Рубрика: AI

Setu by Pine Labs has introduced an agentic bill-payments experience on December 9. According to the company’s press release, it is designed to simplify how consumers track and pay their monthly bills.

Pine Labs is an API-enabled technology platform which offers digital public infrastructure solutions across payments, data and insights.

The new system tackles two of the biggest pain points in bill payments: the fear of wrong charges and the worry of missing due dates.

Most consumers spend only minutes paying a bill but hours tracking them each month. Setu’s new assistant automates that work by fetching every bill, checking for irregularities and ensuring payments are made on time.

“India’s digital public infrastructure has transformed how we pay, but the work behind monthly bills has remained manual. This agentic experience brings automation and trust together, giving people a smarter, safer way to handle their bills,” B Amrish Rau, CEO of Pine Labs, mentioned.

The system runs only on rules set by the user, ensuring that it never pays the wrong bill or crosses spending limits.

Meanwhile, earlier this year, Pine Labs and India’s private sector J&K Bank sought to revolutionise credit issuance in India by introducing a tech-first RuPay Credit Card for the bank’s customers.

The RuPay Credit Card can also be linked to UPI for seamless credit transactions. Developed using Pine Labs’ credit issuance platform Credit+, this integration will also enable seamless processing of pre-sanctioned credit lines on UPI.

Previously, SBI Payments and Pine Labs have also strengthened their long-standing relationship with an expanded strategic alliance, deepening a partnership that has already spanned 12 years. SBI Payments—a joint venture between State Bank of India, the country’s largest commercial bank, and Hitachi Payment Services—together with merchant commerce platform Pine Labs, currently powers more than two lakh digital checkout points across India.

With this renewed collaboration, the two companies aim to accelerate the use of digital payments and digital commerce solutions nationwide.

The focus will be on creating a smoother, more reliable checkout experience across a wide range of payment methods.

By bringing together SBI Payments’ extensive distribution network and robust acceptance infrastructure with Pine Labs’ merchant-focused innovations and comprehensive solution stack, the alliance is expected to enhance merchant capabilities and help drive sales growth significantly.

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Across India, this winter carries an unsettling undertone. With the festive season underway, along with the changing weather patterns, pollution levels have surged again across most of northern India. The National Capital Region, like every year, seems to be recording the worst numbers in its count of pollutants.

Delhi provides the most vivid warning of what this trajectory leads to. After Diwali and the crop burning season, the capital once again slipped into the ‘Severe’ and ‘Severe Plus’ AQI categories.

Several zones recorded PM2.5 levels above 450 and some touched 500. Visibility dropped, schools issued advisories and hospitals saw a jump in respiratory cases. This cycle has become so predictable that it is now considered part of Delhi’s seasonal rhythm.

Even urban centres once considered relatively breathable, like Bengaluru, are now showing worrisome signs of deterioration.

The city is experiencing a form of air stagnation, where polluted air stays trapped close to the surface, blocking sunlight and causing a deeper, unnatural dip in temperature.

Bengaluru’s air quality this winter has seen a sharp decline, with early December recording some of the city’s highest pollution levels of the season. The city witnessed its worst spike on December 7, when the AQI hit 161, falling into the “unhealthy” category and marking the highest reading during the period over the last five years (graph below).

While pollution levels eased slightly after this peak, dropping back toward the 80–100 range, the early-winter surge highlights a worrying trend: Bengaluru, during winter, is increasingly experiencing significant pollution episodes that resemble those typically associated with northern Indian cities.

Air purifier sales across urban India reflect this rising fear. Retailers report a sharp increase in demand in the weeks following pollution spikes. Popular electronics retailer Croma reported a 30% increase in the year-on-year sales of air purifiers across its online and offline channels.

According to IQAir’s 2024 assessment, India remains one of the world’s top five most polluted countries, with six of the 10 most polluted cities globally located here. Toxic air cuts more than three years off the average Indian’s life expectancy.

Despite the scale of the crisis, India’s air monitoring infrastructure has not kept pace. Most cities still rely on only one or two official AQI stations, leaving vast gaps in understanding how pollutants move across complex urban microclimates.

This gap in measurement is one of India’s biggest blind spots. As Amit Banka, founder and CEO of WeNaturalists, says, “AI models using satellite-derived intelligence can virtually sense pollution in areas without physical sensors, creating a scalable virtual monitoring network.” WeNaturalists is a global ecosystem empowering professionals and organisations working with nature with digital solutions.

Banka’s observation highlights a growing consensus among climate scientists that the problem in India is not the absence of data, but the absence of consistent, connected data capable of informing real-time governance.

How Can AI be Leveraged?

A 2024 study by Kuldeep Singh Rautela & Manish Kumar Goyal, published under Scientific Reports in the Nature journal, backs this urgency with hard evidence. Researchers used an AI/ML model, a convolutional autoencoder to forecast PM2.5 levels across India, even in regions with little to no ground monitoring. The model’s accuracy was unexpectedly high, with error margins under 10 µg/m³ and structural-similarity scores above 0.60, proving that AI can generate reliable pollution forecasts even when India’s sensor network falls short.

Rautela & Goyal warn that India’s AQI infrastructure is too sparse to capture true exposure levels, and that AI-driven forecasting is no longer optional; it is essential if cities like Bengaluru want to avoid the “Delhi trajectory.”

“India’s official monitoring network is geographically limited,” says Banka, adding that AI can override these limitations by combining historical data with real-time satellite imagery.

Professor A Damodaran of IIM Bangalore, believes this is where India must act decisively. Ease of driving is being prioritised over ease of breathing, he told AIM.

It is perhaps the clearest articulation of the dysfunction at the heart of India’s pollution problem. Traffic police prioritise vehicle movement. Pollution boards prioritise emissions reporting. Neither system is designed to work with the other.

AI offers the glue that India’s institutions have long lacked. According to Damodaran, India’s biggest pollutant is still suspended particulate matter produced by older vehicles, autorickshaws and trucks.

AI-powered camera-vision systems can already identify which types of vehicles pass through a junction and which ones are likely contributing disproportionately to particulate spikes. When correlated with traffic flow, such systems can recommend rerouting traffic in polluted corridors before the exposure becomes hazardous.

This shift is already visible in the startup ecosystem. Momentum Capital, which invests in climate and deep-tech ventures globally, sees AI as central to the next phase of environmental governance. Founder and managing partner Ankur Shrivastava says they are bullish on AI-led climate solutions that go beyond diagnostics and build mitigation tools, “from smart traffic-flow systems to industrial emission control.”

Shrivastava points out that scaling these systems requires navigating difficult regulatory terrain. “Air-quality startups must navigate a complex policy ecosystem, which is why we prioritise founders who can build teams capable of operating across regulatory environments.”

The future of urban environmental intelligence in India looks increasingly agentic. Banka believes, “India is moving toward agentic AI systems that will not just alert officials to smog, but automatically trigger interventions like rerouting traffic, or activating suppression systems.”

These systems can eventually power climate digital twins for major metros, giving decision makers the ability to run simulations that forecast the impact of electrifying buses, restricting construction dust or restructuring traffic before policies are implemented.

The Centre for Research on Energy and Clean Air analysis published a study last month that claimed that across 60% of Indian districts, “exposure to significant air pollution is not restricted to winter alone as is commonly believed.” The report noted that expanding the ground-monitoring network nationwide is essential.

India can no longer treat air quality as an episodic, wintertime inconvenience. The pollution crisis is structural, shaped by rapid urbanisation, weak monitoring, fragmented governance and climate volatility.

The post What If AI Can Monitor the Air You Breathe? appeared first on Analytics India Magazine.

India has moved closer to creating a formal royalty regime for artificial intelligence (AI) developers, with a government committee recommending a blanket licensing system for training models on copyrighted work.

The Department for Promotion of Industry and Internal Trade (DPIIT) has released a working paper on December 8 to that effect. The proposal marks a significant policy move on generative AI and copyright protection.

The eight-member committee, chaired by Himani Pande, an additional secretary at DPIIT, was tasked with assessing the adequacy of India’s copyright law in addressing AI-driven use of creative works.

The committee sides firmly with creator remuneration and rejects the push by tech firms for unrestricted text and data mining (TDM).

Safeguards Against Exploitation

The paper noted that India’s creative economy, spanning films, arts, music, digital content and informal folk traditions, contributes significantly to GDP and livelihoods and therefore requires strong safeguards against unremunerated AI exploitation of human-created works.

India is among the world’s fastest-growing AI markets and a major consumer base for generative AI systems.

The paper noted that the tech sector, led by industry body Nasscom, supported an opt-out rights framework. The Business Software Alliance, whose members include Google, Microsoft, Amazon Web Services, IBM, Salesforce and OpenAI, also argued for explicit TDM exceptions with opt-out provisions.

The proposal directly challenges the data practices of companies such as Google and OpenAI, which rely heavily on large-scale scraping of online material to train their models.

Google and OpenAI did not reply to emails sent by AIM seeking comment.

Content industry bodies such as broadcasters, music labels and creator organisations opposed the opt-out approach, arguing that it disproportionately benefits large platforms.

In a LinkedIn post, Kriti Sharma, director (regulatory, legal and compliance, India and Southeast Asia) at Dun and Bradstreet, said the proposal reflects an attempt to reconcile competing realities. “It feels like India is trying to reconcile two truths. AI needs data to grow. Creators need protection to survive,” Sharma said. She added that the paper approaches the question “thoughtfully, boldly, and practically.”

Rakesh Umarani, partner at Vidyam Legal, said the hybrid model offers a balanced pathway. “A clear licensing and royalty framework could prevent future disputes and give creators real confidence while allowing AI development to continue responsibly,” Umarani said.

After examining global developments and contrasting stakeholder submissions, the committee rejected a blanket text-and-data mining (TDM) exception, widely supported by technology firms, stating that allowing such an exception “would undermine copyright” and “leave human creators powerless to seek compensation.”

Hybrid Licensing System Proposed

The committee recommended a hybrid system allowing AI developers to train on “all lawfully accessed copyrighted works” as a matter of right, but with mandatory royalty sharing through a government-designated non-profit collective formed by rights holders.

Under this framework, creators will not have the option to withhold their works from AI training but will receive statutory remuneration.

Royalties would be administered through a single-window mechanism, the Copyright Royalties Collective for AI Training (CRCAT), with a government-appointed committee determining rate structures. Even non-members would be eligible for payments upon registering their works.

The proposal aims to reduce transaction costs, provide legal certainty, widen access to copyrighted datasets, mitigate AI bias and hallucinations, and create a level playing field between large platforms and startups.

Burden of Proof

Under the proposed framework, if a copyright owner alleges that their work was used to train an AI system without paying royalties, the law will presume the claim is valid unless the developer can prove otherwise.

Even though the blanket licence system gives developers little reason to hide training data, disputes may arise, for example, when a developer claims that only proprietary or separately licensed data was used.

In such cases, the burden of proof shifts to the AI developer, who must demonstrate that no third-party copyrighted material was used. Until they do, the presumption favours the copyright holder, it stated.

The working paper has now entered a 30-day public consultation phase.

The post India Moves to Regulate AI Training by Google, OpenAI appeared first on Analytics India Magazine.

Microsoft has announced a $17.5 billion investment in India over four years (2026–2029) to expand cloud and AI infrastructure, skilling programmes and ongoing operations.

This marks the company’s largest investment in Asia. This is in addition to the $3 billion announced earlier in 2025.

The announcement followed Microsoft chairman and CEO Satya Nadella’s meeting with Prime Minister Narendra Modi ahead of the company’s India AI tour. Microsoft said the new investment is aligned with three priorities — scale, skills and sovereignty.

The tech giant has also doubled its commitment to equip 20 million Indians with AI skills by 2030. Through its ADVANTA(I)GE India initiative, the company claims to have trained 5.6 million people since January 2025 and enabled over 125,000 individuals to secure jobs or pursue entrepreneurship opportunities.

“Had a very productive discussion with Mr. Satya Nadella. Happy to see India being the place where Microsoft will make its largest-ever investment in Asia,” posted PM Modi in a post on X.

He further said that the youth of India will harness this opportunity to innovate and leverage AI to build a better planet.

Union Minister for Electronics & IT Ashwini Vaishnaw said the investment signals India’s rise as a reliable technology partner for the world and will support the country’s move from digital public infrastructure to AI public infrastructure.

Puneet Chandok, president of Microsoft India and South Asia, said the company aims to translate India’s AI ambitions into “impact for every citizen.” He added, “Building on the $3 billion investment announced in January 2025, our new $17.5 billion commitment and deep partnership across India’s technology ecosystem are focused on turning India’s AI ambition into impact for every citizen.”

Expansion of AI and Cloud Infrastructure

A significant part of the investment will support the India South Central cloud region in Hyderabad, scheduled to go live in mid-2026. Microsoft said this will be its largest hyperscale region in the country, comprising three availability zones. The company will also expand existing regions in Chennai, Hyderabad and Pune.

Microsoft’s existing 22,000 employees across Indian cities contribute to product development, engineering, AI research and datacenter operations, the company noted.

AI Integration Into Public Platforms

The company also announced new AI integrations for the Ministry of Labour and Employment’s e-Shram and National Career Service (NCS) platforms. The initiative aims to benefit more than 310 million informal workers by supporting multilingual access, AI-assisted job matching, predictive analytics and automated resumé generation through Azure OpenAI Service.

It said that e-Shram, built on Microsoft Azure, has already helped expand social protection coverage in India from 24% in 2019 to 64% in 2025, according to ILO estimates.

Sovereign Cloud Offerings

The company also introduced Sovereign Public Cloud and Sovereign Private Cloud for customers in India. These offerings include Sovereign Landing Zones, governance controls, and support for connected and disconnected operations through Azure Local.

Additionally, Microsoft 365 Copilot will begin processing data within India by the end of 2025 for sectors requiring in-country data compliance.

Microsoft stated that its expanded infrastructure, AI adoption support and skilling programmes will help build a national ecosystem for “innovation, trust and opportunity,” positioning India to advance its AI capabilities at a population scale.

The post Microsoft Commits $17.5 Bn to Advance India’s AI Ambition appeared first on Analytics India Magazine.

The Linux Foundation has announced the formation of the Agentic AI Foundation (AAIF), backed by Anthropic, Block and OpenAI. Other members include Amazon Web Services, Bloomberg, Cloudflare, Google, and Microsoft.

The new foundation aims to provide a neutral, open governance structure for the emerging ecosystem of agentic AI systems. The AAIF brings together tools and standards that enable autonomous AI agents to operate across applications and environments.

As part of the launch, OpenAI is bringing AGENTS.md, a markdown-based standard that offers project-specific instructions for AI agents. Meanwhile, Anthropic announced that it is donating the Model Context Protocol (MCP) to the AAIF. Block is contributing Goose, its open-source framework for building and running AI agents.

These founding projects offer shared infrastructure for interoperability and predictable agent behaviour.

“We are seeing AI enter a new phase, as conversational systems shift to autonomous agents that can work together,” said Jim Zemlin, executive director of the Linux Foundation. “Bringing these projects together under the AAIF ensures they can grow with the transparency and stability that open governance provides.”

MCP, released by Anthropic in 2024, has become widely adopted as a standard protocol for connecting AI models to tools, data and applications. Anthropic reports more than 10,000 MCP servers across enterprise and developer environments. MCP is currently used by platforms including Claude, Copilot, Gemini, VS Code and ChatGPT.

“MCP started as an internal project to solve a problem our own teams were facing,” said Mike Krieger, chief product officer at Anthropic. “Donating MCP to the Linux Foundation ensures it stays open, neutral, and community-driven as it becomes infrastructure for AI.”

Block’s goose, introduced in 2025, is an open-source, local-first AI agent framework built around MCP for tool and workflow integration. It provides a structured environment for building and running agentic processes.

“We’re at a critical moment for AI,” said Manik Surtani, head of open source at Block. “By establishing the AAIF, Block and this group of industry leaders are taking a stand for openness. Contributing goose ensures that agentic AI remains shaped by the community.”

OpenAI’s AGENTS.md standard, launched in 2025, gives AI coding agents consistent project-level instructions across repositories and toolchains. The markdown-based format is already used by more than 60,000 open-source projects and frameworks such as Cursor, GitHub Copilot, Gemini CLI and VS Code.

“For AI agents to reach their full potential, developers and enterprises need trustworthy infrastructure and accessible tools to build on,” said Nick Cooper, member of the technical staff at OpenAI. “By co-founding the AAIF and donating AGENTS.md, we’re helping establish open, transparent practices that make AI agent development more predictable and interoperable.”

Open Standards for Agentic AI

Developers are building AI agents for coding, workflow automation and customer service, with many now shifting from prototypes to production use. OpenAI said the industry needs shared standards to avoid fragmentation.

“Open standards make agents safer, easier to build, and more portable across tools and platforms,” the company said, adding that without common conventions, development risks diverging into incompatible silos.

Over the past year, OpenAI has released several components meant to support an open agentic ecosystem, including the Agents SDK, Apps SDK, the Agentic Commerce Protocol, gpt-oss models and the Codex CLI.

OpenAI said it has also contributed to the Model Context Protocol (MCP), which is now integrated into ChatGPT connectors and apps. Last week, OpenAI, Anthropic and MCP-UI extended the Apps SDK to all MCP developers through MCP Apps.

Governance and Participation

AAIF will operate as a directed fund within the Linux Foundation. The organisation has invited tool builders, researchers and enterprises to participate in shaping future standards.

The foundation will support open development, long-term sustainability and collaborative governance.

Gold members include Cisco, Datadog, IBM, Oracle, Salesforce, SAP, Shopify, Snowflake and Twilio; Silver members include Hugging Face, Uber, Zapier, SUSE and Mirantis.

The Linux Foundation has previously stewarded projects such as the Linux Kernel, Kubernetes, Node.js and PyTorch.

The post OpenAI, Anthropic and Block Set up Agentic AI Foundation Under Linux Foundation appeared first on Analytics India Magazine.

ElevenLabs, the voice-AI startup, claimed that it has added $14 million in Annual Recurring Revenue (ARR) in a single day.

Mati Staniszewski, the co-founder, announced it in a post on X. “It was our first day crossing $10M, and it’s crazy to see how much has changed since the early days and our very first deal,” he said.

By definition, ARR reflects the revenue a company is contractually guaranteed to receive over the next 12 months. This includes only customers who have committed to annual or longer-term agreements, and the total ARR figure represents the sum of all such active contracts.

Staniszewski stated that in August, the company crossed $200 million in ARR, and by next January, it aims for $300 million in ARR. ElevenLabs’ products were launched publicly only in January 2023, and in October 2024, the company crossed $100 million in ARR.

In September, the company enabled an employee secondary share sale, pricing some shares at $6.6 billion. It has raised a total of $291 million across six funding rounds, according to data from Tracxn. In January this year, the company raised $180M in Series C funding led by a16z and ICONIQ Growth.

ElevenLabs offers text-to-speech, speech-to-speech, voice-cloning, and dubbing tools built on its own foundation audio models, including its core speech synthesis model and its multilingual voice model.

Last month, the company launched Scribe v2 Realtime, its most advanced Speech-to-Text model designed to deliver human-quality live transcription in under 150 milliseconds.

The model supports more than 90 languages, including 11 Indian ones such as Hindi, Tamil, Malayalam, Kannada, Telugu, and Gujarati. The company said the model achieves 93.5% accuracy on the FLEURS benchmark across 30 European and Asian languages, setting a new standard for real-time multilingual communication.

Scribe v2 Realtime is aimed at developers and enterprises building voice assistants, meeting tools, and live captioning applications.

While the company has established itself as one of the leading players in the ecosystem, it continues to face competition from other players, including Deepgram, Smallest.ai, Murf.ai, and others.

The post ElevenLabs Adds $14 Million in ARR in a Single Day appeared first on Analytics India Magazine.

Accenture has expanded its partnership with Anthropic, launching a multi-year initiative to train around 30,000 employees on Claude and embed the model across enterprise environments.

The new unit, branded the Accenture Anthropic Business Group, is positioned as one of the largest concentrations of Claude practitioners globally.

The collaboration is designed to move large organisations out of the AI pilot phase and into broad production deployment. Accenture framed this as a targeted investment in talent, solution development, and go-to-market capacity.

As part of the expansion, Accenture also becomes a premier AI partner for coding with Claude Code, making the tool available to tens of thousands of developers, which marks Anthropic’s largest enterprise deployment to date.

Beyond training, both companies are launching a joint offering aimed at CIOs. The product provides a structured path for scaling AI-powered software development, built around Claude Code and Accenture’s frameworks for quantifying productivity gains, ROI, and workflow redesign.

It is intended to shift engineering organisations to an AI-first operating model, with change-management support and continuous training baked in.

The partnership also includes co-developed solutions for regulated industries, financial services, life sciences, healthcare, and the public sector, where modernisation is constrained by security, compliance, and legacy systems.

Besides, planned use cases include automating document-heavy compliance tasks in banking, assisting R&D teams in life sciences, and enabling AI agents that help citizens navigate government services while preserving data-governance requirements.

To support hands-on experimentation, Accenture will integrate Claude into its global network of Innovation Hubs, allowing clients to prototype and test AI systems in controlled environments before broad rollout.

The companies will additionally create a Claude Center of Excellence inside Accenture to jointly design new AI offerings tailored to enterprise and regulatory contexts.

“Organisations can embed AI everywhere responsibly and at speed,” said Julie Sweet, Accenture’s CEO. “This partnership moves clients from experimentation to reinvention.”

Anthropic CEO Dario Amodei said the partnership represents the company’s largest real-world deployment of Claude Code so far, adding that the new business group will help enterprises “make major productivity gains” using Anthropic’s most capable models.

In a similar move, Accenture also recently entered a collaboration with OpenAI, which will roll out ChatGPT Enterprise to tens of thousands of its employees, which the company says is the largest group to be upskilled through OpenAI Certifications.

Accenture will use the tool across consulting, operations and delivery work as it builds new AI services for clients.

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