New Delhi [India], September 1 : AvenuesAI Limited is entering a new phase of its evolution. While digital payments remain the company's core operating and financial engine, management is increasingly focused on building higher value businesses around the infrastructure, merchant relationships and transaction ecosystem created over the years.
At the centre of this strategy are Transaction Intelligence Score (TISco), AvenuesAI's expanding applied AI capabilities, and the repositioning of Rediff as a digital distribution and enterprise technology platform.
In its Q1 FY27 earnings call, Chairman and Managing Director Vishal Mehta described the emerging identity of the company as an "AI-first fintech infrastructure company that started with payments." The distinction is important. AvenuesAI is seeking to build additional layers of monetisation on top of a scaled payments franchise. Payments provide transaction infrastructure and merchant relationships; with appropriate consent, transaction activity can generate commercially relevant signals; and AI can potentially transform those signals into intelligence, products and new revenue streams.
The following discussion brings together key themes from the Q1 FY27 earnings call and a subsequent interaction with CMD Vishal Mehta, focusing on how management sees this strategy developing.
Q1. AvenuesAI has traditionally been identified with payments. What is the broader investment thesis today?
A: Payments remain the foundation of AvenuesAI. They provide scale, merchant relationships, technology infrastructure and cash generation.
What is changing is how we think about the value that can potentially be created around that foundation. Historically, the primary economic model was linked to processing transactions. We now see an opportunity to progressively build additional capabilities around that transaction ecosystem. With appropriate merchant consent and governance, transaction activity can provide useful signals about how businesses are actually operating. AI can help interpret those signals and potentially turn them into commercially relevant intelligence. The longer term investment thesis is therefore not about replacing the payments business. It is about building higher-value layers on top of payments.
Q2. Where does Transaction Intelligence Score, or TISco, fit into that strategy?
A: TISco is one of the clearest examples of what we mean by building intelligence around transactions.
Traditional financial information often provides a historical or periodic view of a business. Transaction activity can potentially add another dimension by providing insight into actual commercial behaviour. For example, transaction patterns may help identify business activity, continuity, changes in momentum, customer behaviour and other operating characteristics. With appropriate consent and governance, these signals can potentially contribute to a richer understanding of a merchant. The objective of TISco is to explore whether this transaction intelligence can be transformed into a useful and explainable decision-support layer for financial institutions and other participants in the ecosystem.
Q3. Why could this be particularly relevant for small and thin-file merchants?
A: This is potentially one of the most interesting use cases. India has a large population of small and emerging businesses that may have genuine commercial activity but relatively limited formal borrowing histories. Conventional credit information may therefore provide only part of the picture. Transaction behaviour can potentially help address part of this information asymmetry because it reflects actual economic activity.
A business may have a limited credit file but still demonstrate consistent transaction activity, business continuity and operating momentum. TISco is intended to explore whether these consented signals can help financial institutions better understand such businesses. If successful, that could potentially support more informed underwriting and expand the universe of merchants that lenders are able to evaluate effectively.
Q4. Is TISco intended to compete with or replace conventional credit scores?
A: No. We see TISco as complementary rather than substitutive. Existing credit scores and bureau information remain important components of the financial system. Transaction intelligence can potentially provide an additional perspective. The opportunity is particularly relevant where conventional information alone does not capture the full operating picture of a business.
For AvenuesAI, TISco is strategically important because it brings together capabilities that already exist within the ecosystem: payments infrastructure, merchant relationships, consented transaction signals and AI. If we can successfully commercialise that combination, the economics become interesting because the company could progressively create value not only from processing a transaction, but also from the intelligence that can be derived around transaction behaviour with appropriate consent. That represents a potentially different value layer from the traditional payments model.
Q5. There is enormous investment going into AI globally. Where does AvenuesAI believe it can differentiate?
A: We do not intend to compete in the capital-intensive global race to build hyperscale AI infrastructure or foundational models. Our opportunity is much more applied. We believe valuable AI applications will increasingly depend on the combination of models, domain knowledge, proprietary or permissioned data and clearly defined commercial problems.
AvenuesAI operates within a payments and merchant ecosystem where AI can potentially be applied to real-world financial and enterprise use cases. Our differentiation therefore should not be measured simply by whether we have an AI model. It is whether we can combine AI with relevant data, distribution and domain expertise to solve problems customers are prepared to pay for. The proposed merger of our wholly owned AI subsidiary Neuromind (PhroneticAI) into AvenuesAI is intended to bring AI talent and technology directly into the parent company and more closely integrate AI development with the payments, transaction-intelligence and enterprise businesses.
Q6. Beyond TISco, where else do you see near- to medium-term AI opportunities?
A: We are working on several applied AI opportunities, including Small Language Model applications and PrivateGPT. PrivateGPT is aimed at enterprises, including financial institutions, that want to use generative AI with proprietary or sensitive information while retaining greater control over where their information resides and how it is used. Our broader philosophy is that enterprise AI will increasingly need to be secure, domain-specific and integrated into actual business workflows.
These businesses are still in the investment and commercialisation phase. We have indicated that it could take approximately nine to eighteen months for the newer AI initiatives to begin contributing meaningfully to revenue. Investors should therefore view AI as a medium term growth engine, rather than assuming a significant near term earnings contribution.
Q7. Where does Rediff fit into the broader AvenuesAI strategy?
A: Rediff gives us an additional digital distribution and technology platform. The strategy is to build upon Rediff's existing digital presence while developing new businesses around RediffOne, RediffPay and RediffTV.
RediffOne is being developed as an integrated enterprise technology and productivity ecosystem. The objective is to progressively bring together enterprise capabilities including communication, commerce and other business productivity applications under a unified platform. RediffPay is being developed as a UPI-led consumer payments offering, while RediffTV is being positioned as a non-linear digital video and streaming platform. Each business addresses a different opportunity, but collectively they broaden the surfaces through which AvenuesAI can distribute technology, payments and digital services.
Importantly, RediffPay has not been included in FY27 guidance. Consequently, successful commercialisation would represent an incremental opportunity rather than something investors need to assume in order for the company to meet its existing financial expectations.
Q8. Could Rediff eventually become an important distribution layer for AvenuesAI?
A: Absolutely. That is an important part of the strategic rationale. One of the challenges technology companies face is distribution. Rediff provides AvenuesAI with an established digital platform on which new products and services can potentially be introduced over time. RediffOne gives us an enterprise facing platform, RediffPay provides an opportunity in consumer payments, and RediffTV creates another consumer engagement surface.
We are taking a measured approach. The objective is not to launch multiple disconnected businesses. It is to progressively create an ecosystem where payments, enterprise technology, AI and digital distribution can reinforce one another.
Q9. With investment going into AI, Rediff and international expansion, how do you prevent the strategy from diluting profitability?
A: Capital allocation discipline is extremely important to us. The core payments business is profitable and cash-generative, and we intend to protect that foundation.
A. Our approach is to selectively reinvest a portion of incremental earnings into areas where we believe there is potential to create meaningful long-term enterprise value- particularly AI, transaction intelligence, product development and international expansion. At the same time, we have established profitability guardrails, including maintaining a floor EBITDA margin while funding strategic initiatives.
The FY27-FY29 objective is therefore not simply to maximise earnings in any single year. It is to continue growing the core business while investing in opportunities that can potentially create additional engines of earnings over the medium term. We want to emerge from this investment cycle with a larger underlying business, a stronger earnings base and meaningful new AI-led revenue streams.
Q10. What milestones should investors watch over the next few quarters to determine whether the strategy is working?
A: Investors should focus on execution rather than simply the number of initiatives we announce. There are several milestones that matter. For TISco, the key will be progress from product development and validation towards commercial deployment and adoption. For the broader AI portfolio, investors should watch customer deployments, commercial use cases and ultimately revenue contribution. For Neuromind, the important measure will be how effectively its AI capabilities become integrated with AvenuesAI's existing businesses.
For Rediff, investors should watch the commercial development of RediffOne and the rollout and adoption of RediffPay and RediffTV. And throughout this process, the performance and cash generation of the core payments franchise remain fundamental. The strategic framework can be expressed quite simply: Payments create scale and merchant relationships.
Consented transaction activity can create signals. AI can convert those signals into intelligence. Intelligence can enable new products and revenue streams. Rediff can provide additional distribution for technology and digital services. That is the transition we are working towards. AvenuesAI's next phase is an attempt to compound the value of the payments franchise by building intelligence, AI applications and additional distribution around assets the company has developed over many years. If we execute successfully, the opportunity is to evolve from primarily monetising payment processing into a broader AI led financial technology and digital infrastructure platform with multiple potential layers of monetisation.