Press, partnerships, and product updates from Responsible AI Labs.
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The RAIL Score MCP server is now live at mcp.responsibleailabs.ai, bringing responsible AI evaluation, compliance, agent safety, and DPDP tools directly into any MCP-compatible client. The Python (2.6.1) and JavaScript/TypeScript (2.6.0) SDKs add the DPDP namespace, Indian PII detection, and runtime configuration introspection. We have also published the RAIL Guard Benchmark on Hugging Face.
Responsible AI Labs has joined three more programs across the Indian and global AI ecosystem: the Startup Showcase at Nasscom GCC Summit 2026, Google for Startups Immersion 2026 powered by Antler, and the Razorpay Rize founder community.
NVIDIA has accepted Responsible AI Labs into NVIDIA Inception, the program that supports startups building with AI through hardware and cloud credits, Deep Learning Institute training, and direct technical engagement with NVIDIA's engineering and go-to-market network.
On 17 April 2026, Nasscom announced the fourth cohort of its GenAI Foundry programme, inducting 33 high-potential generative AI startups from across India. Responsible AI Labs is proud to be one of them. Covered by The Hindu.
Responsible AI Labs has been accepted into four partner programs that underpin the infrastructure, data, and collaboration stack behind the RAIL Score platform: Google for Startups Cloud, AWS for Startups (with a feature on the AWS Startup Showcase), MongoDB for Startups, and Atlassian for Startups.
Two public datasets are now available on HuggingFace for responsible AI research: RAIL-HH-10K (a multi-dimensional safety dataset, 789 total downloads) and the Indian Responsible AI Benchmark (158 total downloads).
Major updates to the RAIL Score API and official SDKs. New compliance testing and safe regeneration endpoints, expanded Python and JavaScript/TypeScript SDK support in v2.1.1, and plan-based rate limiting.
The first stable release of the RAIL Score API, live at api.responsibleailabs.ai. Initial endpoints: unified /eval, /safe-regenerate, and public /health.
Three official client libraries for the RAIL Score API are now public and MIT-licensed: the Python SDK on PyPI, the JavaScript/TypeScript SDK on npm, and the Drupal module on drupal.org.
Our methodology paper is now on arXiv: 'RAIL in the Wild: Operationalizing Responsible AI Evaluation Using Anthropic's Value Dataset.' Applies the eight-dimension RAIL framework to Anthropic's Values in the Wild dataset (308K+ anonymized Claude conversations and 3K+ annotated value expressions) and shows what falls out.
