Pre-seed · investor deck
01

€500K SAFE · 18-month market proof


Get inspired. Personalize. Purchase.

We are building the next level, AI-native shopping experience. First targeting home & deco.

Mobile-first solution with native iOS · Android · web platform support Partner pilots + affiliate onboarding Public launch · targeting September 2026
vuve
InspirationStop scrolling random room ideas. Take a photo of yours and get inspired by ideas built on local supply.
PersonalizationSee what you buy directly where it'll be. Recommendations tailored to you.
Stay in the flowNo long waits for a single messages. Vuve runs on fast & efficient AI models trained for AI-driven shopping.
Expert adviceNo need to understand the tech jargon to buy a phone with a good camera. Vuve asks questions that everyone understands, and supports decisions making.
Problem
02

The discovery market is misaligned

The highest bidder gets seen. The best fit gets buried.

Advertising rewards spend—not product quality.

Top bids and high-margin products buy visibility, even when a lower-priced merchant or better product is the stronger choice.

More ad spend → more visibility
Product fit stays unclear.

Buyers guess through complexity

They cannot be experts in every categoryImportant trade-offs stay hidden behind filters, jargon, and incomplete product data.
They cannot picture the outcomeClothes, furniture, and décor are difficult to evaluate outside the shopper’s own context.
Inspiration images lead nowhereA photo may express the need perfectly, yet most shopping tools cannot search from it.

Merchants pay to enter a black box

Low prices leave less room to bidValue-focused merchants must choose between affordable offers and expensive visibility.
Chatbots make discovery even less visibleBlack-box answers offer no ranking transparency and little of the control merchants expect from SEO.
Rankings miss the local realityCurrent supply, availability, local characteristics, and merchant context are rarely explained.
Solution
03

From uncertainty to a decision

vuve makes discovery explainable—and products imaginable.

The advisor clarifies the need, searches current supply, and shows the result in the shopper’s context.

Guided decision journey Clickable vuve questionnaire asking a non-expert laptop use-case question defined in the catalog schema
vuve asks the right questionThe AI-driven questionnaire is tailored for the needs of vuvers - based on their expertise and needs.
Base roomEmpty living room used as the base image
1 · SofaSage sofa product reference
2 · TableOak coffee table product reference
3 · LampBlack arched floor lamp product reference
Generated roomGenerated room containing the selected sofa, coffee table, and lamp
Higher value shopping intents - delivered by visualizationEvery preview links inspiration, selected products, and real supply—improving relevance as categories and usage grow.
Similarity search integration
04

A new discovery entry point

Similarity search turns inspiration into catalog demand.

A shopper uploads or shares an image; vuve returns visually related products from approved merchant supply in the same results overview used for every search.

Working results overviewReference image → related catalog products → attributable merchant action
01

One workflow, new intent

Visual discovery joins the existing catalog, comparison, ranking, and click-attribution journey.

02

No new storefront to build

Partners keep their current feed while vuve adds an image-led entry point across consumer and embedded surfaces.

03

Supply compounds the advantage

Every connected catalog expands the matchable universe—a network advantage a standalone image model cannot reproduce.

For partners
05

Low-friction onboarding

Five minutes to submit existing webshop supply for review.

vuve integrates with all popular webshop engines, and also custom webshops using product feeds

PreparedClaim the webshopCompany and shop context can be prefilled for review.→
~5 minSubmit the feed URLNo custom integration project and no manual catalog re-entry.→
AutomaticParse, match, diagnoseRow-level issues and catalog mappings are visible.→
ControlledActivate after checksManual fallback covers partners without a feed.✓
Low-upfront-friction wedge: submit existing supply without a bespoke integration; pay through an attributable click model after activation. Sponsored influence and visibility rules remain disclosed.
Guided vuve partner onboarding wizard showing organization, shop, feed, and submission steps
Guided partner onboardingOrganization · shop · feed · submit

“Five minutes” refers to submitting/connecting an existing feed, not guaranteed public activation time; approval and catalog-quality checks remain explicit.

Product demo
06

57 seconds · English

See the current shopping journey end to end.

demo-video-chat-en.webmEnglish interface · no narration · 57.12 s

What this demonstrates

  • Plain-language intent becomes structured criteria.
  • Visible assistant work makes progress understandable.
  • Real catalog facts ground the recommendation.
  • Grid and comparison views keep the decision usable.
Open the full video ↗

Recorded product walkthrough. It demonstrates the implemented interface flow—not customer usage, conversion, or live-model latency.

Product and validation
07

A product, not a promise

The system exists. Early demand signals are visible.

vuve enters the round with a working cross-platform product, partner operations, an embedded distribution surface, and clear launch measurements.

3Customer surfacesWorking web, iOS, and Android product codepaths.
SignedInitial partner pilotsFounder-reported pilot agreements; payment status is not implied.
BuiltEmbedded advisorThe domain-scoped on-site assistant is implemented and evidenced.
50+Beta + waitlistFounder-reported pre-launch consumer interest.
53%Observed action signalEarly live-widget partner-action observation; methodology belongs in diligence.
Planned 90-day launch scorecard · from 13 Jul 2026Verify the model in market
Active partners and renewed budgetsCommercial searches by real shoppersAI cost per completed searchRealized revenue per search and repeat usage

The signed-pilot, 50+, and 53% figures are founder-reported early signals and should be supported by raw agreements, signup exports, and widget data during diligence; they are not presented as audited traction.

Market and entry wedge
08

Existing demand, focused entry

A large European intent market, entered through DACH shopping.

vuve does not need to become the merchant. It monetizes qualified discovery inside an established commerce and retail-media budget pool.

76.7MGerman comparison-site visits / monthPublic June 2026 traffic estimate across idealo.de, geizhals.de, billiger.de, and guenstiger.de.
€842BEuropean B2C e-commerce2024 turnover context across 38 European countries.
€28.8BEuropean retail media2028 forecast: the adjacent budget pool for measurable shopping intent.
DEPrimary commercial wedgeLarge comparison habit and published CPC benchmarks.
AT + HUExpansion and operating proofAustria extends the DACH motion; Hungary validates fast localization and operations.
01GermanyPrimary market
02AustriaDACH reuse
03HungaryOperations testbed
04Further EURepeatable playbook

Sources: Ecommerce Europe / EuroCommerce; IAB Europe Retail Media Hub; Similarweb public June 2026 traffic pages for idealo.de, geizhals.de, billiger.de, and guenstiger.de. Figures are market context, not vuve revenue.

Business model
09

Partner-funded demand

A simple CPC model with a testable unit equation.

The first economic hypothesis combines an observed shopper-action signal with a public German CPC benchmark. Realized billing and acquisition cost are the launch proof.

Observed early signal53%Partner-action rateFounder-reported observation on the live widget; sample and event definition require diligence support.
×
External benchmark€0.51Published German CPCidealo standard CPC benchmark, effective 1 Apr 2025, excluding VAT.
=
Modeled output€0.27Revenue potential / searchA scenario input—not realized vuve revenue and not yet a validated acquisition ceiling.
Demand spend scales only after measurement
Realized net revenue per completed search>Blended acquisition + AI cost per search
Validated by the public 90-day scorecard

CPC benchmark: idealo Listing Kosten & Konditionen. Core revenue mechanics already implemented: tracked click-out, prepaid partner balance, billing ledger, invoices, attribution evidence, and partner analytics. No current revenue is claimed.

Go to market and defensibility
10

Three compounding loops

Supply, distribution, and trust reinforce each other.

The wedge is not one chatbot feature. It is a transparent decision network that becomes more useful as local supply and expert workflows deepen.

01

Supply loop

Prepared claims and feed-led onboarding add more eligible products, prices, locations, and partner alternatives.

5-minute feed connection
02

Distribution loop

SEO guidance, margin-gated paid acquisition, and embedded partner advisors create multiple paths into the same shopping graph.

Potential low-CAC partner channel
03

Trust loop

Visible criteria, catalog evidence, disclosed sponsorship, and reviewed operations are designed to support repeat usage and partner confidence.

Evidence compounds
Shopping is the initial wedge.Once the country playbook and trust layer work, the same decision architecture expands to services, activities, events, and special offers—higher-frequency local intent without diluting the first proof.
Founder-market fit
11

Built the hard parts before

Retail systems, AI platforms, search, and consumer product execution.

Beni Kovacs

Beni Kovacs

Founder · retail systems and AI platforms

PhD in Quantum Computing and Machine Learning in Austria. Built management and intelligence systems used in real retail operations. At Scale AI, deployed enterprise AI infrastructure across Azure, GCP, and on-premise environments.

Balazs Kemenes

Balazs Kemenes

Founder · AI search and product engineering

Head of Engineering at Superlinked, the Index Ventures-backed AI-search company. Researched and shipped search infrastructure, built platforms from zero to production, and brings more than a decade of product engineering.

Retail operationsReal systems used for 7+ yearsEnterprise AILarge-scale deployment experienceConsumer appsPrior Hungarian app-chart leadersAI searchProduction search and ranking depth

Founder biographies and historical achievements are founder-supplied and should be supported with employment, education, product, and ranking evidence during diligence.

The ask
12

SAFE · 18-month runway

€500K turns a working product into repeatable market proof.

The round is designed to validate economics, partner supply, retention, and a repeatable country-launch motion—not to discover whether the product can be built.

€500K
Pre-seed SAFE · disciplined 18-month plan
3 marketsGermany, Austria, and Hungary operating with localized supply.
~500 / marketTarget active partner supply by the end of runway.
≥€20K MRRAbout 74K searches/month at the modeled €0.27—not yet realized economics.
Measured unitsRealized revenue, AI cost, acquisition cost, and repeat usage per search.

Use of funds

Marketing + demand
30%
Staffing + exceptions
30%
Models + product
25%
Infrastructure
10%
Contingency
5%
Marketing spend is gated by measured contribution margin. Staffing focuses on partner and quality exceptions. Model investment moves suitable workloads toward lower-cost, controllable open-weight paths and hardens visual AI.

All end-of-runway figures are targets, not current performance. The detailed planning ramp appears in the appendix.

Closing
13

The category opportunity

Europe needs a shopping layer it can trust.

Transparent decisions for shoppers. Fair, measurable access for merchants. European control over the intelligence layer that connects them.

Try vuve live ↗Watch Design Studio ↗Book a meeting ↗
Execution risk is lowerThe customer product, partner workflows, billing mechanics, embedded advisor, and operations cockpit already exist.
The partner wedge is unusually lightAn existing feed can enter the system in minutes, with measurable click-out economics instead of a bespoke integration.
The long-term position is largerShopping proves the trusted decision layer; local services, activities, and events expand frequency after the model works.
Appendix · financial planning
14

Planning scenario

The 18-month path clears the €20K MRR milestone.

A staged ramp lets the company validate supply, search economics, and retention before increasing acquisition.

MRR path from public launch

Month 3
€1.5K
Month 6
€4K
Month 9
€8K
Month 12
€12K
Month 15
€17K
Month 18
€22K
1

Validate before scaling

Replace benchmark-derived revenue assumptions with realized billing, attribution, and invalid-click data.

2

Build repeatable supply

Reach partner density market by market, measuring activation, catalog quality, and renewed budgets.

3

Earn retention

Track repeat commercial searches and whether transparent guidance creates durable consumer behavior.

This is a founder planning scenario, not a forecast supported by historical revenue. The month-18 path reaches €22K MRR, clearing the headline ≥€20K milestone.

Appendix · competition
15

A distinct operating model

vuve combines advice, local supply, partner economics, and accountable operations.

Alternative
Where it is strong
vuve wedge
Price comparison
Traffic, merchant familiarity, prices, broad catalog coverage.
Conversational need discovery, visible criteria, expert guidance, and a mobile-first decision flow.
Global search / marketplaces
Scale, identity, logistics, attention, and massive graphs.
Local partner workflows, European control, transparent evidence, and measurable referral economics.
Generic AI assistants
Broad knowledge, fluent conversation, and fast feature iteration.
Structured partner catalogs, current offers, category skills, product tables, maps, billing, and visual product composition.
Merchant chatbots
On-site context and direct access to the shopper.
Shared shopping intelligence, partner-scoped supply, cross-market expertise, and a full customer + partner + operator platform.
Directories / maps
Local discovery and geographic coverage.
Guided decisions that combine constraints, schedules, availability, expert questions, and comparable offers.

The claim is not that incumbents cannot add chat. The defensible path is the combined local catalog graph, partner activation layer, decision evidence, operating automation, and trusted European positioning.

Continue the conversation
16

From deck to product

See the decision layer in action.

Explore the live vuve experience, or book time with the founders to discuss the product, market entry, and this pre-seed round.

Try vuve now ↗ Book a founder meeting ↗
Both links open in a new tab · vuve demo access is protected
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