Fundle.ai: How Fundle's ConsentFirst Powers DPDP Compliant Loyalty Data Platform

Why DPDP Compliance Is a Loyalty-Specific Crisis, Not a Generic IT Problem

Most enterprise IT teams frame DPDP compliance as a data governance project — classify your data, map your flows, appoint a Data Protection Officer, and update your privacy policy. That framing works for an HR system or a CRM tool used internally. It fails catastrophically for a loyalty program, because loyalty data is simultaneously the most personal, the most commercially exploited, and the most consumer-facing category of data in retail.

Consider what a single loyalty profile at a Phoenix Marketcity-style mixed-use mall actually contains: name, mobile number, email, date of birth, vehicle registration (for parking integrations), transaction history across 80+ brands, visit frequency, food court preferences, cinema booking history, and in newer deployments, geolocation dwell data from the mall's Wi-Fi or BLE beacon network. Each of these data attributes was collected under a different interaction context. The DPDP Act requires that the purpose stated at collection time precisely matches the processing activity — you cannot use cinema preference data to send a jewellery offer from Tanishq unless the member explicitly consented to cross-category marketing.

This is not an edge case. It is the core business model of mall loyalty. And it is precisely why generic CMPs — tools built for cookie consent on websites — are architecturally inadequate. A web CMP captures a browser-level consent signal. It has no concept of a POS transaction, a WhatsApp campaign, an SMS-based OTP enrolment, or a brand-specific data-sharing agreement between a mall operator and a brand like Lenskart or Cafe Coffee Day. The consent taxonomy for loyalty is an order of magnitude more complex.

Operators who have deployed point solutions from players like EasyRewardz or Capillary for their loyalty engine, and then attempt to layer a generic consent tool on top, face a painful reality: the consent data and the loyalty data live in separate systems with no real-time synchronisation. A member who withdraws consent for promotional communications at 11 PM on a Tuesday will still receive a campaign SMS at 10 AM Wednesday because the suppression signal never reached the campaign scheduler. That is a DPDP violation. The only structural fix is a consent-native loyalty architecture — which is what Fundle's ConsentFirst delivers.

Features of Fundle ConsentFirst CMP: Purpose-Built for Retail Loyalty

ConsentFirst is not a repurposed cookie banner tool. It was architected from the ground up as a consent management plane for loyalty-grade personal data, with five capabilities that no generic CMP offers.

First, purpose-layered consent capture. At enrolment — whether at a Reliance Trends billing counter, a Lifestyle store kiosk, or a D2C app signup — ConsentFirst surfaces a structured consent UI that separates at minimum six consent purposes: transactional communications, promotional marketing, cross-brand data sharing, analytics profiling, third-party partner marketing, and location-based services. Each purpose is independently toggleable. The underlying data schema stores not just the boolean yes/no but the exact consent text version shown, the channel, the timestamp, and the device or terminal ID. This creates the specific, informed, freely given consent record that the DPDP Act demands.

Second, real-time consent propagation. When a member updates a preference — say, opting out of third-party brand marketing while keeping transactional alerts active — that signal propagates across the Fundle AI Platform in under 200 milliseconds. The campaign scheduler, the data-sharing API, and the analytics pipeline all receive the updated consent state before the next processing event. This eliminates the dangerous lag that plagues bolted-on consent tools.

Third, consent-aware data tokenisation. Personal identifiers are tokenised at ingestion. Analytics and campaign tools operate on pseudonymised tokens. Raw PII is decrypted only when a consent-verified, logged business action requires it. This means that even if a campaign vendor or a brand partner is compromised, the exposed data is not directly re-identifiable — reducing both regulatory exposure and reputational damage.

Fourth, multi-modal consent withdrawal. Members can withdraw or modify consent through any channel: the loyalty app, a WhatsApp bot, a toll-free IVR, an in-store staff terminal, or a self-service kiosk. Every withdrawal path writes to the same ConsentFirst vault. There is no scenario in which a member who has withdrawn consent continues to receive processing that depends on that consent.

Fifth, DPO-ready audit exports. The Data Protection Officer tooling in ConsentFirst allows a retail chain's DPO to pull a full consent history for any individual member or any cohort in under 90 seconds, formatted as a structured JSON or PDF report suitable for regulatory submission. For a mall operator potentially managing 20 lakh loyalty members, this is not a nice-to-have — it is the difference between a manageable regulatory inquiry and a multi-week operational crisis.

Ensuring Transparent User Consent Collection Across Every Channel

The DPDP Act's requirement for 'clear and plain language' consent notices is harder to operationalise than it sounds when you are running 80+ brand stores in a single mall, each with its own billing system — a mix of POSist-powered F&B counters, Petpooja terminals at food courts, Wondersoft POS at fashion anchors, and GoFrugal systems at pharmacy outlets. Each terminal has a different UI, a different operator skill level, and historically a different consent flow. ConsentFirst solves this through a headless consent API that any POS system can call, rendering a standardised, brand-templated consent screen regardless of the underlying billing software.

Transparency in the DPDP context means three specific things. One, the member must understand what data is being collected. Two, they must understand why each category is being collected. Three, they must understand who it will be shared with. ConsentFirst's consent notice builder — accessible to mall operators and brand managers through the Fundle AI Platform dashboard — allows customisation of the plain-language notice text while enforcing a compliance template that has been reviewed against the DPDP draft rules. Brands cannot accidentally create a notice that omits the mandatory disclosure elements.

For digital channels, ConsentFirst integrates directly with WhatsApp Business API flows and app onboarding screens. A customer enrolling in the Manyavar loyalty program via WhatsApp, for instance, receives a structured consent card that mirrors the in-store consent taxonomy — same six purposes, same language, same withdrawal mechanism. The mobile number becomes the consent identity anchor, and all subsequent channels (email, push, SMS) inherit the consent state validated at enrolment.

One of the most underappreciated transparency requirements under DPDP is the obligation to notify members when consent purposes change — for example, when a mall operator signs a new data-sharing agreement with a fintech partner for EMI offers. ConsentFirst automates this through what the platform calls Consent Change Notifications: templated push or WhatsApp messages that inform affected members of the new data use, present a fresh consent toggle, and record the outcome. Brands that have historically just updated their privacy policy URL and called it done will find this requirement non-negotiable under the Act.

Seamless Integration with Loyalty and POS Systems at Scale

One of the structural weaknesses of India's organised retail loyalty ecosystem is its extraordinary fragmentation at the technology layer. A single mall operator might have 60+ brand stores running six different POS platforms, three different loyalty engines, two different app providers, and a WhatsApp Business solution layer that was bolted on during COVID. For a consent management infrastructure to work, it must function as a horizontal plane across all of these — not as yet another silo.

ConsentFirst's integration architecture is built on three layers. The first is the POS Connector Library — pre-built, certified integrations with the major Indian POS platforms including POSist, Petpooja, GoFrugal, and Wondersoft. These connectors handle the consent UI rendering at the billing terminal, the real-time consent API call, and the response handling — all within the transaction flow without adding perceptible latency. Store staff do not need to understand consent management; the terminal guides them through a standardised interaction.

The second layer is the Loyalty Engine Middleware. Fundle's Fundle Brand Loyalty and Fundle Mall Loyalty modules natively consume consent state from ConsentFirst. For operators running a third-party loyalty engine — Capillary, EasyRewardz, or a custom-built solution — ConsentFirst exposes a webhook-based event stream that pushes consent state changes in real time. This means a brand on any loyalty platform can enforce consent-gated campaign execution without re-platforming.

The third layer is the Campaign Channel Adapter. ConsentFirst maintains a consent-verified suppression list that is pushed via API to connected campaign platforms. Whether a brand's marketing team sends campaigns through MoEngage, WebEngage, or Xeno, the suppression list ensures that no outbound communication reaches a member who has not consented to that specific communication purpose. The Fundle Agentic AI layer adds an additional check: AI Agents that orchestrate multi-step campaigns automatically validate consent state at each step of the journey, not just at the initial trigger. This eliminates the scenario where a member consents to transactional messages, receives a campaign journey trigger, and then gets promotional messages three steps later because the journey logic did not re-check consent mid-flight.

How Fundle solves this

Fundle was built on a foundational belief that first-party data is only as valuable as the trust it was collected with. Vineet Narang's vision for the Fundle AI Platform was never to build another points-and-rewards engine — it was to build the consent-native data infrastructure that makes loyalty genuinely valuable to members and genuinely defensible for operators. ConsentFirst is the most visible expression of that thesis.

The Fundle Loyalty Platform, encompassing both Fundle Mall Loyalty for multi-brand mall environments and Fundle Brand Loyalty for single-brand or multi-channel retail chains, has consent management woven into every data flow. There is no way to create a member profile, execute a campaign, share data with a brand partner, or run an analytics cohort without a valid consent record gating that action. This is not a compliance layer sitting on top of the product — it is the product's foundational data model.

Fundle AI Agents, the autonomous orchestration layer within Fundle Agentic AI, add a dimension that no legacy loyalty platform or standalone CMP can match. These agents monitor consent state across the entire active member base in real time, proactively identifying members whose consent is approaching expiry, whose withdrawal signals are ambiguous, or whose data usage has drifted beyond the originally consented purpose. The Fundle AI Workflow then triggers the appropriate re-consent or suppression action without requiring manual DPO intervention. For a mall operator managing 20 lakh members across multiple city assets, this level of automation is not optional — it is the only way to maintain compliance at operational scale.

ConsentFirst is already deployed across 123+ malls supporting 270+ brands' data privacy, making it the largest consent infrastructure deployment in Indian organised retail. The brands and operators on the platform — spanning fashion anchors, F&B operators, entertainment venues, and pharmacy chains — benefit from a shared consent technology investment that would cost multiples of the Fundle platform fee to build and maintain independently. For a CMO at a mid-sized retail chain spending ₹15-20 crore annually on loyalty program operations, the alternative to a platform like Fundle is not just a technology build cost — it is a ₹250 crore penalty exposure that no CFO will accept once the DPDP rules are formally notified. The question for India's retail leadership is not whether to invest in a DPDP compliant loyalty data platform. It is how quickly they can close the gap between where they are today and where the law requires them to be.