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Twimbit AI Radar (APAC)#3

A roundup of innovative enterprise deployments and announcements.

Summary

This edition of Twimbit AI Radar (APAC) highlights India’s progress in AI and how businesses are reshaping industries and unlocking new growth opportunities. Here, we aim to cover the development of Artificial Intelligence across nations, rather than by sectors such as telecoms or banking.

In our previous Twimbit AI Radar (APAC)#2 on different Malaysian industries, we covered Malaysia’s key industry leaders – from Telecom Malaysia maximising the potential of artificial intelligence chatbots to FGV Holdings transforming its operations with Palm Oil Mill Integrated System (POMIS).

Introduction

As India strives for its ambitious USD 5 trillion GDP target by 2025, AI technology is projected to contribute USD 957 billion by 2035. The India AI Mission also aims to propel artificial intelligence developments over the next 5 years with a budget of USD 1.3 billion.

The mission has allocated over 552 crores for the fiscal year 2024-2025. However, the journey has hurdles, including a significant digital divide and a shortage of over 800,000 intelligent systems developers. These challenges drive creative solutions, particularly in tier-2 and tier-3 cities, which are emerging as dynamic hubs for AI innovation.

Practo unveils advanced AI-powered healthcare

As India’s leading digital healthcare platform, Practo offers 4 key technologies.

  • Predictive Health Analytics: Analyze patient data to identify health trends and personalized care plans early with a heart health yield of up to 90% accuracy compared to traditional methods at 56% accuracy
  • AI Symptom Checker: Analyze symptoms to guide patients toward appropriate healthcare services
  • AI-Powered Health Records Management: Offers healthcare providers immediate access to comprehensive patient histories for improved diagnostics and decision-making
  • Enhanced Telemedicine Services

Designed to enhance patient care and streamline services, these innovations empower patients and healthcare providers with real-time insights and seamless access to care.

How is it ranked?

💎 Organisational Impact ●●●●◐

🛠️ Ease of Deployment ●●●◐○

🛡️ Safety & Trustworthiness ●●○○○

Commentary

The improvement in heart health accuracy from 56% to 90% showcases significant direct economic value with reduced costs and improved patient outcomes. As highlighted in Practo’s FY 2024-25 annual report, the integration of artificial intelligence has driven a 90% reduction in adjusted negative EBITDA.

This results in enhanced financial health, optimized resource allocation, and robust long-term growth potential. Additionally, the profitability of its core business has achieved a CAGR of 68%, underscoring substantial business outcomes and operational excellence.

Paytm deploys (pi) for smarter fraud prevention

Paytm Intelligence (Pi) is Paytm’s latest fraud risk management platform powered by artificial intelligence with 2 core capabilities.

The Centralized Fraud Detection Hub

  • Connects data signals from multiple customer interactions into one integrated decisioning centre
  • Uses artificial intelligence and machine learning to provide enhanced pattern recognition, allowing organizations to identify and mitigate fraud risks in real time

Unlike traditional methods, Pi’s Centralized Fraud Detection Hub aggregates diverse data points to improve fraud detection accuracy and minimize false positives.

The Advanced Anomaly Detection Suite

  • Strengthens fraud prevention through data ingestion, a sophisticated rules and modelling engine, and real-time simulations
  • Enables businesses to track unusual patterns, conduct in-depth case management, and enhance fraud resilience

Paytm Intelligence empowers secure digital operations through a unified and intelligent fraud management platform that underscores Paytm’s commitment to advancing digital safety on a global scale.

How is it ranked?

💎 Organisational Impact ●●●●●

🛠️ Ease of Deployment ●●●●◐

🛡️ Safety & Trustworthiness ●●◐○○

Commentary

Paytm’s Pi fraud detection platform has significantly enhanced operational efficiency, processing five billion rule evaluations and 500 million decisions daily. According to PayPay Corporation, this advanced capability has led to a remarkable reduction in fraud to 0.0005%, far below the industry average.

Decision-making speeds are now 2X faster than the industry average, which typically falls within the range of 100-200ms​. This scalability allows it to be adopted across businesses of various sizes, showcasing its ability to support rapid growth. As a result, Paytm’s market share has expanded across emerging markets, leading to enhanced revenue growth and market presence.

Flipkart deploys AI-driven personalization and operations

AI
Sources:How Flipkart is using Artificial Intelligence (www.hireddigital.com)

As India’s largest e-commerce platform, Flipkart has deployed a series of advanced algorithm-driven solutions such as Mira and its ultimate experience chatbot.

Generative Artificial Intelligence Virtual Assistant (Mira)

  • Offers personalised recommendations and resolves issues throughout the shopping journey with real-time support.
  • Ability to predict and customise responses has increased cart additions by ~12%, reducing return rates and enhancing the overall shopping experience.

Decision Assistant Chatbot

  • Utilises natural language processing (NLP) and a large language model (LLM) to understand customer intent.
  • Deliver relevant, personalized responses and empower users to make informed purchasing decisions.

In addition to customer support, Flipkart has deployed Demand Prediction to optimise its logistics and supply chain operations.

Demand Prediction

  • Leverages AI in time series analysis to accurately forecast product demand, improve inventory management, and ensure timely product delivery.
  • Classify and identify addresses with 98% accuracy and reduce delivery time by at least 3 hours per hub.
  • Minimize stockouts and overstock situations to enhance overall service efficiency.

Flipkart’s Fraud Detection system also uses X-ray scanning technology to analyze returned products, ensuring they match original specifications and preventing losses from counterfeit returns. Flipkart Utkarsh (meaning ‘excellence’) also supports its 100,000 registered sellers in enhancing overall product quality.

How is it ranked?

💎 Organisational Impact ●●●●●

🛠️ Ease of Deployment ●●●●○

🛡️ Safety & Trustworthiness ●●●○○

Commentary

Flipkart’s innovation has transformed its e-commerce operations, delivering tangible results across various facets of its business. The Mira assistant has driven a 12% increase in cart additions, significantly boosting revenue. Additionally, a three-hour reduction in delivery time underscores the company’s operational efficiency gains. Their strategic approach closely aligns with evolving e-commerce trends — from customer interaction to logistics optimization. The system’s ability to manage diverse functions and maintain 98% address accuracy demonstrates exceptional data quality management and scalability. As a result, Flipkart is positioned as a comprehensive e-commerce artificial intelligence integration leader.

Byju deploys AI innovations to transform educational experiences

As India’s leading edtech (education + tech), Byju provides personalized learning for students in India and beyond. Their latest innovation – the Byjus Wiz platform- aims to revolutionize educational experiences for all.

Sources: How Byju works (Opencell)
  • BADRI
  • Assess students’ learning patterns and identify challenge areas where they may struggle with specific concepts.
  • Use knowledge tracing to predict future performance and proactively recommend resources to address learning gaps.
  • Provide continuous support to students and ensure they stay on track.

    MathGPT
  • Leverage advanced machine learning algorithms to provide precise step-by-step solutions to complex problems.
  • Utilise visual aids and analogies to break down intricate concepts for students to easily understand and engage with mathematical content.

    TeacherGPT
  • Provide personalized guidance, adapt to various learning styles, and assist in grading student responses.
  • Ensure the learning process remains dynamic and tailored to each student’s pace.
  • Bridge gaps in understanding and provide targeted feedback.

Trained on vast datasets from millions of student interactions, the platform scored an accuracy rate of ~90%, highlighting how Byju has created an optimized, personalized learning experience for each user.

In addition to these models, Byju leverages technologies powered by Generative Artificial Intelligence, including ChatGPT, to enhance content creation. This allows for dynamic, real-time generation of educational materials that align with students’ evolving needs, keeping content fresh and highly relevant.

Byju also strongly emphasises safety and ethical standards in artificial intelligence deployment. The company has implemented strict guardrails to ensure operations within safe limits, focusing on augmenting teachers’ roles rather than replacing them. This ensures that human interaction remains central to learning while leveraging the potential of automated and intelligent systems for enhanced support and personalization.

How is it ranked?

💎 Organisational Impact ●●●●◐

🛠️ Ease of Deployment ●●●◐○

🛡️ Safety & Trustworthiness ●●●●○

Commentary

Byju has set a benchmark in personalized learning, achieving 90% accuracy in tailoring content to individual needs, showcasing strong data quality management and effective algorithm implementation.

Integrating multiple artificially intelligent models (BADRI, MathGPT, and TeacherGPT) also reflects a strategic alignment with their commitment to ethical considerations for artificial intelligence in education . Furthermore, strict guardrails ensure artificial intelligence models are used as an enhancement tool instead of a replacement, demonstrating thoughtful governance and stakeholder consideration towards the role of teachers.

CropIn Drives smarter farming with advanced AI solutions

CropIn is an agri-tech firm optimizing farming practices through automation-driven solutions – CropIn Intelligence Platform and CropIn Sage – focusing on predictive analytics, field intelligence, and generative machine learning.

Centred on revolutionising agriculture, these deployments aim to optimize crop management, enhance yield outcomes, and drive sustainable farming practices.

Sources: Smart farming in practice (Cropin)

CropIn Intelligence Platform

The platform leverages over 22 AI models to deliver predictive analytics and actionable insights, helping farmers optimize crop management practices. Key features include:

Predictive Analytics

  • Aids in crop detection, yield estimation, irrigation scheduling, pest and disease prediction, and nitrogen uptake analysis.
  • Empower farmers to make data-driven decisions with a proven accuracy of 92% in crop detection and yield benchmarking.
  • Ensures precision in assessing crop health and potential outputs.

Field-Level Intelligence

  • CropIn Intelligence enables farmers to monitor crop health, identify water stress, and receive early warnings about potential pest infestations.
  • Assist in resource use optimization and improve yield outcomes.
Sources: An overlay of Cropin Sage intelligent architecture cloud solution (Cropin)

CropIn Sage

CropIn Sage is a breakthrough in agricultural technology, touted as the world’s first agri-intelligence platform powered by Generative Artificial Intelligence. Key capabilities include:

  • Grid-Based Mapping: Sage converts agricultural landscapes into detailed, grid-based maps (ranging from 3×3 meters to 5×5 kilometres), allowing stakeholders to visualize agricultural data globally and make more precise decisions.
  • Natural Language Processing (NLP): The platform incorporates NLP to allow users to query the system in their native language, translating queries into SQL commands for fast data retrieval. This feature significantly enhances user accessibility, especially for farmers with limited technical knowledge.
  • Comprehensive Crop Insights: Initial insights cover 13 key crops (wheat, rice, potato, and maize) for nearly 80% of the world’s food demand. Sage provides in-depth insights into cultivation practices, irrigation needs, climate conditions, and soil health. This enables stakeholders to make informed, strategic agricultural decisions.

These deployments demonstrate CropIn’s commitment to leveraging machine intelligence technology for smarter, more sustainable agriculture. By providing actionable insights, real-time data, and accessible tools, CropIn can help farmers improve productivity and resilience, ultimately driving greater efficiency in the agricultural sector.

How is it ranked?

💎 Organisational Impact ●●●●●

🛠️ Ease of Deployment ●●●◐○

🛡️ Safety & Trustworthiness ●●◐○○

Commentary

Cropin’s platform demonstrates remarkable economic potential with 92% accuracy in crop detection, covering 13 key crops that account for 80% of global food demand. This highlights the platform’s strong data management capabilities and its direct impact on agricultural productivity.

The grid-based mapping system (ranging from 3×3 meters to 5×5 kilometres) also showcases impressive scalability and technical expertise in managing complex agricultural data.

Additionally, the platform’s ability to process and analyze vast datasets while delivering insights through natural language processing reflects a keen focus on enhancing stakeholder experience and improving the ecosystem — especially in agriculture, where users’ technical expertise varies widely.

Ola leverages AI to improve passenger safety and experience

Sources: Ola to roll out guardian features in more markets across India and Australia for platform safety (Olacabs.com)

Focusing on safe and convenient transportation, Guardian is the next big step for India’s e-ride hailing service.

Currently, Guardian is located across 16 Indian cities and Perth, Australia, with plans to expand to more cities in the upcoming quarter. Key features include:

  • Real-time data on rides to automatically detect irregular trip activities, including prolonged stops and unexpected route deviations.
  • Ola’s 24/7 safety response team promptly contacts the customer and driver to confirm safety and provide assistance if necessary.
  • An emergency button in the app that alerts police and loved ones in real-time.

Built using artificial intelligence and machine learning, Guardian continuously learns from millions of data points to enhance risk detection and ensure timely intervention. This deployment enhances Ola’s existing safety initiatives, including the emergency button, facial recognition for driver authentication, and an OTP system.

The introduction of Guardian is a great step in Ola’s commitment to providing a secure and reliable transportation experience

How is it ranked?

💎 Organisational Impact ●●●●◐

🛠️ Ease of Deployment ●●●●○

🛡️ Safety & Trustworthiness ●●●○○

Commentary

Ola’s real-time monitoring and automatic detection of irregular trip activities across 16 cities highlight its strong scalability and robust data management. The system’s seamless integration with emergency services and immediate alert mechanisms demonstrates exceptional operational risk management.

On top of that, Ola has successfully balanced user privacy with safety features, showcasing a strong commitment to ethical considerations. This is reflected by its excellent data lifecycle management that utilises continuous learning from millions of data points to enhance risk detection.

Transformative Impact on India’s Industries

New heights of innovation, operational efficiency, and customer experiences – this is the magic that AI unlocks for India’s industries today. For instance:

Healthcare – Predictive analytics like Practo’s autonomous intelligent systems have improved diagnostic accuracy by over 34%, setting new standards for patient care.

E-commerce – Flipkart’s artificial intelligence-powered logistics and personalization tools have optimised operations, cutting delivery times by 3 hours and increasing consumer engagement by 12%.

Banking – Paytm’s fraud detection platform that leverages artificial intelligence has significantly reduced fraud rates, ensuring enhanced digital transaction security.

The contribution of artificial intelligence to India’s GDP is also expected to be $450 to $500 billion by 2025, accounting for 10% of the country’s overall GDP as its applications across sectors are proving indispensable.

As it stands, the adoption of intelligent, autonomous systems has shown remarkable progress. However, companies must always remember to focus on creating a balance between leveraging advanced technology and addressing organizational readiness.

Critical steps to achieve this include strengthening partnerships with technology providers, fostering internal capabilities, and building frameworks to scale AI solutions. Moving beyond, tailored strategies that align with business goals and seamless integration with legacy systems will be essential for long-term success. This journey promises to transform industries, create lasting value, and drive India’s economic future in the age of intelligence.

Appendix

Use Case Prioritization Criteria

  • Organisation Impact
    • Direct & indirect economic value (incl. revenue gains, cost savings, increase in productivity)
    • Experiential benefits (business processes and stakeholder experience)
    • Strategic fit/alignment to company priorities (in line with industry trends)
    • Efficiency, engagement, and ecosystem improvement (twimbit 3Es – internal and external stakeholders)
  • Ease of deployment (impacting time and cost)
    • Data availability & quality (data lifecycle management)
    • Interoperability/Integration with existing systems (reusability of use cases)
    • Technical and business expertise needs (domain knowledge, machine learning understanding, need for training/hiring)
    • Infrastructure requirement (hardware & software like cloud computing, AI development & training, deployment & execution)
    • Documentation & support accessibility and adequacy (solution design from internal and external resources)
    • Scalability (with minimal operational process disruptions)
  • Safety and Trustworthiness
    • Regulatory compliance (linked to high-exposure business areas)
    • Ethical considerations (need for new governance in place)
    • Operational risk (performance issues, system failure, integration breakdown)
    • Reputational risk (brand impact, public perception)
    • Technological risk (vendor lock-in, tech maturity, cybersecurity)

Scoring Methodology

Each main criterion in our framework is evaluated using a scoring scale from 1 to 5, where 1 signifies a very low organisation impact or ease of deployment, and 5 signifies a very high organisation impact or ease of deployment. To calculate the overall score for each criterion, we use an average approach, where each sub- dimension (i.e., direct & indirect economic impact or regulatory compliance) is assigned a rating of low, medium, or high. The threshold is slightly skewed towards the lower range as the scoring of each sub-dimension will be accounted for in the final score (e.g., each sub-dimension is given a low rating).

Note that the scoring range and threshold will be inversed for the last criterion (Safety and Trustworthiness), whereby a low rating is more favourable.

These ratings are determined based on a thorough analysis of the use case’s potential benefits and challenges, informed by secondary research. The final score for each criterion is the sum of the weighted ratings of its sub-dimensions, providing a nuanced and precise evaluation of the use case.

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