interaction and sales teams had to find the resulting handoff useful.

Built two conversation flows, tested three positioning variants, and generated structured sales-ready handoffs.

The shorter flow won, shifting the product toward a qualification layer before human sales rather than an AI replacement for sales.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Generated illustration of small fractional stakes aggregating into property investment
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06Real Estate & Proptech2025–2026Full case

Investor acquisition for a fractional property app

Meta Ads · UK · B2C

Getting first-time property investors into an app where a stake starts at £100.

  • £1.93Cost per lead · 33 leads
  • 4.69%CTR, all clicks
  • Demand & Acquisition

Fractional ownership had to be explained and sold inside a single ad, to people who assume property investing needs a large budget.

Ran Meta on UK audiences with static creative only, after it outperformed the alternative, and built the winning ad around the entry price itself: invest in UK property without a large budget, starting at £100 in fractional shares.

33 website leads at £1.93 on £63.71 of spend and a 4.69% all-click rate. One static visual out of the set carried 21 of those leads at £1.60 each, so the creative question was settled before scaling budget.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Generated illustration of video creative outperforming static in a practitioner audience
Generated illustration
08Health & Telemedicine2025–2026Full case

Therapist acquisition for a VR therapy app

Meta Ads · USA · B2B

Selling a VR hypnotherapy tool to practising psychotherapists, where video did the work static could not.

  • $10.12CPL · winning video set
  • 46Leads · $16.65 blended
  • Demand & Acquisition

The offer was new enough that psychotherapists, psychologists, and clinics had to understand an unfamiliar treatment method before they would leave their contact details.

Ran twelve ad sets on Meta against US practitioners and clinics, splitting static feed creative against video that showed a session and positioned VR hypnotherapy as an addition to an existing practice rather than a replacement for it.

46 leads on $765.77 of spend — every one of them from a video ad set, the best at $10.12 per lead, while the static feed sets produced none. Blended cost per lead was $16.65 against a $150 monthly subscription.

AnonymizedExperience represented by the Proof Engine team
Read the full case
Bloom app screens: bouquet feed, bouquet detail, shop order queue, and delivery step
Original product design
10Media & MarketplacesProduct historyFull case

Bloom local flower marketplace

A two-sided mobile marketplace connecting bouquet buyers with local flower shops.

  • Product & MVP
  • Platforms & Marketplaces

Discovery, trust, delivery, checkout, and shop operations had to work as one local-commerce experience.

Designed both marketplace sides: occasion and location discovery, florist profiles, catalog, favorites, checkout, and order management.

Created a complete buyer-to-florist product flow ready for implementation and market testing.

PublicExperience represented by the Proof Engine team
Read the full case
Connected battery-charging station prototype with a built-in display
Project archive
16Smart Cities & IoT2022–2025

Connected charging and access control

Hardware/software architecture for connected charging and access-control products, including a related computer-vision capability.

  • Architecture & Reengineering
  • IoT & Computer Vision
  • Data, AI & Automation

Physical devices, presence and access control, and computer vision had to be translated into a coherent technical roadmap without coupling unrelated product functions.

Reviewed architecture and delivery for charging and access-control products, including neural-network number-plate recognition, and translated product constraints into technical and hiring priorities.

Established an implementation roadmap with clear boundaries between connected devices, access control, and computer-vision integration.

PublicExperience represented by the Proof Engine team
Original Giga Watt project mark
Original project material
20Fintech & Crypto2017–2018

Giga Watt mining-facility operations platform

One operations layer for distributed crypto-mining facilities.

  • Architecture & Reengineering
  • Data, AI & Automation
  • Scale & Infrastructure

Monitoring, pool control, efficiency, and stock management were fragmented across a distributed physical operation.

Designed, developed, and implemented the software management system spanning facilities, devices, pools, efficiency, and inventory.

Created a unified operational view for site operators and owners of hosted mining equipment across facilities, devices, pools, efficiency, inventory, and customer dashboard functions.

PublicExperience represented by the Proof Engine team
Original easy10 mobile language-learning product presentation
Original project material
24Consumer & Hospitality2013–2014

easy10 language-learning platform

A language-learning product built around ten words a day.

  • Product & MVP
  • Architecture & Reengineering
  • Teams & Delivery
  • Scale & Infrastructure

After iOS 7 disrupted the early app for roughly one in three users, the product needed a full mobile rebuild, scalable backend and data processing, and a delivery team.

Designed and prototyped the architecture, implemented redundant high-load infrastructure, rebuilt iOS and Android apps, assembled the team, and supported business development.

Reached 200,000 users in the first three months; later public reporting recorded more than 500,000 downloads and about $450,000 in seed investment after a three-month IIDF accelerator.

PublicExperience represented by the Proof Engine team

Case themes

Beyond the three featured patterns, representative experience includes the themes below. Detailed proof for these can be shared in partner conversations where appropriate.

Validation before MVP

Testing demand, buyer urgency, and willingness to pay before committing to product build. Representative experience includes founder and operator-led validation engagements. Explore Validate

MVP diagnosis and repositioning

Finding why an MVP is not converting, whether the issue is product, market, message, or buyer segment. Explore Build

Product build with GTM logic

Building MVPs, V1 products, internal tools, or AI workflows around validated users and buying paths. Explore Build

First customers and paid pilots

Turning product signal into first revenue, pilot design, conversion paths, and sales learning. Explore Grow

Developer ecosystem growth

Improving developer narrative, onboarding, examples, community, and adoption loops. Representative experience includes developer-tool and ecosystem work; detailed proof can be shared in partner conversations where appropriate. Explore Grow

Mature initiative proof

Testing market entry, AI, data, cloud, modernization, or product growth bets before larger investment. Explore Scale

Proof can be public, anonymized, or private.

Not every good case can be shown with a logo. The site still makes the evidence standard visible. We classify each proof point by permission level before it appears here, and we use cautious language for anything not yet confirmed.

  • Public named: client or project can be named publicly.
  • Public anonymized: pattern and result can be described without a name. The three featured cases above sit here.
  • Private sales-only: discussed in partner conversations, not published.
  • Needs confirmation: a potential proof point whose permission or status is still unclear, so it is not published.

Until a proof point is confirmed, we describe it as representative experience rather than a hard claim. Detailed proof can be shared in partner conversations where appropriate.

Explore how the work happens

More context on the studio behind these patterns.

FAQ

Frequently asked questions

Some, not all. Every proof point is classified by permission level before it appears: public named, public anonymized, private sales-only, or needs confirmation. The featured proof patterns on this page are public anonymized — the metric ranges are approved, and client names, logos, and identifiable project names are intentionally withheld.

The catalog spans product architecture, MVP delivery, AI, data platforms, demand and acquisition testing, team building, infrastructure, IoT, marketplaces, and public-sector systems. Filters on this page combine industry and problem type, so you can narrow to the pattern closest to your own situation.

Each case is labelled by evidence level — early validation, prototype interaction, prototype proof, or pilot proof — because a good case should make the next decision clearer without pretending the next stage has already been proven. Each one also states what it does not yet prove and the recommended next proof gate.

Detailed proof for private cases can be shared in partner and sales conversations where permission allows. Until a proof point is confirmed, it is described as representative experience rather than a hard claim. Tell us your situation and we will share what is relevant to it.

By whether it changed a decision. Each case states the decision supported, what the evidence proved, what it did not prove, and the recommended next proof gate. Activity matters less than the capability or the decision the work made possible.

Contact

Bring us the decision you need to make.

Tell us where you are, what you are trying to prove, and what would make the next move worth it.

Kirill Artsymenia, Founder of Proof Engine

Founder, Proof Engine

Kirill Artsymenia

Reads every brief personally. Usually replies within 24h.

Opens your email app with the brief pre-filled.Book a routing call

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