The Tech Panda takes a look at recent launches in the superfast field of Artificial Intelligence (AI).
Healthcare: At-Home AI-Powered Online Physiotherapy
PharmEasy, an Indian healthcare platform, launched its online physiotherapy service. Online physiotherapy makes expert-led pain management more convenient and accessible from the comfort of one’s home. It bridges the gap between diagnosis and recovery, enabling users to address physical discomfort without visiting a clinic.
Gaurav Verma, Chief Business Officer, PharmEasy, stated: “Pain doesn’t wait for a convenient time. Neither should care. Expert care shouldn’t be limited by geography or the ability to step out of your home. Our online physiotherapy service meets you where you are. Certified physiotherapists work alongside AI-powered posture and movement analysis to address the root cause of your pain, not just the symptoms.”
FEATURES
- Personalised care for 250+ conditions
- 60+ certified physiotherapists (11+ years experience)
- AI-powered movement tracking
- Recovery plans are updated every 5 sessions
- 24*7 care manager support
- Online consultation at Rs.99 (100% cashback on first consultation)
Industrial Software: A New Lifecycle Digital Twin Architecture for Gigawatt-Scale AI Factories
AVEVA, an industrial software company, announced a new collaboration with NVIDIA, where they’re integrating their engineering and operations software into the NVIDIA Omniverse DSX Blueprint. Together, the two companies are creating physical and digital modules that can be deployed in large-scale data centres, known as AI Factories. The approach replicates the methods used in engineering, procurement and construction projects. The collaboration draws on AVEVA’s comprehensive portfolio, including the CONNECT industrial intelligence platform and industrial digital twin capabilities. It is projected to accelerate time-to-token for AI factories, using domain-specific simulations, digital visualization and collaborative design tools to maximize GPU efficiency and accelerate deployment of AI Factories at speed and scale.
Rob McGreevy, Chief Product Officer, AVEVA said: “AI Factories are fast becoming the industrial-scale engines of the global digital economy. To drive this transformation, AVEVA and NVIDIA are creating a new approach to digital twin deployments, founded on domain-specific expertise, pioneering software and operational excellence. Together, our companies are creating this new digital twin at scale, combining SimReady assets, NVIDIA hardware, and IT and OT data-driven insights to design, build and AI-optimise the intelligent industries of the future.”
FEATURES
- Customers may bring OpenUSD SimReady assets into AVEVA Unified Engineering through a new converter, enabling them to reuse existing assets, design new ones, and leverage high-fidelity SimReady data and environments built on NVIDIA Omniverse libraries.
- With a single source of truth from AVEVA Asset Information Management, customers can manage equipment, systems and make changes seamlessly, ensuring alignment from design throughout operations.
- With AVEVA Process Simulation, customers can model and run simulations of advanced liquid-cooling networks for AI factories to refine designs and maximize cooling efficiency.
- AVEVA’s PI System enables customers to aggregate IT and OT data across NVIDIA Omniverse DSX Exchange. In time this will be extended to include the NVIDIA NV-Tesseract model for anomaly detection and forecasting, enabling customers to interpret telemetry in real time from BMS, EPMS, cooling systems, server racks and workloads, all at giga-scale. This will transform efficiency throughout the lifecycle.
- Customers can use AVEVA Operations Control and Unified Operations Center to manage data centre infrastructure which comprises of electrical (UPS, switchgear, PDU, generator etc.), mechanical (chiller, CDU etc.) and safety systems into one scalable unified platform using a templatized situational awareness approach.
Cybersecurity: AI-Driven Threat Research & Continuous Exposure Validation to Help Security Teams Validate Exposure
Securonix, Inc., a six-time Leader in the Gartner® Magic Quadrant™ for SIEM, today announced the Securonix Threat Research Agent and ThreatWatch for ThreatQ, expanding how security teams research threats, validate exposure, and turn intelligence into documented action. Built on the ThreatQ platform and connected to Securonix security operations workflows, the new capabilities help teams generate role-specific intelligence, validate emerging threats against historical telemetry, and deliver explainable findings for analysts, SOC leaders, and executives.
“Threat intelligence only creates value when it leads to action. What we are doing here is helping teams close the gap between knowing something matters and proving whether it matters in their own environment,” said Simon Hunt, Chief Product Officer of Securonix. “That means faster research, clearer validation, and better decisions when time and confidence both matter.”
FEATURES
- Designed to improve communication across teams, strengthen executive confidence, and reduce manual reporting effort by up to 70 percent.
- Continuously monitors emerging threats curated by Securonix Threat Labs, automatically generates and executes SIEM queries, and runs retroactive sweeps across historical telemetry.
- Human validation is applied before escalation.
- Findings are surfaced through ThreatQ with direct pivots into the SIEM, giving teams documented, audit-ready answers when leaders need to know whether exposure was real.
- Lets analysts extract, validate, enrich, and curate intelligence directly from what they are reading, including blogs, reports, GitHub pages, and PDFs, then sync that work into ThreatQ investigations and workflows while surfacing relevant Securonix evidence and historical sightings.
Voice AI: Report for AI Voice Benchmarking Across Indian & Global South Languages
Humyn Labs, a physical and voice AI data infrastructure company, published BRIDGE (Benchmark of Regional & International Data for Global Evaluation), the largest independent benchmark to evaluate commercial AI speech-recognition tools on real Indian language data. Covering 15+ Indic languages, 22 Indian states, and 15 global models, including tools from ElevenLabs Scribe v2, Deepgram Nova-3, Gemini 2.5 Flash, OpenAI GPT-4o, and Indian providers Sarvam saaras v3 and Gnani vachana v3, it is the most comprehensive evaluation of its kind ever conducted for languages spoken by over 5.5 billion people across the Global South.
“The models are grading their own work. ASR providers published their own accuracy scores using benchmarks built on English-first, internet-trained datasets, with little independent validation. Meanwhile, enterprises are making million-dollar deployment decisions on numbers that rarely reflect how their users in Global South actually speak. Before BRIDGE, there was no independent benchmark for real-world conversational audio across non-English markets,” said Manish Agarwal, Co-founder, Humyn Labs.
FEATURES
- BRIDGE applies a seven-metric stack: WER, CER, Semantic Similarity, Code-Switch F1, Loan Word WER, Phoneme-Informed Error Rate, and Word Information Lost. Each captures a different dimension of failure.
- Semantic Similarity measures whether the meaning of what was said is preserved, even when exact words differ.
- Loan Word WER tracks accuracy specifically on English words embedded in Indian language speech. Phoneme-Informed Error Rate accounts for how Indic phonology is transcribed.
- Word Information Lost penalises both under- and over-transcription. Together they expose failure modes that a word count alone will never surface.
Non-profit: Initiative to Build AI Capacity in India’s Nonprofit Sector
ImpactAI Foundry, a new Bangalore-based initiative, has launched a hands-on programme to help India’s nonprofits integrate artificial intelligence into their operations. With applications now open for its June 2026 pilot cohort, the programme offers participating organisations two months of structured workshops, dedicated tech mentorship, and practical support to build AI tools tailored to their specific challenges.
“We grew up in Bangalore and have seen firsthand how much the social sector here does with very little. AI shouldn’t be something that only well-resourced organisations can access. We’re here to make sure that the nonprofits doing the most important work are not the ones left behind,” said Arjun Balaji and Jyothika Raju Co-Founders, ImpactAI Foundry.
FEATURES
- The programme is intentionally platform-agnostic, focusing on use-case-driven adoption rather than any specific software.
- Each participating organisation is paired with a volunteer tech mentor from Bangalore’s technology community, who guides their team through the process of identifying where AI can add value and building a tool that fits their existing workflows.
- The commitment for mentors is light, making it accessible to professionals from across Bangalore’s tech sector who want to contribute meaningfully to the city’s social ecosystem.
- Open to nonprofits across all sectors education, healthcare, livelihoods, women’s empowerment, and more where AI has the potential to meaningfully increase efficiency and impact.
- The pilot cohort will work with six to eight Bangalore-based organisations, with plans to scale the model to other Indian cities following pilot validation.
