AI-first
Face recognition automatically groups every photo by guest.
ShaadiShots helps photographers and event professionals organize, identify, and deliver event photos using AI-powered technology and QR-based guest photo discovery.
Investor deck: coming soon
ShaadiShots is a self-hosted desktop application for wedding and event photographers. It automates the most time-consuming part of the job — organizing thousands of photos and getting each guest their own pictures — using AI face recognition and QR-code guest galleries. It is built and operated by KumawatPulse Technologies Pvt Ltd, Jaipur, Rajasthan, India.
Face recognition automatically groups every photo by guest.
Photos and face data never leave the photographer's computer.
Guests open their gallery by scanning a QR code — no app, no account.
Galleries are built as photos are imported, so they are ready during the event.
Each guest sees only their own photos.
One-time setup fee during early access — ₹49 in India, $0.99 elsewhere.
Large events create a huge amount of photos — and a huge amount of manual work to organize and deliver them.
These are the problems we observe in the market; we will add validated customer examples as real case studies become available.
One workflow from camera to guest — entirely on the photographer's own computer.
A photographer creates an event and imports photos from a camera or memory card. ShaadiShots runs on the photographer's own computer.
Photos are analyzed locally with AI face recognition. Every face is detected and photos of the same person are grouped automatically — in real time as photos are imported.
Each guest is given a personal gallery containing every photo they appear in. No app or account is needed to view it.
Every event gets a unique QR code. Guests scan it with their phone and land directly on their own gallery.
Guests can view and download the photos from their personal gallery, directly in the browser.
Several long-running trends have recently converged, making an on-device AI photo workflow practical and timely.
Face recognition and image understanding are now reliable enough to run on a photographer's own hardware, which has not been true until recently.
Guests expect to see and share event photos on their phones immediately — not weeks later on a disc or a slow gallery.
Weddings and large events routinely produce thousands of images per event, making manual sorting impractical.
Scan-to-open is a familiar, friction-free interaction for audiences in every market we target.
Couples, families and event organizers increasingly value same-day photo delivery as part of the event experience.
Photographers are actively moving from manual, file-folder workflows toward software that automates delivery.
Market statistics: we intentionally do not quote market-size numbers here until we can cite a verified source for each. Placeholders will be filled with sourced figures: [Add verified statistic + source].
We size the opportunity bottom-up, transparently, so the assumptions are visible and testable. Figures below are placeholders until verified sources are added.
| Input / assumption | Value | Source |
|---|---|---|
| Number of professional wedding / event photographers worldwide | [Add verified figure] | [Source] |
| Average annual spend on photo delivery software per photographer | [Add verified figure] | [Source] |
| TAM ≈ photographers × annual software spend | [Add verified figure] | Calculated from the inputs above |
| Input / assumption | Value | Source |
|---|---|---|
| Photographers in target markets (India first, then English-speaking) | [Add verified figure] | [Source] |
| Share reachable with the current desktop-only product | [Add verified assumption] | [Source] |
| SAM ≈ target-market photographers × average software spend | [Add verified figure] | Calculated from the inputs above |
| Input / assumption | Value | Source |
|---|---|---|
| Realistic early-years customer acquisition (events / photographers) | [Add verified assumption] | Team estimate — state the basis |
| SOM ≈ customers × average revenue per customer in early years | [Add verified figure] | Calculated from the inputs above |
ShaadiShots is available today on Windows, with a 7-day free trial, no credit card required. macOS and Linux builds are in progress.
Detects and groups every face in every photo, automatically.
One QR code per event; guests open their own gallery in the browser.
Galleries are built as photos are imported — ready during the event.
Each guest sees and downloads only their own photos.
Processing and storage are local; no cloud upload of client photos.
Events can be published with a shareable link for guests beyond the venue.
Product screenshots: real product screenshots of the event workflow (create event → upload → AI processing → QR → guest gallery) will be added by the team. [To be added]
The core insight: AI photo organization runs on the photographer's own hardware, removing cloud upload, storage bills, and privacy concerns in one move.
Local face detection and grouping across large photo sets.
AI runs on the photographer's computer — no photo uploads required.
Scan-to-open galleries that work without an app or account.
Local backend + browser frontend on a single install.
Cryptographically signed license tokens validate activation and offline use.
Shareable event links for guests outside the venue when enabled.
Described at a high level; internal architecture and security details are shared under NDA with qualified investors.
Guests create usage; photographers and events generate revenue.
Current pricing: during early access, ShaadiShots has a one-time setup fee of ₹49 in India or $0.99 elsewhere, with no per-event fees during early access. Confirmed future pricing will be published here. [To be updated]
An objective comparison. Competitor capabilities are marked as "Varies" where they differ by product; we do not claim specifics we have not verified.
| Capability | Traditional Workflow | Generic Gallery Platform | ShaadiShots |
|---|---|---|---|
| AI face-recognition photo organization | — | Varies | Yes — automatic grouping by guest |
| QR-code guest access, no app/account | Varies | Varies | Yes |
| Personal gallery per guest | Manual | Varies | Yes |
| Real-time grouping during the event | — | Varies | Yes — as photos are imported |
| Photos stay on the photographer's computer | Yes (files) | Usually no (cloud) | Yes — self-hosted |
| Wedding/event workflow focus | Manual | Partial | Yes — purpose-built for events |
Upload, AI organization, and guest delivery happen in a single workflow — no stitching together multiple services.
Client photos never leave the photographer's machine. That is a defensible, verifiable difference.
A QR scan opens the gallery. Lower friction means guests actually use it.
Real-time grouping means galleries are ready during the event, not weeks later.
Early-access pricing is a one-time fee — no subscription, no per-gigabyte storage bills.
Designed around the wedding/event workflow rather than adapted from general cloud storage.
We publish only verified operational figures. The fields below are placeholders that will be replaced as real, auditable numbers become available.
Additional metrics we will track as they become verifiable: trial-to-paid conversion, retention, customer acquisition channels, and geographic mix.
This is the intended growth loop, not a guaranteed network effect. We will validate each step with real usage data before claiming it.
These are planned channels; we will publish which ones actually drive verified acquisition.
Software delivery with no physical distribution — but scaling is not free, and we are explicit about the costs.
Digital download and installation — no physical logistics, per-unit cost near zero.
Compute runs on the photographer's hardware, keeping marginal AI cost low.
A single product serves many independent photographers and events.
Weddings and events exist everywhere; the product is language-adaptable.
Real constraints: AI processing (compute) costs, storage and bandwidth for large events and public galleries, infrastructure for public URLs, and customer support scale with usage. We model these explicitly in our projections rather than assuming unlimited scalability.
These metrics matter to us. We will not publish numbers we have not measured.
| Metric | Status | What is needed to populate |
|---|---|---|
| CAC — Customer Acquisition Cost | Data required | Needs spend + conversions from marketing channels |
| ARPU — Average Revenue Per User | Data required | Needs verified paying users and revenue |
| AOV — Average Order/Event Value | Data required | Needs confirmed event pricing and mix |
| Gross Margin | Data required | Needs verified infrastructure + support costs |
| LTV — Customer Lifetime Value | Data required | Needs retention data |
| LTV : CAC | Data required | Computed from the figures above once available |
Illustrative projections for planning only. These are scenarios, not actual revenue and not guarantees of outcomes.
Formula: paying events × average revenue per event. Inputs and assumptions will be documented and shared with qualified investors.
Investment amount to be discussed with qualified investors.
We will share the specific round size, terms, and use-of-funds details with qualified investors under appropriate agreements.
Proposed allocations, not final. These will be refined with the board and investors before any raise.
| Category | Proposed allocation | Includes |
|---|---|---|
| Product & Engineering | 40% | AI infrastructure, product development, mobile/web improvements, performance, security |
| AI Infrastructure | 25% | Model processing, compute, storage, optimization |
| Marketing & Growth | 20% | Photographer acquisition, content, partnerships, international expansion |
| Operations & Team | 15% | Engineering, sales, customer success, operations |
Labels as proposed allocations — final percentages subject to founder and investor agreement.
Plans, not guarantees. Progress will be reported against these goals.
Weddings and events are a global market. We are not claiming penetration anywhere — this is our planned expansion strategy.
Large wedding market, high photo volumes per event, and the product is priced and designed for it.
US, UK, Canada, Australia — photographers already pay for delivery tools.
Middle East, Southeast Asia, Europe — based on what phases 1 and 2 validate.
We do not hide risk. A credible plan names what could go wrong.
Competition from established gallery platforms and free cloud tools
AI processing and storage costs rising with photo volume
Customer acquisition costs in a seasonal, word-of-mouth market
Privacy and face-recognition regulation varies by country
Seasonal demand concentrated around wedding seasons
Photographer adoption depends on trust in a small vendor
Rapid change in AI tooling could make parts of the stack obsolete
Infrastructure scaling for large events and public galleries
This list is illustrative and will be expanded as the business evolves.
Investor deck coming soon.
We will link the real deck here once it is finalized. Request access through the form below or by emailing investors@kumawat.co.in.
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Information presented on this page is provided for informational purposes only and does not constitute an offer to sell or a solicitation of an offer to purchase securities. Any investment opportunity, if available, will be subject to applicable laws, definitive documentation, eligibility requirements, and applicable regulatory requirements. Statements about the product, market, and strategy are forward-looking, based on the company's current expectations, and subject to risk and uncertainty. Figures marked as placeholders are not verified data. Nothing on this page is a promise of returns or profitability. This wording should be reviewed by qualified legal counsel before publishing.