NxtGen Cloud Technologies recently announced the general availability of M for Coding, India’s first sovereign AI coding autopilot.
Built entirely with Indian talent, open-source innovation and powered by NxtGen’s high-performance GPU cloud infrastructure, M for Coding ensures that code written stays secure, compliant and within India’s jurisdiction, protecting enterprise intellectual property while delivering world-class AI performance.
India’s technology ecosystem is experiencing phenomenal growth with annual revenues projected to surpass $280 billion this year and over six million people employed across the tech and AI sectors, as per PIB.
The country is home to more than 1,800 global capability centres (GCCs), including over 500 focused on AI and around 1.8 lakh startups, of which nearly 89% of new ventures launched last year incorporated AI into their products or services.
On the NASSCOM AI Adoption Index, India scores 2.45 out of four, reflecting that 87% of enterprises are actively leveraging AI solutions. Key sectors driving AI adoption include industrial and automotive, consumer goods and retail, banking, financial services and insurance and healthcare, together contributing roughly 60% of AI’s total value.
According to a recent BCG survey, about 26% of Indian companies have achieved AI maturity at scale.
Fuelling these developments, the IndiaAI Mission’s ₹10,300-crore outlay for domestic compute, datasets and skilling ensures that foundational AI infrastructure and training remain within national jurisdiction.
During an interaction with AIM, AS Rajgopal, MD and CEO of NxtGen Cloud Technologies, said, “Sovereign AI sits at the intersection of India’s three defining policy pillars: the IndiaAI Mission, the Digital India Act (DIA) and the Digital Personal Data Protection Act (DPDPA). Together, they mark India’s shift from digital adoption to digital autonomy.”
The DPDPA provides the lawful framework for processing data used in AI pipelines, while the forthcoming DIA strengthens accountability for platforms and AI systems. In essence, Sovereign AI represents the practical layer of India’s evolving digital sovereignty stack.
Furthermore, Rajgopal said, “The US CLOUD Act empowers American authorities to compel US service providers to disclose data they control, regardless of where that data physically resides.”
Similarly, FISA Section 702, reauthorised in 2024, permits surveillance on non-US persons through electronic service providers. For Indian enterprises relying on US hyperscalers, this introduces ongoing compliance risks, as data stored in India can still fall under foreign jurisdiction.
The only effective mitigation is structural, which includes collaboration with India-incorporated providers, maintaining India-resident compute and adopting customer-controlled encryption keys. Combined with DPDPA-aligned data policies, these measures form the foundation of genuine digital sovereignty.
How M for Coding Differs from GPT-4 or Claude
“M for Coding is engineered as an agentic, enterprise-grade system, not merely a conversational model,” Rajgopal explained.
Operating entirely on India-based GPU infrastructure, it guarantees that no data or inference path leaves national boundaries. Its design integrates tool-calling middleware with guarded code generation, enabling the system to plan, execute and verify changes across enterprise repositories and CI/CD pipelines.
Unlike traditional models reliant on generic reinforcement learning, M for Coding focuses on code quality outcomes, compilation success, test coverage and security linting, while supporting deterministic inference modes for reproducible builds. In short, it functions as a coding co-pilot built for sovereignty, auditability and enterprise control.
In fact, independent benchmarks demonstrate that M for Coding outperforms global competitors across key coding and agentic tasks.
On the SWE-bench Verified (500 turns), it scored 73.8, surpassing Claude Sonnet 4 (70.4) and closely matching Claude Opus 4.1 (74.5).
In Aider’s polyglot, it achieved 67.0, well ahead of GPT-4.1 (52.4) and Claude Sonnet 4 (56.4). Its tool use performance on BFCL V3 reached 71.5, compared with GPT-4.1 at 62.9 and Claude Sonnet 4 at 73.3. Meanwhile, on retail task automation (TAU-bench), it scored 81.9, outperforming both Claude Sonnet 4 (80.5) and GPT-4.1.
These results position M for Coding as a sovereign AI alternative and a world-class coding autopilot, excelling in multi-turn reasoning, multilingual coding and real-world task automation.
Balancing Open-Source Innovation and Sovereignty
“Open-source software remains indispensable. However, sovereignty demands verifiable control,” Rajgopal added.
This entails hosting in-country mirrors of critical repositories, enforcing reproducible builds and signed artefacts and tracking dependencies via software bills of materials. Essential packages are vendored or forked into long-term support branches, and all builds occur in hermetic, air-gapped environments within India. Rajgopal said that the guiding mantra remains clear: “open by source, sovereign by control.”
Across the BFSI, government and manufacturing sectors, three key waves of agentic AI adoption are gaining momentum.
The first, Agentic Workflows, enables AI not only to draft code but also to execute actions such as IT incident triage, security orchestration and compliance automation.
The second wave, Internal Code Generation and Refactoring, accelerates modernisation of legacy codebases by generating tests and managing infrastructure-as-code.
The third, Automation Co-pilots, integrates spreadsheets, APIs and business systems into event-driven automations, driving efficiency and intelligent process automation across enterprises.
Rajgopal added that “Agentic AI, AI that can act like ‘M’ by NxtGen, is emerging as the real differentiator, signalling the next stage of enterprise automation.”
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