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Yuki Emerges from Stealth with $6M to Tackle Spiraling AI Data Costs

Posted on by Yashika Aneja

NEW YORK: Data cost optimization startup Yuki emerged from stealth today with $6 million in seed funding to address what enterprises describe as unmanageable AI and data infrastructure expenses driven by rigid, one-size-fits-all compute models.

The round was led by Hyperwise Ventures, with participation from VelocitX, Tal Ventures, Fresh.fund, and Yakir Daniel, founder of Spot.io (now part of Flexera). Daniel stated, “They’re building the control layer for data cost optimization just as AI is turning data spend into a board-level issue.”

Ido Arieli Noga, Yuki’s CEO, emphasized, “Data is the only resource in an organization that no one truly manages. We know how to store it, but not how to govern it.” He also highlighted that traditional infrastructure lacks control systems for data workloads themselves. Noga added, “For years, the default response to growth was to burn more money on the same one-size-fits-all infrastructure. That model is fundamentally broken, and it doesn’t scale in an AI-driven world.”

Yuki’s AI-powered control plane continuously learns workload behavior, service-level agreements, and cost-performance tradeoffs, routing queries to optimal compute resources in real time. The platform distinguishes between business-critical tasks and lower-priority internal processes, enabling dynamic resource allocation without code changes.

Early customers using Yuki’s platform in 2025 achieved average cost reductions of 42.6 percent, representing millions in savings for large enterprises. Customers include cybersecurity firm Tenable and media company Angel Studios.

The platform addresses inefficiencies where teams with different SLAs, budgets, and performance needs share identical compute resources. As enterprises adopt Apache Iceberg to decouple storage and compute, Yuki provides “the missing intelligence layer that governs how workloads consume those resources,” according to the company.

Founded in 2025 by childhood friends Noga and CTO Amir Peres, Yuki employs 15 people across Israel, the United States, and United Kingdom. The funding will expand Israeli R&D operations, deepen product capabilities, add support for additional data platforms, and scale U.S. sales efforts.

AI Could Transform Jobs, Overall Economic Growth by 2030: World Economic Forum

Posted on by Shobhit Kalra

New Delhi: Artificial Intelligence (AI) is expected to bring major changes to jobs across the world by 2030, according to a new World Economic Forum (WEF) white paper released this month. The report says the impact could vary widely, from a major rise in productivity to large-scale job losses, depending on how fast AI improves and how prepared workers and businesses are.

The paper, titled ‘Four Futures for Jobs in the New Economy: AI and Talent in 2030’ said, “It presents four possible scenarios that explain how AI could transform jobs, business value chains, and overall economic growth. The report is based on insights from the Forum’s Chief Strategy Officers Community and global experts who study long-term trends.”

Survey data mentioned in the report shows that business leaders are unsure about what the future will look like. Around 54% of executives globally believe AI will replace existing jobs, while only 24% think it will create new ones. The report also points out a possible gap between profits and worker benefits. While nearly 45% expect AI to improve profit margins, only 12% believe it will lead to higher wages, meaning the benefits of productivity may not be shared equally.

The WEF highlights that technology alone will not decide what happens next. It stresses that actions taken today, such as investing in people and skills, will shape the outcomes.

The report said, “The future of workplaces and value chains will not be defined by technologies alone. Human capital strategies and investments prioritised today will determine how well societies and individual businesses can adapt to, and lead in, the new economy.”

The four scenarios range from ‘Supercharged Progress’, where new occupations grow rapidly, to ‘The Age of Displacement’, where automation grows faster than reskilling, causing unemployment and instability. Two other outcomes include the ‘Co-Pilot Economy’ and ‘Stalled Progress’.

Cosmoserve Eyes on the Sky: Wins INR 5.5cr Funding on Bharat Ke Super Founders

Posted on by Shobhit Kalra

Bengaluru: Spacetech startup Cosmoserve Space has raised INR5.5 crore in funding through Bharat Ke Super Founders, a founder-first entrepreneurial television series streaming on Amazon MX Player. The deal values the company at INR 225 crore.

Founded by former Indian Space Research Organisation (ISRO) scientist Chiranjeevi Phanindra, Cosmoserve Space is building autonomous spacecraft systems aimed at solving the growing challenge of space debris. The company is developing its proprietary platforms, Reviver and Mothercraft, which are designed to detect, capture, and safely de-orbit defunct satellites and other high-risk orbital debris.

Apart from debris removal, the startup is also working on technologies that support in-orbit servicing, including robotic arms, optical navigation systems, and refuelling support devices to improve satellite life-cycle management.

The investment round was led by Dr A. Velumani, who committed INR 5 crore for a 2.22% stake, subject to a proposed follow-on raise of INR 45 crore. Two other investors, Shivam M and Srini S, also participated, investing INR 25 lakh each for 0.11% equity each.

Cosmoserve currently has a 15-member team and is still in the product development stage, with commercial deployment planned for 2028.

HCLTech Acquires Singapore-Based Finergic Solutions for $14.8M to Strengthen Wealth Management Capabilities

Posted on by Anurag Shukla

SINGAPORE & NOIDA, India – HCLTech signed a definitive agreement to acquire Finergic Solutions for 19 million Singapore dollars in an all-cash transaction, bolstering the IT services company’s financial services expertise as wealth management institutions accelerate digital transformation initiatives.

The deal, valued at approximately $14.8 million USD, targets Finergic’s specialized capabilities in core banking and wealth management transformation. The transaction is expected to close by April 30, 2026, subject to customary conditions. HCLTech, India’s third-largest IT services firm, will integrate Finergic’s boutique consulting practice into its financial services division.

Founded in 2019 and headquartered in Singapore, Finergic focuses exclusively on wealth management transformation programs with established global presence. The company reported revenue of 12.6 million Singapore dollars for fiscal year 2024, with 5.1 million derived from HCLTech as an existing client relationship, demonstrating operational integration prior to the acquisition announcement.

Finergic demonstrated consistent growth trajectory, increasing revenues from 5.8 million Singapore dollars in 2022 to 6.2 million in 2023 before more than doubling to 12.6 million in 2024. The acquisition provides HCLTech with specialized transformation strategy, consulting, and wealth architecture capabilities that complement the acquirer’s scale and financial services industry experience.

Srinivasan Seshadri, Chief Growth Officer and Global Head of Financial Services at HCLTech, emphasized strategic positioning to strengthen digital services capabilities in wealth management. The transaction enables delivery of advanced capabilities, innovation acceleration, and substantial synergies empowering clients to realize greater business outcomes across the financial services landscape.

HCLTech brings over 25 years of global experience serving leading financial institutions, supporting more than 40 global banks with Temenos platform implementations. The addition of Finergic’s niche expertise aims to accelerate delivery of next-generation platform-enabled wealth management solutions anchored by advanced AI-native workflows.

Finergic co-founders Ganesh Swaminathan, Saravanan Kandaswamy, and Senthil Kumar Sekar expressed enthusiasm about joining HCLTech’s growth trajectory. The founders highlighted shared vision for financial services industry transformation and complementary strengths positioning the combined organization to deliver greater value to enterprise clients.

The acquisition does not constitute a related party transaction, with no promoter, promoter group, or group companies holding interest in the entity being acquired. The deal requires no governmental or regulatory approvals, facilitating streamlined completion within the projected timeline.

For HCLTech, the transaction represents continued strategic focus on financial services sector consolidation, particularly around specialized consulting capabilities that enhance the company’s ability to compete for complex digital transformation projects at wealth management institutions modernizing technology platforms and operational processes.

Chata Technologies Closes $10M Series A for AI in Financial Services

Posted on by Shobhit Kalra

TORONTO – Financial technology startup Chata Technologies secured $10 million USD in Series A funding to scale what the company describes as deterministic AI designed specifically for regulated financial sector workflows requiring predictable, auditable outcomes.

The Toronto-based company targets a core enterprise challenge facing financial institutions: organizations want automation benefits but require predictable behavior, complete auditability, and compliance-friendly outputs. In regulated environments where approximate answers create unacceptable liability, Chata’s approach prioritizes reliability over flexibility.

The funding round reflects a broader market correction within enterprise AI adoption. After early waves pushed general-purpose automation tools promising transformative productivity gains, corporate buyers increasingly demand systems with tighter constraints, clearer explainability, and seamless integration into existing governance processes.

Chata’s platform addresses financial services organizations that face stringent regulatory oversight where AI systems must demonstrate consistent, traceable decision-making. Unlike probabilistic models that may produce varying outputs for identical inputs, deterministic systems follow explicit rules ensuring repeatable results that compliance teams can validate and audit.

The challenge for Chata lies in proving advantages against both established financial software incumbents and fast-moving AI platforms adding compliance layers to general-purpose models. Success requires demonstrating reliability in actual financial deployments while scaling beyond initial niche use cases into broader operational tooling.

Financial institutions have approached AI adoption cautiously due to regulatory requirements around model explainability, bias detection, and decision transparency. Traditional machine learning systems operating as black boxes create compliance risks when regulators demand clear explanations for automated decisions affecting customers or capital allocation.

Chata’s deterministic approach provides financial organizations with automation tools that maintain the predictability and governance controls required in banking, insurance, and investment management. The Series A capital will fund platform development, regulatory compliance features, and expansion into additional financial services verticals.

The funding comes as financial services firms balance competing pressures: demands for digital transformation and operational efficiency against heightened regulatory scrutiny of AI systems. Solutions offering automation without sacrificing auditability address this tension directly, positioning Chata to capture market share as banks and insurers advance beyond pilot projects into production deployments requiring regulatory approval and risk committee oversight.

Microsoft 365 Services Restored Following Widespread Thursday Outage

Posted on by Amita Parul

REDMOND – Microsoft confirmed restoration of Microsoft 365 services following a widespread outage Thursday that disrupted email, collaboration tools, and productivity applications for thousands of enterprise and individual users across key regions.

The incident affected Outlook email delivery, Teams collaboration platform, and other Microsoft 365 endpoint services during peak business hours. Downdetector reported spikes in outage reports as organizations experienced operational interruptions to cloud-dependent workflows.

Microsoft acknowledged the disruption publicly via status channels and responded by redirecting traffic and rebalancing infrastructure loads to mitigate impact. By January 23, the company confirmed access had been restored, though enterprise administrators continued reviewing root causes and system logs to prevent recurrence.

The outage underscores how deeply cloud productivity platforms have woven into global business operations and how quickly disruptions at major providers ripple across organizations. Enterprises relying on Microsoft 365 for email, document collaboration, video conferencing, and business process automation experienced immediate productivity impacts as core communication tools became unavailable.

Cloud service reliability has become critical for distributed workforces where digital collaboration tools enable remote and hybrid work arrangements. When platforms like Microsoft 365 experience outages, organizations lose access to email communications, shared documents, scheduled meetings, and internal messaging, creating cascading disruptions across business functions.

Microsoft operates one of the world’s largest cloud infrastructures supporting hundreds of millions of users globally. The company’s Azure cloud platform and Microsoft 365 services represent mission-critical infrastructure for enterprises across industries, making service availability and incident response capabilities central to customer retention.

The incident adds to ongoing discussions about enterprise dependencies on major cloud providers and the importance of business continuity planning accounting for potential service disruptions. Organizations increasingly evaluate multi-cloud strategies and backup communication channels to maintain operations during platform outages.

Microsoft has not publicly disclosed technical details about the outage’s root cause, though the company’s response involving traffic redirection and load rebalancing suggests infrastructure or capacity management issues rather than security breaches or cyberattacks.

Neurophos Secures $110M Series A for AI Chip Technology

Posted on by Yashika Aneja

AUSTIN – Neurophos, an AI chip startup developing optical processors for machine learning inference, raised $110 million in Series A funding led by Gates Frontier, the investment fund managed by Bill Gates.

The round included participation from Microsoft’s M12 venture arm, Carbon Direct, Aramco Ventures, Bosch Ventures, Tectonic Ventures, and Space Capital. The Austin-based company spun out of Duke University with proprietary technology that uses light-based computing rather than traditional electronic processors.

Neurophos has developed what it describes as metasurface modulators that function as photonic tensor cores, enabling thousands of light-based computing neurons on a single chip. The technology aims to dramatically accelerate AI inference workloads while reducing power consumption compared to conventional GPU-based systems.

The company’s approach addresses growing concerns about the energy intensity of large-scale AI deployments. As enterprises move beyond experimental AI projects into production environments, infrastructure power requirements have become a critical constraint for data center operators and cloud providers.

Photonic computing represents a fundamental departure from silicon-based processors. By performing mathematical operations using optical signals rather than electrical ones, the technology promises both speed advantages and significant energy efficiency gains. Industry analysts suggest photonic AI accelerators could reduce inference costs by orders of magnitude if successfully commercialized.

The Series A funding will accelerate development of Neurophos’s ultra-fast, energy-efficient AI accelerators designed for machine learning inference at scale. The company plans to deploy capital toward advancing chip manufacturing processes and building partnerships with hyperscale cloud providers.

Gates Frontier’s involvement signals strong confidence in photonic computing as a viable path for next-generation AI infrastructure. Microsoft’s M12 participation suggests potential integration opportunities with Azure’s AI cloud services, though no formal partnerships were announced.

Neurophos joins a growing field of alternative AI chip architectures competing with established GPU manufacturers. While graphics processing units from companies like NVIDIA currently dominate AI training and inference markets, startups developing specialized accelerators argue that purpose-built hardware will prove more efficient for production workloads.

The funding comes during a period of intense investment in AI infrastructure companies as venture capitalists seek to capitalize on the computing requirements of increasingly sophisticated models and widespread enterprise AI adoption.

Keyfactor, IBM launch joint post-quantum cryptography solution

Posted on by Shobhit Kalra

CLEVELAND, Ohio: Keyfactor and IBM Consulting announced a joint solution today designed to give enterprises comprehensive visibility into cryptographic assets and accelerate preparation for post-quantum cryptography threats, addressing what security experts describe as one of the most vulnerable dependencies in modern infrastructure.

The collaboration combines Keyfactor’s “industry-leading cryptographic discovery, PKI, digital signing, and certificate lifecycle automation capabilities” with IBM Consulting’s “global cybersecurity expertise, governance frameworks, and enterprise-scale quantum-safe delivery methods, accelerators, and AI-based assets,” according to a press release issued this morning.

Ted Shorter, Keyfactor’s Chief Technology Officer and Co-Founder, stated, “Cryptography sits at the center of every digital interaction, yet most enterprises struggle to see or understand the full scope of their cryptographic footprint.” The partnership addresses critical blind spots where fragmented ownership and inconsistent controls across certificates, keys, algorithms, protocols, and libraries create security vulnerabilities.

Emerging regulations and post-quantum computing guidance are increasing pressure on enterprises to demonstrate control across their cryptographic landscape. The joint solution provides “end-to-end cryptographic discovery and inventory” through “automated discovery” that “reveals where cryptographic assets live across on-prem, cloud, hybrid, and DevOps environments, exposing blind spots and shadow cryptography,” according to the announcement.

Dinesh Nagarajan, Global Partner for Cybersecurity at IBM Consulting, emphasized, “Quantum-safe transformation is more than a cryptographic upgrade; it’s a major operational shift that requires coordination across people, processes, and technology.” The solution enables enterprises to build comprehensive Cryptographic Bills of Materials (CBOM) and structured risk analysis.

The partnership delivers risk scoring, prioritization capabilities, and modern PKI automation that replaces manual workflows with policy-driven processes. The solution aligns with National Institute of Standards and Technology, European Union, and global post-quantum cryptography guidance, creating phased modernization paths for enterprises.

The announcement follows IBM’s development of two algorithms now published among NIST’s first three post-quantum cryptography standards, positioning both companies as leaders in quantum-safe transformation.

Railway Secures $100M Series B to Scale AI-Native Cloud Infrastructure Platform

Posted on by Shobhit Kalra

SAN FRANCISCO: Cloud infrastructure startup Railway announced a $100 million Series B funding round led by TQ Ventures, positioning the platform to challenge legacy cloud providers as artificial intelligence accelerates software development beyond traditional infrastructure capabilities.

The round included participation from FPV Ventures, Redpoint, and Unusual Ventures, bringing Railway’s total funding beyond $130 million. Founder and CEO Jake Cooper disclosed annual recurring revenue exceeds $10 million, according to reports.

Cooper said, “As AI models get better at writing code, more and more people are asking the age-old question; where, and how, do I run my applications? The last generation of cloud primitives were slow and outdated, and now with AI moving everything faster, teams simply can’t keep up.”

Railway rebuilt software and hardware infrastructure from the ground up to eliminate configuration complexity, operating custom data centers with proprietary networking and orchestration. The platform handles approximately 100 billion requests monthly across six million microservices, 20 million deploys, and a quarter-trillion logs for two million users.

Customers report a 10x increase in developer velocity and up to 65% cost savings compared to traditional cloud platforms. Railway charges only for actual usage, avoiding markups common in overprovisioned legacy infrastructure.

The platform serves 31 percent of Fortune 500 companies including Intuit’s GoCo, TripAdvisor’s Cruise Critic, and MGM Resorts, alongside thousands of AI-native startups. Railway achieved 176x revenue growth while adding nearly 200,000 developers monthly.

Schuster Tanger, co-founding partner of TQ Ventures, commented, “Railway is building the infrastructure layer that will power the next era of software. Jake Cooper is an extraordinary talent under whose leadership Railway’s Zero-Ops architecture has been purpose-built for an AI-native world.”

The funding will expand Railway’s global data center footprint, grow its team, and develop tools designed for both human developers and AI systems as the company pursues enterprise adoption.

Andreessen-Backed Inferact Emerges from Stealth with $150M to Commercialize vLLM AI Inference Engine

Posted on by Shobhit Kalra

Artificial intelligence infrastructure startup Inferact launched with $150 million in seed funding at an $800 million valuation to commercialize vLLM, the open-source AI inference acceleration framework developed at UC Berkeley.

The round was co-led by Andreessen Horowitz and Lightspeed Venture Partners, with participation from Databricks Ventures, UC Berkeley Chancellor’s Fund, Sequoia Capital, Altimeter Capital, Redpoint Ventures, and ZhenFund.

Inferact’s founding team includes Databricks co-founder and UC Berkeley computer science professor Ion Stoica, who directs the university’s Sky Computing Lab where vLLM originated in 2023. The project has since attracted contributions from more than 2,000 developers globally.

CEO Simon Mo stated, “We see a future where serving AI becomes effortless. Today, deploying a frontier model at scale requires a dedicated infrastructure team. Tomorrow, it should be as simple as spinning up a serverless database.”

vLLM optimizes AI model inference – the production deployment phase where models generate responses, through innovations like PagedAttention memory management, which eliminates GPU memory fragmentation. The technology enables models to generate multiple tokens simultaneously rather than one at a time, reducing loading times for users.

Co-founder Woosuk Kwon wrote in the announcement, “The complexity doesn’t disappear; it gets absorbed into the infrastructure we’re building,” describing Inferact’s strategy to provide enterprise-grade managed services atop the free open-source core.

Major technology companies including Amazon Web Services, Meta, Google, and Character.AI already deploy vLLM in production environments. The framework currently supports more than 500 model architectures and runs on more than 200 accelerators.]]

Inferact plans to launch a paid serverless version of vLLM that automates administrative tasks like infrastructure provisioning and software updates. The company will continue supporting vLLM as an independent open-source project while building proprietary enterprise features.

The funding follows a broader investment trend toward AI inference infrastructure as industry focus shifts from model training to cost-efficient production deployment at scale.