WekaIO

WekaIO

AI-native data platform for high-performance workloads

Overview

WEKA provides an AI-native data platform that is cloud- and hardware-agnostic for performance-intensive AI, ML, and GPU workloads. The WEKA Data Platform brings data from on-premises, cloud, edge, and multicloud into dynamic pipelines to speed up data access and processing. It differentiates by offering a single scalable data platform across infrastructure footprints with emphasis on energy efficiency and high performance at scale. The goal is to replace data silos with unified, fast storage and data management to accelerate discoveries and insights.

About WekaIO

Simplify's Rating
Why WekaIO is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & Analytics

Enterprise Software

AI & Machine Learning

Company Size

501-1,000

Company Stage

Series E

Total Funding

$465.1M

Headquarters

Campbell, California

Founded

2013

Get referred to WekaIO

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • July 2026 NeuralMesh 6 launched with OCI benchmarks showing 10x token throughput.
  • Backblaze partnership on September 10, 2026 extends WEKA into cold storage retention.
  • Ingram Micro's August 2026 Australia deal expands channel reach and enterprise distribution.

What critics are saying

  • DDN, VAST Data, HPE, Dell, and NetApp now target the same inference stack.
  • Customer concentration remains dangerous if Oracle, WhiteFiber, or Andromeda slow deployments in 2027.
  • If AI storage commoditizes, WEKA becomes a hardware-margin appliance vendor fighting faster clouds.

What makes WekaIO unique

  • NeuralMesh 6 unifies file, object, and GPU-memory acceleration on NVMe.
  • WEKA spans hybrid, cloud, edge, and hardware-agnostic deployments across 50-plus compute providers.
  • WEKApod 3 delivers exabyte-scale density, giving WEKA control over software and appliance economics.

Help us improve and share your feedback! Did you find this helpful?

Funding

Total Funding

$465.1M

Above

Industry Average

Funded Over

7 Rounds

Series E funding typically includes additional rounds after Series D if the company needs more capital. The business is usually stable, and these rounds are typically used for further expansion or to address market challenges.
Series E Funding Comparison
Above Average

Industry standards

$100M
$245M
Stripe
$250M
Reddit
$1.3B
Epic Games
$1.5B
Airbnb

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

↑ 0%

1 year growth

↑ 0%

2 year growth

↑ 3%
Construct for St. Louis
Sep 15th, 2026
Greater St. Louis, Inc., GeoSTL ink MOU to grow region's geospatial economy.

Greater St. Louis, Inc., GeoSTL ink MOU to grow region's geospatial economy. Pictured Above: Ron Kitchens (left) and Mark Munsell Date posted: september 15, 2026. Posted in: regionalism. Greater St. Louis, Inc. and GeoSTL have formalized a partnership aimed at accelerating growth of the St. Louis region's geospatial technology sector, an ecosystem estimated at nearly $5 billion annually. The organizations have signed a memorandum of understanding that builds on their existing relationship and calls for closer collaboration on business attraction and expansion, public relations and public policy. The agreement comes as St. Louis works to capitalize on major investments in geospatial technology, including the $1.7 billion-plus National Geospatial-Intelligence Agency campus in North St. Louis and growing activity around geospatial artificial intelligence. GeoSTL was formed in January and formally launched in February as the regional "backbone" organization for the geospatial ecosystem, succeeding the GeoFutures initiative originally convened by Greater St. Louis, Inc. Its role is to connect industry, government, universities, entrepreneurs, investors and community organizations around a common strategy for growing companies, developing talent and attracting investment. "St. Louis has the assets, expertise, and momentum to lead the nation in geospatial technology," GeoSTL Executive Director Mark Munsell said in announcing the agreement. He said the partnership will strengthen efforts to connect talent, accelerate innovation and turn the region's geospatial assets into long-term economic growth. Greater St. Louis, Inc. Managing Partner Ron Kitchens said formalizing the organizations' relationship will help build on the region's emerging position as a national center for geospatial research and innovation. Working to Attract Geospatial Companies Under the agreement, the organizations will work jointly to attract geospatial companies while supporting companies already operating in the region. The partnership also extends into public policy. Among the initiatives cited by the organizations is support for the Missouri GIS Advisory Council Act, intended to create a formal structure for statewide geospatial strategy and coordination, as well as efforts to restore funding for the Missouri Technology Corporation. The agreement follows another major geospatial announcement in August. GeoSTL is spearheading development of the Spirit of St. Louis AI Innovation Center in partnership with technology companies including World Wide Technology, Google, Amazon Web Services, NVIDIA, Overture Maps Foundation and WEKA. The initiative is intended to provide advanced computing infrastructure for AI and geospatial innovation. Broader Strategies of Careers, Entrepreneurship The broader regional strategy goes beyond technology development. GeoSTL's work includes expanding pathways into geospatial careers, supporting entrepreneurship and commercialization, attracting companies and investment, and measuring progress through job creation, investment and business growth. The organization is also placing particular emphasis on connecting growth in the geospatial sector with economic opportunity in North St. Louis, where the new NGA campus represents one of the largest federal investments in the city's history.

Blocks & Files
Sep 10th, 2026
WEKA partnering Backblaze for its B2 cloud storage.

WEKA partnering Backblaze for its B2 cloud storage. Chris Mellor STORAGE EDITOR Blocks & Files editor Published thu 10 Sep 2026 // 14:03 UTC WEKA, which supplies high-speed unstructured data access for AI and accelerated computing, has a deal with Backblaze to store data needed for re-use in its B2 cloud storage. The two companies say GPUs need extremely fast access to data to stay fed, while the datasets, checkpoints and outputs surrounding those workloads are growing toward enormous scale and that data can need retaining. They are combining WEKA NeuralMesh for performance-sensitive AI and accelerated computing workloads with Backblaze B2 cloud object storage as the capacity layer for large datasets and retained AI assets. In effect, hot data in WEKA and cold data in B2's cloud. Data can be kept on the appropriate tier as it moves through ingestion, training, checkpointing, inference and downstream workflows. You can't keep once hot AI data on flash for ever. Gleb Budman, Backblaze's CEO, said: "AI teams need their GPUs fed and an infrastructure with the performance and capacity to support the full AI data workflow. WEKA has mastered the performance tier. Blocks & Files has spent nearly two decades doing the same for capacity storage. Together, AI teams get a qualified, complete solution to ensure fast and efficient production,. WEKA Chief Strategy Officer Nilesh Patel, neatly put forward WEKA's point of view: "AI workloads are stretching storage in two directions at once. GPUs need microsecond access to data to stay fed, while datasets and checkpoints are growing to exabyte scale. Our collaboration with Backblaze gives customers a validated path to both - without the cost of building and testing that integration themselves. Speed where it matters, scale wherever you need it." For example, raw training data (training sets, media libraries, source files) can reside in B2, move into NeuralMesh when needed for a performance-sensitive workload, and checkpoints and outputs can then return to B2 for retention and future reuse, or in situations where recovery to an earlier stage of testing is necessary. WEKA's Snap-to-Object capability has tested with Backblaze, enabling teams to recover checkpoints or saved inference data from the B2 capacity tier. Backblaze recently signed a $335 million strategic agreement with CoreWeave for that Neocloud to use B2 cloud storage for retained AI data. Coreweave is the fourth major AI cloud infrastructure company to contract with Backblaze in this way. Certification of B2 Cloud Storage for NeuralMesh is underway. Customers can contact Backblaze or WEKA to get started. Bootnote. Scality and WEKA set up a similar deal to the WEKA-Backblaze one, using WEKA's NeuralMesh high-performance storage with Scality RING's cost-efficient object tier, in February this year. Backblaze competitor Wasabi is also providing cloud storage for AI. It has formed a dedicated AI business, and appointed semiconductor and storage veteran Pinaki Mukherjee as SVP and GM to lead it. It says it stores hundreds of petabytes of AI data for frontier model labs, generative AI startups, and Neocloud compute providers worldwide. The new AI business will bring dedicated strategy, partnerships and go-to-market focus for this demand as AI infrastructure matures. Wasabi raised $70 million for AI cloud storage funding in January, and subsequently arranged a $250 million credit facility.

Associated Press
Sep 9th, 2026
Backblaze and WEKA team up to streamline AI data management across lifecycle

Backblaze and WEKA have announced a collaboration to simplify data management across the AI lifecycle. The partnership combines WEKA's NeuralMesh platform, designed for performance-intensive AI workloads, with Backblaze B2 cloud object storage for large-scale data retention. The solution allows AI teams to keep performance-sensitive workloads on WEKA NeuralMesh whilst storing large datasets, checkpoints, and outputs in Backblaze B2. The integration has been pre-validated, eliminating the need for customers to build and test their own systems. Customers can retain raw training data in B2 and transfer it to NeuralMesh when needed for high-performance computing. WEKA's Snap-to-Object capability enables teams to revert to previous checkpoints or recover inference data. Certification of B2 Cloud Storage for NeuralMesh is currently underway. Backblaze serves over 500,000 customers, whilst WEKA is trusted by 30% of the Fortune 50.

ARN
Aug 5th, 2026
Ingram Micro doubles down on AI push with WEKA deal, launches 'Great Migration' initiative.

Ingram Micro doubles down on AI push with WEKA deal, launches 'Great Migration' initiative. 5 Aug 2026 4 mins WEKA and The Great Migration initiative signal Ingram's intent to position itself at the centre of Australia's next phase of AI adoption. Ingram Micro has expanded its Australian AI ambitions on two fronts, signing AI data infrastructure specialist WEKA as an exclusive distribution partner while launching a new industry-wide 'Great Migration' initiative aimed at accelerating AI readiness. Announced at Ingram Micro Experience 2026 in Sydney, the distributor has added WEKA's AI-native data platform to its local portfolio as organisations move beyond AI experimentation and begin investing in the infrastructure, devices and security foundations required for large-scale deployments. Under the agreement, Ingram Micro becomes WEKA's primary route-to-market partner in Australia, providing channel partners access to the vendor's full portfolio, including its NeuralMesh software platform and WEKApod storage and memory appliance, both designed to support demanding AI workloads. The move comes as Australian organisations increasingly shift focus from simply acquiring AI tools to building the underlying infrastructure needed to operationalise AI and achieve measurable returns on investment. According to Ingram Micro, data movement, storage performance and memory capacity are rapidly emerging as critical bottlenecks for businesses scaling AI environments. "While GPUs have become central to many AI deployments, data movement, storage performance and memory constraints are emerging as critical factors in determining AI performance, infrastructure efficiency, and the overall economics of AI," the distributor said. All WEKA products will be available through Ingram Micro's Xvantage platform, allowing partners to package AI data infrastructure with compute, networking, cloud and services offerings. Ingram Micro senior general manager of strategy, AI and emerging vendors John Brown said WEKA strengthens the distributor's growing AI ecosystem. "WEKA is a standout addition to our AI ecosystem," Brown said. "Its focus on performance, efficiency and simplicity perfectly complements its commitment to equipping Australian partners with the tools to deliver production-grade AI infrastructure that drives real business velocity. "With NeuralMesh and WEKApod, partners can now offer customers high-efficiency, scalable solutions that improve GPU productivity, support agentic AI initiatives and deliver superior economics for the most demanding workloads in research, finance, media and beyond." WEKA chief strategy officer Nilesh Patel said Ingram Micro's channel reach and technical capabilities made it a natural fit for the vendor's expansion plans. "Together, we're helping Australian organisations build the data and memory foundation they need to get maximum AI output from their infrastructure," Patel added. The WEKA signing coincides with the launch of The Great Migration, a new Ingram Micro-led initiative designed to help partners capitalise on a wave of workplace modernisation driven by AI adoption and the approaching end of support for Windows 10. Developed in collaboration with Microsoft and backed by vendors including Intel, AMD, Qualcomm, Dell Technologies, HP, Lenovo, ASUS, MSI and Microsoft Surface, the program is designed to help partners guide customers through Windows 11 migrations, AI-ready device refreshes and broader hybrid AI deployments. According to Ingram Micro, Australia's technology market is currently being shaped by three converging forces: growing demand for AI-powered productivity, increased cybersecurity requirements stemming from ageing devices and legacy systems, and pressure on organisations to demonstrate AI return on investment. Ingram Micro director of consumer, client and endpoint, Mo Kandeel said the conversation around AI has changed significantly. "Australia has largely moved beyond asking whether AI matters," Kandeel said. "The next challenge is deploying AI in ways that improve productivity while strengthening security, supporting governance and managing cost." He added that organisations are increasingly evaluating where AI workloads should run across cloud environments, edge infrastructure and endpoint devices. "Rather than treating device refreshes, operating system upgrades and AI adoption as separate projects, organisations are bringing them together as part of a broader workplace transformation," he said. The initiative builds on Ingram Micro's 2025 Race to Upgrade campaign and provides partners with sales and technical enablement, customer workshops, AI PC demonstrations, funding support, incentives and migration programs. Don't miss a thing From its editors straight to your inbox. Get started by entering your email address below. Sasha Karen is a nationally recognised highly commended senior journalist at ARN. With a decade's worth of experience, Sasha serves the local channel community with news and inspiration about channel partners.

Ohsem.me
Jul 30th, 2026
WEKA and Andromeda partner to power AI workloads at global scale.

WEKA and Andromeda partner to power AI workloads at global scale. 30/07/2026 Partnership delivers consistent, high-performance AI storage across Andromeda's global provider network, lowering the total cost of innovation for AI teams CAMPBELL, Calif., July 30, 2026 /PRNewswire/ - WEKA, the AI data and memory infrastructure company, today announced that Andromeda, the platform connecting AI teams with high-performance compute, is integrating the WEKA NeuralMesh platform as a core AI data storage layer for managed GPU clusters. Andromeda's customers can now access a dedicated NeuralMesh or a GPU-native WEKA NeuralMesh Axon deployment to achieve consistent storage performance across any cluster running on any hyperscaler or AI cloud. WEKA and Andromeda: powering AI teams building at the frontier Keeping GPUs Fed Across Every Environment Andromeda is on a mission to make high-performance compute available to every team building at the frontier, so breakthroughs are driven by ideas, not hardware access. The company works with leading AI labs, data centers, and cloud providers, routing training and inference jobs across the global supply chain. Andromeda operates across more than 50 compute providers worldwide, routing training and inference workloads through a growing global fleet of managed clusters. Every cluster on Andromeda's platform must meet the same quality benchmarks regardless of who operates the infrastructure; the company certifies each cluster across GPU, storage, network fabric, and security before it reaches a customer. That standard exposed a hard problem: each provider brought its own storage environment and performance varied cluster to cluster. With WEKA, Andromeda achieves significant performance gains on existing hardware, deployment in minutes, consistency across every provider, and lower storage costs. "Our goal is to enable the global flow of compute, and that means every cluster we deliver has to perform, no matter where the capacity comes from. Standardizing on WEKA NeuralMesh has given our customers hyperscaler-grade consistency with open-market flexibility at the storage and memory layer, where performance is won or lost," said Wil Moushey, CEO at Andromeda. "Idle GPUs are throttling the pace of AI innovation. WEKA helps us ensure every GPU we manage is earning its keep." GPU-Native AI Storage & Memory, Deployed in Minutes When one research lab found its workloads bottlenecked by its cluster's supplied storage, Andromeda deployed NeuralMesh Axon on the same hardware, unlocking the performance the lab needed, without additional infrastructure. NeuralMesh Axon is the GPU-native deployment of the NeuralMesh software platform. It fuses storage directly into Andromeda's GPU servers, converting each cluster's existing NVMe into a unified, high-performance data layer that feeds training and inference at full speed. Because that infrastructure is already racked, powered, and paid for, it adds performance without adding footprint, power draw, or cost. Using the NeuralMesh Kubernetes Operator, Andromeda can stand up a complete NeuralMesh cluster in minutes and manage its full fleet through the same workflows that run every other layer of the stack. Among Andromeda's NeuralMesh deployments, roughly half run NeuralMesh Axon; the rest run dedicated NeuralMesh deployments for customers who need every GPU core and every gigabyte of memory dedicated to their workloads. Wherever it's deployed, NeuralMesh delivers the same performance floor, regardless of which provider's hardware sits underneath it. That reliability allows Andromeda to onboard customers onto clusters that previously had no shared storage. For Andromeda, the impact is evident: * Ready on day one. New NeuralMesh Axon clusters deploy in as little as 10 minutes, so AI teams start running workloads the day their cluster comes online. * Rapid iteration. AI teams building on Andromeda-managed clusters have seen environment startup load times drop from three minutes to 30 seconds, fitting more experiments into every day. * Performance at scale. Andromeda clusters running on NeuralMesh Axon are achieving sustained throughput of over 400 GB per second per cluster and over 6 million IOPS in production. That performance enabled one Andromeda biotech customer to complete metadata-heavy transfers involving one billion files per directory in minutes rather than hours. * Native resilience. When faults threaten to cascade across an Andromeda cluster, NeuralMesh contains them and keeps the cluster available, protecting every customer workload. "Andromeda's first WEKA NeuralMesh Axon deployment took just 10 minutes to stand up from bare metal. That became our blueprint," said Vishvajit Kher, lead architect at Andromeda. "If a cloud provider doesn't offer shared storage, we're no longer blocked. We deploy WEKA NeuralMesh and know it will perform. It's a full-featured system, up to 90% less expensive than market alternatives, delivering savings that compound as we scale. Every dollar flows straight through to benefit the AI teams we serve." "Andromeda is solving one of the hardest problems in AI infrastructure: making compute from more than 50 different providers feel like one platform," said Liran Zvibel, co-founder and CEO at WEKA. "WEKA NeuralMesh extends that promise to the data layer, deploying in minutes and feeding training and inference workloads at full speed on any GPU provider's hardware, anywhere in the world. The teams building on Andromeda can skip the storage question entirely and start innovating. Together, we're helping AI teams reduce time from idea to outcome." Extending to the Newest Generation of AI Infrastructure Andromeda is deploying WEKA NeuralMesh across its global platform, spanning dedicated and GPU-native deployments. The partnership is already extending to next-generation AI hardware as Andromeda scales its global platform. AI teams interested in running workloads on Andromeda can get started at andromeda.ai. About Andromeda Andromeda connects buyers and suppliers of compute through a single platform that makes AI infrastructure easier to buy, sell, and operate - combining the simplicity and reliability of a hyperscaler with the flexibility, speed, and economics of an open market. Buyers get one interface to a global network of compute providers, with reservations, on-demand, and spot capacity validated against consistent benchmarks. Suppliers get the software, expertise, and distribution to acquire customers, run GPU clusters, and monetize capacity at scale. Andromeda serves more than 100 AI customers across 50+ capacity providers, with billions of GPU-hours supported. Learn more at www.andromeda.ai. About WEKA WEKA is the AI data and memory infrastructure company transforming the economics of agentic AI. The WEKA(R) NeuralMesh(TM) platform extends high-performance data storage and GPU memory to wherever they need to run, giving enterprises, AI cloud providers, and AI builders a unified foundation for training, inference, and agentic workloads. With WEKA Augmented Memory Grid, NeuralMesh extends GPU memory capacity by 1000x, accelerating time to first token by up to 20x, and serving 10x more concurrent users from the same GPU footprint, proven in production benchmarks. Trusted by leading global enterprises, frontier labs, and AI cloud providers, WEKA empowers customers to maximize GPU utilization, generate more tokens per watt, lower their cost per token, and scale production AI faster. Learn more at www.weka.io, or connect on LinkedIn and X. WEKA, WEKApod, and the W logo are registered trademarks of WekaIO, Inc. Other trade names herein may be trademarks of their respective owners. WEKA, The Foundation for Enterprise & Agentic AI Innovation 02/07/2026 18/08/2014 13/05/2026 27/04/2026 30/04/2026

Recently Posted Jobs

Sign up to get curated job recommendations

WekaIO is Hiring for 29 Jobs on Simplify!

Find jobs on Simplify and start your career today

Don't see your dream role? Check out thousands of other roles on Simplify. Browse all jobs →