MAM
Storj Acquires PetaGene, Creator of Distributed Mount Client cunoFS, to Enhance Capabilities for AI and Data-Intensive Industries
ATLANTA and CAMBRIDGE, England – Today Storj announces the acquisition of PetaGene, creator of cunoFS, to build on growth propelled by Storj’s recent acquisition of distributed GPU provider, Valdi. With today’s news, Storj now delivers distributed cloud object storage, distributed on-demand GPU compute, and distributed file storage mount. Together, these capabilities provide seamless access to the distributed cloud for video and AI workloads, enhancing performance, security, cost, and carbon savings to more customers at the edge and around the world.
cunoFS was developed by PetaGene as a high-performance mount client, which is now poised to revolutionize cloud workflows for the data-heavy media and entertainment industry, and for users of all cloud platforms and object storage vendors. Adding to its Linux client, cunoFS launched a Windows-native client at IBC 2024, and its macOS-native client will launch later this year. PetaGene also provides secure, transparent, lossless compression to decrease the size of genomic data, reducing storage costs and data transfer times by 60% to 90% while giving faster access in the original file formats without a decompression step.
PetaGene works with leaders in genomics and clinical research including the NHS in England and Wales, AstraZeneca, NVIDIA, CeGaT, Princess Máxima Center for Pediatric Oncology, the largest pediatric cancer center in Europe, and one of the top three children’s hospitals in the US. These data heavy arenas are ideally suited to benefit from this acquisition. Jacob Willoughby, Storj CTO, noted: “Storage is vital in AI training, and is seldom talked about. As models grow to include training on large amounts of image, video, and text, data grows significantly. The integration of cunoFS into our ecosystem marks a significant milestone in our goal to revolutionize cloud infrastructure for AI. cunoFS enables performant data loading with intelligent prediction of what will be needed in advance. By combining distributed storage and GPU with cunoFS’s high-performance file system, we’ve created an unparalleled platform for training and deploying large language models like LLaMA, GPT-4, and beyond.”
Vaughan Wittorff, Co-Founder and CCO of PetaGene said, “Thanks to this acquisition, more customers in sports and news broadcasting, post production, VFX studios and ad agencies can get up and running faster with a drag-and-drop, plug-and-play approach to accessing the benefits of distributed cloud object storage all over the world. We have strong complementary expertise and relationships in AI, genomics and more, and in terms of growth and market leadership – the sky is the limit for us as part of Storj. PetaGene’s current customer base uses their products to help manage 100s of PB of scientific data, and we look forward to serving even more of their storage, compute, and file needs in the years to come.”
This news brings the value of Storj to more users to set up and run projects even faster. cunoFS requires no additional configuration and doesn’t have a proprietary format that locks-in users like other file management systems. This democratizes data service, giving users more freedom, flexibility and speed.
“On the heels of the expansion we experienced as a result of bringing Valdi into the fold, we knew cunoFS was another close partner that would deliver its full potential as a part of Storj,” said Colby Winegar, Storj Chief Revenue Officer. “cunoFS satisfies a painful unmet need, the team is extremely talented and cunoFS creates great synergy with Storj – especially in M&E. Their product is a perfect solution for those who want fast, file system-based cloud storage. This acquisition also accelerates our joint efforts to advance and simplify AI learning and inference when utilizing our on-demand GPUs.”
Storj and cunoFS already work with joint customers including Cambridge University / DiRAC, and partners including Cambridge Computer, CineSys LLC and Tyrell. Brent Angle, CTO of media and broadcast systems integrator CineSys said, “cunoFS delivers highly responsive and POSIX compliant file system access to content on cloud or on-prem object storage platforms, without changing the data format. Combining cunoFS and Storj, creative professionals can access content in an instant, knowing it is protected in a non-proprietary format on the resilient, scalable and cost effective Storj platform. This is an extremely powerful joint solution already, and we look forward to the innovation their teams will bring to the market as a united entity.”
PetaGene will continue to operate as a wholly owned subsidiary of Storj, and all current PetaGene employees will continue on as employees. PetaGene and Storj will continue to support all current PetaGene products and customers, and cunoFS will continue to be available for users of all object storage vendors and cloud platforms.
Brands
Wipro hires 7,500 freshers, withholds FY27 hiring outlook
Profit rises to Rs 3,522 crore, Rs 15,000 crore buyback announced.
MUMBAI- Hiring may be on, but visibility is off, Wipro is adding talent even as it pauses the crystal ball. The company hired 7,500 freshers in FY26 but stopped short of offering any hiring outlook for FY27, underscoring the uncertainty gripping the IT services sector as it pivots towards an AI-led operating model.
The disclosure came alongside its fourth-quarter earnings, where management flagged volatile demand conditions and refrained from committing to future workforce expansion. Chief human resources officer Saurabh Govil noted that over 3,000 of the total hires were onboarded in the March quarter alone, signalling continued intake despite a lack of clarity on deployment pipelines.
This divergence active hiring without forward guidance reflects a broader industry pattern where talent acquisition continues even as deal conversions remain uneven and client spending cycles stretch. Wipro expects its IT services revenue for the June quarter to range between a decline of 2 per cent and flat growth sequentially in constant currency terms, reinforcing near-term caution.
Chief executive officer Srini Pallia pointed to artificial intelligence as both a disruptor and an opportunity. He said evolving client priorities are pushing the company towards outcome-driven engagements, with Wipro increasingly focusing on a services-as-software model through its AI Native Business and Platforms unit. The shift marks a structural change from traditional headcount-led growth to AI-enabled delivery frameworks.
The company has already committed over $1 billion to its AI ecosystem, with investors closely watching how these investments translate into revenue. For now, the numbers present a mixed picture. Net profit rose sequentially to Rs 3,522 crore, while revenue grew 3 per cent to Rs 24,236 crore. However, core IT services performance remained under pressure, with full-year revenue declining 0.3 per cent in dollar terms and 1.6 per cent in constant currency.
Large deal bookings offered a counterpoint, rising 45.4 per cent year-on-year to $7.8 billion, highlighting a widening gap between deal wins and actual revenue realisation. On a quarterly basis, IT services revenue slipped 1.2 per cent sequentially, signalling continued softness in execution.
Margins, however, told a more optimistic story. Operating margins expanded to 17.3 per cent in the fourth quarter, up from 14.8 per cent in the previous quarter, reflecting improved cost discipline. That said, the company cautioned that upcoming wage hikes and the ramp-up of large deals could exert pressure going forward.
Attrition stood at 13.8 per cent in the March quarter, indicating stabilisation after periods of elevated churn. Alongside its earnings, Wipro also announced a Rs 15,000 crore share buyback, reinforcing its focus on shareholder returns, with a payout ratio of 88 per cent over the past three years.
Taken together, the numbers capture a company in transition investing in AI, maintaining hiring momentum, but navigating a demand environment where growth is uneven and visibility remains limited.
