Category Archives: Technology

GIA 2.0 Soon to Expand Karnataka’s Tech Partnerships

Apr 15 (BNP): Karnataka’s Global Innovation Alliance (GIA) has emerged as a strong platform for international technology collaboration, helping connect startups, innovators, and institutions across global markets.

The initiative has facilitated partnerships between Karnataka-based startups and global innovation ecosystems, strengthening knowledge exchange and access to international opportunities.

Officials said the programme has helped position Karnataka as a leading hub for innovation-driven growth and global tech engagement.

The state is now preparing to launch GIA 2.0, which is expected to further expand global partnerships and enhance support for emerging technologies and startups.

Helical raises $10M for virtual AI lab that operates at pharma scale to make in-silico discovery reproducible 

The Helical virtual AI lab for pharma, an application layer that turns biological foundation models into decision-ready, reproducible in-silico discovery workflows. The $10 million funding will support expansion across more top-20 pharma programs and growth of its deployed science engineering team.

London, UK – Apr 15; Pharma has no shortage of ideas. It has a shortage of throughput. Roughly 50 new drugs are approved each year despite more than 10,000 known diseases, and every promising hypothesis still collides with the same constraint: slow, expensive physical experimentation. Biological foundation models have opened the door to a new mode of discovery, where scientists can test hypotheses computationally before committing to the wet lab. Helical was built to make that shift real inside modern pharma R&D.

Today, the company announced a $10 million seed round led by redalpine with participation from Gradient, BoxGroup, Frst and notable angels including Aidan Gomez (CEO Cohere), Clement Delangue (CEO HuggingFace) and Mario Goetze (pro soccer player).

The timing reflects a gap that has emerged as bio foundation models have taken off. Pharma teams are excited about the model layer, but many efforts stall because the work between a model output and a scientific decision is still fragmented. New architectures are emerging constantly, while bench scientists and ML engineers operate in silos. As a result, teams often recreate one-off notebooks and analyses that are difficult to reproduce or transfer across programs. What pharma has needed is an application layer that turns powerful models into systems scientists can run, trust, and defend.

Helical is the virtual AI lab for pharma, designed to turn bio foundation models into reproducible discovery systems so every scientist can test hypotheses in-silico at the speed of inference. The platform has two product surfaces — the Virtual Lab for biologists and translational scientists, and the Model Factory for ML engineers and data scientists — built on the same data, the same models, and the same results. By putting both sides in the same system, Helical closes the gap between computational predictions and biological decision-making, so teams that traditionally worked in silos can collaborate on the same evidence.

“The models alone don’t discover drugs. The system does” said Rick Schneider, co-founder of Helical. “Pharma teams need a system that turns foundation models into workflows scientists can run, validate, and defend. We built Helical to make in-silico science reproducible at pharma scale, so teams can go from hypothesis to decision in days instead of months.”

Helical was founded in early 2024. The company was created by three school friends who took different paths into the same problem. Rick Schneider built tech at Amazon and later helped the German enterprise Celonis scale in France and Japan. Maxime Allard led data science teams at IBM before pursuing a PhD focused on reinforcement learning and robotics. Mathieu Klop became a cardiologist and genomics researcher. When bio foundation models emerged, the trio saw the chance to build the missing application layer that would let pharma teams move from model experimentation to reproducible, production discovery.

Helical is already in production with multiple top-20 global pharma companies, including a public collaboration with Pfizer on predictive blood-based safety biomarkers. Across deployments in target identification, biomarker discovery, and therapeutic design, teams have compressed discovery timelines from years to weeks and expanded organically from single indications into adjacent therapeutic areas.

The broader industry context is increasingly unforgiving. R&D spending exceeds $300 billion annually, timelines stretch beyond a decade, costs to bring a drug to market now exceed $2 billion on average, and more than 90 percent of candidates entering clinical trials fail. AI has been positioned as the answer, but many efforts stall in pilot because predictions alone are not enough. Discovery teams need outputs grounded in biological evidence, delivered through a system that makes decisions reproducible and explainable, not another black-box ranking. 

“We are at a unique point in time where biological foundation models and general language reasoning models are converging.” Said Daniel Graf, General Partner at redalpine. “We backed Helical because we strongly believe they have what it takes to build the pharma AI orchestration platform that will drive this transition from siloed AI models to integrated virtual AI labs.”

Looking ahead, Helical plans to deepen deployments across more therapeutic areas and programs with existing clients, expand to additional top-20 pharma organizations, and continue building the compounding evidence layer that improves performance across diseases. The company’s mission is to make every scientist able to test hypotheses at the speed of inference and to turn in-silico discovery into a reliable engine for R&D throughput.

PayU Rolls Out AI Voice Tool to Streamline Onboarding

GoCredit Rolls Out AI-Powered Loan Assistant to Simplify Borrowing

Bangalore, Apr 15 (BNP): Financial intelligence platform GoCredit has launched what it claims to be India’s first AI-powered Loan Agent in Bengaluru, introducing a chat-based system that helps users find and apply for personal loans through a single conversational interface.

The AI tool allows borrowers to compare loan options, check eligibility, and complete applications within one interaction, simplifying the lending process.

According to the company, the system has been in active use since March 2026 and is already processing real loan applications.

GoCredit also reported that it has facilitated over ₹100 crore in loan disbursals, generated more than 15 million loan offers, and served over 2 million borrowers so far.

The platform aims to make credit access faster, more transparent, and easier for users through artificial intelligence-driven solutions.

Kärcher India Champions ‘Mechanised cleaning’ with Manual vs Mechanised’ Campaign

New Delhi, Apr 15: The recent campaign launched by Kärcher India is known as “True Clean” and encouraging consumers to move beyond traditional cleaning methods and adopt smarter, more efficient mechanised solutions

This marketing campaign is founded on the principle that there is a distinction between surfaces that seem clean and are truly clean. Regular practices like sweeping and scrubbing tend to disperse dust and leave behind stubborn grime along with requiring physical exertion continuously. In this way, Kärcher emphasizes “invisible inefficiencies” that are associated with traditional cleaning processes and do not lead to true hygiene.

“Clean = Kärcher” is one of the company’s key slogans. This slogan reflects the efficacy of the technology-driven products provided by the organization from vacuum cleaners that capture and hold in dust instead of dispersing it, to steam cleaners that promise 100% chemical free cleaning process as well as killing off 99.999% of viruses and 99.99% of bacteria, along with high-pressure washers that deliver powerful cleaning far beyond conventional methods.

Ayesha Prasad Narain, AGM Marketing at Kärcher India said, “The cleaning process cannot be limited only to the surface level; we must go beyond visible cleaning results. This is the message of our “Manual vs Mechanised‘ campaign, which is designed to help consumers see the difference between perception and reality and motivate them to choose technology-based smart solutions that offer deep cleaning without putting any additional effort.” 

The campaign is also an indication of changing consumer behavior and lifestyle. By introducing innovations like robotic vacuum cleaners and easy-to-carry cleaning products, Kärcher makes it possible for consumers to opt for cleaner yet efficient ways of cleaning.

Through this campaign, Kärcher India aims to drive a clear shift in consumer mindset—from viewing cleaning as a manual chore to experiencing it as a smart, effortless, and efficient process.

Orbital sets date for first test mission to put AI data centers in low Earth orbit

Orbital is building and operating AI data centers in space, using solar power and radiative cooling to remove the energy and cooling constraints that limit terrestrial AI infrastructure. Backed by funding from a16z Speedrun, the company plans to launch its first test mission in 2027 and is opening Factory-1, its R&D facility in Los Angeles.

Los Angeles, California – Apr 15; The demand for AI compute is surging, but the bottleneck is no longer chips, it’s the power required to run them. Orbital was founded on the belief that the only way to scale compute and unlock future progress on artificial intelligence is to stop competing for power on Earth and generate it in orbit.

Today, the company announced funding from a16z Speedrun to support Orbital-1, the company’s first test mission on its aim of deploying data centers in space. “Speedrun backs founders to explore ambitious ideas — the harder the problem, the better,” said Andrew Chen, General Partner, a16z speedrun. “Orbital is taking on AI‘s biggest constraint with a bold and radical idea.”

Orbital is designing and manufacturing a constellation of satellites to operate in low Earth orbit, each housing a cluster of NVIDIA-powered servers. Each satellite is powered by solar arrays and cooled by radiating heat directly into space. In orbit, solar power is available 24/7 in sun-synchronous orbit and stronger, with no weather, no night, and no dependence on the power grid. 

“AI progress is being constrained by the grid,” said Euwyn Poon, CEO and founder of Orbital. “Data center economics are dominated by electricity and cooling, and both are getting harder. In orbit, solar power is continuous and cooling is fundamentally different. Orbital is building compute infrastructure that removes the energy ceiling and scales with AI‘s potential.”

Orbital‘s compute infrastructure is designed around a specific technical insight. Training large AI models requires thousands of GPUs tightly coupled, communicating at near-zero latency. That architecture does not translate to satellites. Inference is different. Each request is handled independently, and capacity can be distributed across many nodes. Orbital is focused on inference, where orbital compute can scale as a constellation and serve workloads in parallel.

Orbital‘s first satellite, Orbital-1, is scheduled to launch on a SpaceX Falcon 9 in April 2027. Its primary goal is to validate sustained GPU operation in orbit, test radiation hardening, and run AI inference workloads commercially in space post-validation. The company is also in the process of filing with the FCC to deploy a constellation of satellites for orbital AI compute infrastructure.

Orbital was founded by Euwyn Poon, a Cornell-educated engineer and lawyer who previously founded Spin, the micromobility company acquired by Ford. At Spin, Poon built and deployed hundreds of thousands of small electric vehicles across 100 cities and scaled the business to over $100 million in revenue. After exiting Spin, he began investing in AI infrastructure and saw the impending constraint clearly. “The energy ceiling on AI isn’t theoretical, it’s a real constraint that will impede the advancement of intelligence,” said Poon. “This is the solution.”

ITS America Conference & Expo 2026 Launches Cybersecurity & Data Zone in Detroit

DETROIT, Mich. (April 15, 2026) – ITS America Conference & Expo, organized in partnership by RX Global and ITS America, announces the launch of the Cybersecurity & Data Zone at the June 9-12, 2026 event to address the evolving connected industry and the management of data and cybersecurity. The dedicated space within the Huntington Place Exhibit Hall in Detroit will showcase cutting-edge technologies designed to protect connected vehicles, secure smart infrastructure, and strengthen transportation system resilience. The zone brings together cybersecurity tools, data management solutions, and industry experts, offering attendees direct access to technologies shaping secure and reliable intelligent transportation systems.

More than 30 exhibitors focused on Cyber and Digital Security and Data Management and Data Analytics will be part of the event, giving attendees direct access to some of the most recognized names in the field. Among them, Palo Alto Networks brings its AI-driven cybersecurity platforms trusted by more than 70,000 customers worldwide, Flock Safety offers its automated license plate recognition, video surveillance, and other detection systems, and Cisco Systems contributes its globally recognized networking and cybersecurity solutions.

“Cybersecurity is a fundamental requirement for the safe deployment of intelligent transportation technologies that connect our vehicles, infrastructure, and data systems,” said Laura Chace, President and CEO, ITS America. “The Cybersecurity & Data Zone represents our industry’s commitment to safe innovation and demonstrates how we can advance transportation technology while maintaining the highest security standards that protect people and the critical infrastructure they use.”

As transportation systems become more connected, the need to protect them grows just as fast. Cybersecurity threats targeting vehicles, infrastructure, and data networks pose real risks to public safety and system reliability. The Cybersecurity & Data Zone gives transportation professionals a dedicated space to find the tools and expertise needed to stay ahead of those risks.

“Transportation leaders need practical tools and strategies to address cybersecurity challenges while continuing to advance innovation,” said Jaime McAuley, Event Vice President, RX Global. “This zone creates a focused environment where professionals can explore solutions, connect with experts, and develop the knowledge needed to deploy secure transportation technologies that benefit communities nationwide.”

The ITS America Conference & Expo 2026 emphasizes cybersecurity as a core requirement for safety, reliability, and public trust as transportation systems become more digital, connected, and automated. Industry leaders will spotlight these topics to help attendees stay ahead of emerging challenges through cutting-edge solutions, hands-on workshops, and insights. The event provides transportation professionals with comprehensive resources to navigate the complex security landscape facing modern mobility systems.

Cybersecurity & Data Sessions & Events

• Data Exchange and Its Role in the Larger Digital Infrastructure System

• From Data to Decisions: AI-Driven Solutions for Modern Transportation

• Breaking Down Data Silos to Unlock Scalable ITS Solutions

• Smart Transportation: Digital Infrastructure and Data Integration

• Workshop: Building Cyber Resilient Transportation Systems

Running June 9-12, 2026, at Huntington Place in Detroit, Michigan, ITS America Conference & Expo connects public and private sector transportation professionals through hands-on demonstrations of technologies, including automated traffic signal performance measures, emergency vehicle preemption systems, connected vehicle integration capabilities, and autonomous mobility solutions. This year’s event operates under the theme “Empowering Innovation” and focuses on how leaders implement and deploy new technology to create safer, smarter, and more connected transportation systems.

See below to explore these innovations and more: https://www.itsamericaevents.com/expo/en-us/discover/cybersecurity-and-data.html

Lightrun’s 2026 State of AI-Powered Engineering Report: Almost Half of AI-Generated Code Fails in Production

Software Failures and Lack of Runtime Visibility Prevent Engineering Teams from Trusting Coding Assistants and AI SREs 

NEW YORK, April 14, 2026 — Lightrun, the leader in software reliability, today released its State of AI-Powered Engineering Report 2026, based on an independent poll of 200 SREs and DevOps leaders (Directors, VPs, and C-levels at Enterprises in the US, UK, and EU). The report reveals that, until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems. 

Lightrun’s report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production.

As the volume of AI-generated code is rapidly increasing, it is essential to close this verification loop. As a result, engineering teams are turning to AI SRE (site reliability engineering) tools. These agents reason over existing observability, codebase changes, and infrastructure signals to propose incident causes and recommend fixes. However, the report found that 77% of engineering leaders lack confidence in current observability stacks to support automated root cause analyses and remediations. 

Lightrun’s report, conducted with independent research firm Global Surveyz, captures the perspectives of senior engineering leaders on the AI-powered SDLC. It explores several timely issues, including: 

● AI-Generated Code Reliability Concerns: 88% of companies require 2-3 manual redeploy cycles just to confirm an AI-generated fix actually works in production.

● Wasted Developer Time: Developers spend an average of 38% of their week (two days) on debugging, verification, and troubleshooting.

● The Runtime Visibility Gap: 60% of SRE and DevOps leaders identify a lack of runtime visibility as the primary bottleneck in resolving incidents. This is underscored by the fact that, in 44% of cases where AI SREs or APM tools investigations failed, it was due to the necessary execution-level data not being captured.

● AI SREs: The Trust Wall: 97% of engineering leaders say AI SREs operate without significant visibility into what’s actually happening in production. And, 54% of resolutions to high-severity incidents still use tribal knowledge rather than diagnostic evidence from AI SREs or APMs. 

This represents the core challenge of AI-accelerated engineering. Today’s AI agents operate using probability, reasoning their way toward conclusions. To ground that reasoning in reality, the report makes clear they need real-time visibility into what’s happening, including variable states, memory usage, and how requests move through a system. 

“Engineering organizations need runtime visibility to embrace the possibilities offered by AI-accelerated engineering. Without this grounding, we aren’t slowed by writing code anymore, but by our inability to trust it,” said Ilan Peleg, CEO of Lightrun. “When almost half of AI-generated changes still need debugging in production, we need to fundamentally rethink how we expect our AI agents to solve complex challenges.” 

The report is available online at http://lightrun.com/ebooks/state-of-ai-powered-engineering-2026.

BIScience Launches the First AI Suite for Effortless Cross-Media Ad Intelligence

The AdClarity AI Suite combines an AI-powered chatbot that acts as a personal data science expert with proactive AI Insights, covering up to 85% of analyst work in seconds across digital, CTV, and linear TV channels. 

New York, NY, April 14, 2026 – BIScience, the company behind AdClarity, the cross-media ad intelligence platform serving more than 2,000 brands including Adidas, Amazon, Booking.com, Disney, Shell, Sony, and Wix, today launches the AdClarity AI Suite. BIScience is the first ad intelligence provider to introduce these capabilities, making competitive insights effortless and accessible to every team member.

The launch represents a fundamental change in methodology, not just a new feature. Until now, ad intelligence platforms have operated as static data repositories, requiring companies to spend significant time, money, and manual effort building reports. BIScience has redesigned this workflow entirely: instead of requiring users to find answers in data, the AI Suite delivers answers and intelligence directly to them across digital display, social, online video, CTV, and linear TV channels.

The suite offers two complementary sides of a single solution. One side helps users clearly define what they need and get precise answers on demand. The other guides them forward, proactively uncovering what matters even when they are not sure where to start, since many teams do not even know which questions they should be asking.

AdClarity AI Chatbot functions as a personal data science expert. Users type questions in natural language and receive structured answers in seconds, drawn exclusively from AdClarity’s own cross-media data. A user can ask “Who’s winning in CTV in 2026 in the US?” or “How did my competitor’s channel mix shift last quarter?” and receive a clear response with key findings, detailed analysis, and supporting tables and charts. Users can drill deeper with follow-up questions and export executive-ready summaries directly from the interface.

AI Insights takes a complementary approach, proactively surfacing important findings inside Brand Reports and key widgets. Rather than waiting for a user to ask the right question, AI Insights automatically generates clear narratives explaining what changed in the competitive landscape and why, updating as users change filters and selections. 

“The AdClarity AI Suite represents a fundamental shift in how teams interact with market intelligence,” said Dorit Kaplan, VP of Product and Strategy at BIScience. “By embedding an AI data science layer directly into the platform, we’ve automated the heavy lifting of complex analysis. What used to require hours of manual work is now delivered in seconds, effectively handling 85% of the analytical pipeline instantly. With AI Insights, we’re moving beyond reactive searching to a proactive model that surfaces critical trends before they even appear on a team’s radar.” 

Both capabilities operate entirely within the AdClarity platform and draw on BIScience’s full ad intelligence dataset, covering $393 billion in annual ad spend across 52 markets. To learn more or request a demo, visit: https://adclarity.com

Ransomware Attacks Surge in India; Manufacturing Firms Among Most Affected: Report

Apr 14 (BNP): India has emerged as a major target for cybercriminals, becoming the Asia-Pacific hotspot for ransomware attacks, with the manufacturing sector among the worst affected, according to a recent industry report.

The study highlights that a significant share of impacted organisations in India’s manufacturing sector were forced to pay ransom demands in 2025, underscoring the growing financial and operational risks posed by cyberattacks.

Experts note that ransomware groups are increasingly targeting industrial operations, where disruptions can halt production, impact supply chains, and cause large-scale financial losses.

The report also points to a rising trend of extortion-based attacks, where data is stolen and companies are pressured into paying to prevent its release or to restore access.

India’s rapid digitalisation and expanding industrial base have made it an attractive target for global cybercriminal networks, particularly those focusing on high-value sectors like manufacturing.

Security experts warn that unless organisations strengthen cyber defences and invest in advanced threat detection systems, such attacks are likely to continue rising in frequency and severity.