Introducing aana

Every guest, every photo,
before they leave.

AI face-matching on a portable edge box. WhatsApp delivery during the event. Works with no Wi-Fi. Built for Tier-2 and Tier-3 India.

<30%
of event guests ever receive their photos
800M+
Indians in Tier-2/3 cities and towns
Zero
incumbents solve offline + hostless events
scroll

The problem

The photos exist. They just never arrive.

You go home from a 500-person event. Someone photographed you. You will never see that photo.

Every function in India generates thousands of photos. A portion land on one person's phone. The rest vanish. The tools that exist sell to professional photographers and require stable internet. They solve the wrong problem for the wrong customer in the wrong place.

<30%
of event guests receive photos of themselves, per industry estimates
#1
delivery channel preference is WhatsApp, not email or shared drive
0
of the major incumbents work reliably at venues with weak or no internet

The solution

aana: photographic memory for your gathering

"At your event, everyone's phone photos get pooled, sorted by face on a box we bring, and every guest gets their own photos on WhatsApp before they reach home, even with no Wi-Fi."

The name is Malayalam for elephant. Elephants remember everything. That is what aana does for every gathering, large or small, with or without a professional photographer.

Step 01
Pool and ingest

Guests upload phone photos to a local Wi-Fi hotspot. The operator's edge box ingests them with no internet needed.

Step 02
Face-match on-device

ArcFace embeddings run locally on the edge appliance. Every face is clustered and tagged in real time, entirely offline.

Step 03
Deliver via WhatsApp

Guests register by selfie or QR. Their album arrives on WhatsApp before the event ends. Consent-first, DPDP-clean.

Market landscape

A crowded category with a large unclaimed gap

The photographer-SaaS market is a red ocean. The white space is the no-photographer small gathering, the bad-connectivity venue, and the hyperlocal operator relationship.

PlayerPositioningGap we exploit
PremagicEvent-marketing platform; face delivery at large events (GITEX, 2000+)Enterprise only no small hostless gatherings
KwikpicPhotographer SaaS; AI face recognition; VC-backed; ₹849–₹29,990/yrNeeds internet post-event sharing, not live
Memzo / Foto Owl / PhotomallSelfie/QR face delivery for weddingsPhotographer-led no-photographer events ignored
SamaroWhatsApp bot; targets Tier-2/3 and real-time explicitlyDirect rival must out-execute on edge + local trust
aanaEdge-first, offline-capable, operator franchise networkOur wedge hostless events + no Wi-Fi + local trust

The beachhead is not weddings (incumbents own that) but community mid-size events: temple festivals, school annual days, college fests, association functions, milestone birthdays. High guest count, no professional photographer, strong demand, and no one serving it well.

Business model

Operator-led. Three clean revenue lines.

Local operators buy or lease the edge kit, pay a monthly platform fee, and keep the host fee in their territory. The company's marginal cost per event collapses to WhatsApp delivery and cloud storage.

Event host
Pays per event

The person hosting the birthday, festival, or function pays the operator a flat fee. Clean single transaction, aligned incentive.

Guest upsells
Optional keepsakes

HD downloads are free. Photobook (Rs.499 to Rs.1,499), private vault (Rs.99 to Rs.199), AI highlight reel. Company captures 30% of upsell revenue. Upside, not a pillar.

Event sizeHost priceNotes
Small (up to 75 guests)Rs.999 to Rs.1,999Birthdays, anniversaries, small functions
Mid (75 to 250 guests)Rs.2,499 to Rs.4,999Community, school, college, association events
Large (250 to 1000+ guests)Rs.5,000 to Rs.15,000Weddings; competes on real-time + reliability
Operator platform feeRs.2,500/monthUnlimited events; covers cloud + delivery + platform

Unit economics

Per-event P&L: company-run vs. franchise

Cost line50 guests250 guests1,000 guests
Edge appliance amort.Rs.90Rs.120cloud-burst
Venue connectivity (5G)Rs.75Rs.100Rs.150
Cloud-burst GPU--Rs.600
WhatsApp deliveryRs.25Rs.125Rs.500
Cloud gallery (90 days)Rs.20Rs.40Rs.120
Payment gateway (2%)Rs.30Rs.80Rs.240
Operator time on-siteRs.450Rs.750Rs.2,000
Total cost (company-run)Rs.690Rs.1,215Rs.3,610
Indicative host priceRs.1,499Rs.3,999Rs.12,000
Contribution (company-run)Rs.809Rs.2,784Rs.8,390
Company marginal cost (franchise)~Rs.75~Rs.245~Rs.860

In the franchise model the operator absorbs kit, time, and connectivity. Company marginal cost collapses to WhatsApp + cloud + gateway. Platform fee and kit margin are near-pure contribution at scale.

Edge appliance

The field box: two configs for every operator tier

Real-time face detection (RetinaFace/SCRFD) and embedding (ArcFace via InsightFace, ONNXRuntime-GPU) benefits materially from a GPU. Two validated configurations cover the range.

Config A
Pro Edge Box
~Rs.1,40,000 all-in
Mid and large events, up to 300 guests / 3,000 photos
CPURyzen 5 8600G (Zen 4)
GPURTX 4060 8GB (or 3060 12GB)
RAM32GB DDR5
Storage1TB NVMe + 2TB archive
PowerMains / inverter
Compute only~Rs.98,000
Config B
Lite Edge Box
~Rs.70,000 all-in
Small events up to 150 guests, runs off a power bank
ComputeJetson Orin Nano Super 8GB
Performance67 INT8 TOPS, 7 to 25W
Storage1TB NVMe (M.2)
Power20,000mAh USB-PD bank
Key advantageWorks at venues with no power
Compute only~Rs.53,000

Startup capex (self-built software path)

Subsequent operator kits are not company capex; operators buy or lease them, and aana earns ~Rs.16k to Rs.20k margin per kit.

1x Pro kit (founder demo)
Rs.1L to Rs.1.4L
First unit for live proof-of-concept events
2x Lite kits (seed operators)
Rs.1.4L to Rs.1.9L
First two franchisee units to validate operator playbook
DPDP / legal
Rs.50k to Rs.1.5L
Privacy policy, consent templates, operator DPAs
Brand + web
Rs.20k to Rs.50k
Identity, landing page, operator collateral
Infra + working capital
Rs.1.8L to Rs.3.6L
Backend infra buffer, marketing seed, contingency
Total startup capex
Rs.4.9L to Rs.9L
Software built in-house (Next.js + Neon/Postgres + Drizzle). Agency path adds Rs.3L to Rs.8L.

5-year financial model

Adjust the drivers. See the P&L.

The model is most sensitive to operator count and upsell take-rate. Pull the sliders to stress-test the base case.

Year 5 operator target 350
Operators active at end of Year 5
Events per operator / month 10
Mature operator; ramp factor applied in early years
Platform fee / operator / month Rs.2,500
Monthly SaaS fee charged to each operator
Company upsell income / event Rs.250
aana's 30% share of guest keepsake revenue per event
Year 5 Revenue
-
total annual
Year 5 EBITDA
-
operating profit
Year 5 Margin
-
EBITDA %
Break-even
-
first profitable year
Line (Rs. lakh) Year 1Year 2Year 3Year 4Year 5

Figures in Rs. lakh (1L = Rs.100,000). Operator ramp: 6% / 21% / 57% / 77% / 100% of Year 5 target at year-end. Event ramp factor applied as operators mature. Team cost scales with operator count and year. All figures illustrative; validate against live vendor quotes and market conditions.

Go-to-market

Four phases from zero to network

The crowdsourcing intent is preserved as a franchise network. Local people, local hustle, asset-light scaling — biometric matching stays on company-controlled infrastructure.

Phase 0
Validate
0 to 3 months
1 town, founder-run

Use existing Immich setup (already does face recognition and shared albums). Take the home server and a 5G hotspot to 3 to 5 real events. Measure two numbers: guest download rate and host willingness to pay Rs.1,499. Zero build cost until those numbers are proven.

Phase 1
Seed
3 to 9 months
1 to 2 districts, 5 to 10 operators

Build consent flow, WhatsApp delivery, operator app, host dashboard. Recruit first operators from people who saw the product work at a real event. Standardise the kit and playbook. Prove operator economics.

Phase 2
Expand
9 to 24 months
1 state, 50 to 75 operators

Channel partnerships with event decorators, caterers, and tent/sound houses who already sell to every function in town. Revenue share for bundling. Viral loop: real-time delivery creates the WhatsApp-share moment; every shared photo drives the next host enquiry at near-zero CAC.

Phase 3
Network
24 months onward
Multi-state, 150 to 350+ operators

Cloud-burst GPU for large events. Regional micro-PoPs as volume justifies. Each operator becomes a node in a distributed edge compute network — the foundation for the long-term infrastructure play described in the next section.

Network growth

One town seeds the next

Each operator proves the model locally, then refers adjacent towns. Local trust compounds faster than any ad spend.

Phase 0
1 operators active
Phase 0
Validate
1 town, founder-run. 1 to 2 operators.
Phase 1
Seed
1 to 2 districts. 5 to 10 operators.
Phase 2
Expand
1 state. 50 to 75 operators.
Phase 3
Network
Multi-state. 200 to 350 operators.

Long-term vision

From photo memory to distributed compute

The event photo product is the wedge. The real long-term value is the operator network itself: bonded local operators in every Tier-2 and Tier-3 town, each running a standardised edge appliance, each earning a living from the network.

01
Now
Event photo delivery

The core product. Operators run edge appliances at gatherings. aana earns platform fees, kit margin, and upsell share. Operators build a recurring local business. Every event is a proof point for the network's reliability and reach.

02
Next
Edge services platform

As operator count grows, the appliances in the field represent meaningful distributed compute capacity. Each node is already capable of local inference, storage, and delivery. The platform layer evolves to expose that capacity to adjacent use cases: local AI inference, edge CDN, IoT data aggregation.

03
Future
Distributed Tier-2/3 infrastructure (Dhara thesis)

A network of 300+ operator-run edge nodes across India's smaller cities and towns becomes a different kind of asset: distributed storage and compute built into the fabric of communities that hyperscalers do not reach. The operator earns from events today and from node revenue tomorrow. aana's moat is not the software feature; it is the trusted human network and the hardware footprint that took years to build.

DPDP compliance

Facial data handled right is a marketing edge

DPDP Rules 2025 notified November 2025, phased rollout through May 2027. Facial data requires specific, informed, free, and unambiguous consent at collection. Penalties up to Rs.250 crore. Incumbents are vague on this — aana makes compliance a visible differentiator.

🔒
Consent at capture

QR/selfie pre-registration is the consent moment. Plain-language notice, distinct parental-consent flow for guests under 18 (relevant at birthday parties).

🎯
Purpose limitation

Faces processed only for this event's delivery. No reuse across events. No cross-event profiling. Face templates deleted when the gallery expires, default 90 days.

🗑
Deletion by default

Auto-purge on gallery expiry. Deletion-on-request built from day one. Auditable consent and deletion logs.

🔒
Controlled matching

Face matching runs on company-controlled infrastructure only. Biometric data never distributed to uncontrolled operator nodes. Franchisees bound by Data Processing Agreements.

🛡
Security posture

Images and templates encrypted in transit and at rest. Role-based access controls. Security review budgeted before Phase 2 launch.

📋
SDF watch

As volume grows, Significant Data Fiduciary obligations may apply. Compliance review scheduled ahead of Phase 2 expansion.

Key risks

What needs to be true for this to work

RiskSeverityWhy it mattersMitigation
Commoditised core featureMediumIncumbents already do face-matched deliveryCompete on edge/offline + hostless segment + local trust, not the feature itself
Low ARPU at small gatheringsMediumRs.999 to Rs.1,999 per event is thin at single-unit levelFranchise model shifts cost to operators; upsells and platform fee are higher-margin lines
DPDP liabilityHighBiometric data, children present, Rs.250Cr penalty ceilingConsent-at-capture, purpose limitation, auto-deletion, DPAs, controlled matching stack
Connectivity at venuesMediumWhatsApp delivery requires uplink at some pointEdge box processes locally offline; delivery queues and fires when connectivity is available
Operator quality and churnHighNetwork reputation depends entirely on operator executionStandard kit + playbook, operator certification, delivery metrics monitored centrally
Samaro out-executes on Tier-2/3MediumDirect competitor already targeting the same wedgeEdge offline capability and bonded operator network are harder to replicate than a WhatsApp bot

90-day validation plan

Prove willingness-to-pay before committing capital

You do not need to build anything new to test demand. The existing Immich setup already does face recognition and shared albums.

01
Run 3 to 5 real events

Take the current home server and a 5G hotspot to real gatherings. A family function in Aryanad is an ideal first one. Zero build cost.

02
Pool and face-group

Collect phone photos from guests, run Immich face grouping, hand each guest a retrieval link. Measure how many actually open and download.

03
Measure two numbers

Guest download rate (engagement signal) and whether the host would have paid Rs.1,499 (willingness-to-pay signal). Both must be clear yes before building.

04
Then build, in order

Only if hosts say yes: consent flow first, then WhatsApp delivery, then operator playbook. Not the other way around.

This is a network business, not a single-unit cash cow. Its value is as a franchise-able operator network or as a wedge into distributed edge infrastructure. Prove the 90-day demand signal before committing real capital.

aana — ആന

The elephant
never forgets.
Neither do we.

A network of local operators. An edge appliance at every gathering. Every guest gets their photos. Every town becomes a node. This is the long game.

Get in touch
aana / SnapHome  ·  Prepared June 2026  ·  Working draft for venture evaluation
Illustrative figures only. Validate against live vendor quotes before committing capital.
DPDP compliance obligations should be confirmed with a qualified legal advisor.