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Delos Data designs hardware and infrastructure tailored for AI inference in enterprise data centers. It builds high-performance servers and specialized interconnects to optimize how compute is distributed and memory is connected, with emphasis on chiplet integration and advanced packaging. The company focuses on inference-specific networking and hardware for always-on AI deployments, plus software monitoring to provide real-time visibility into the infrastructure. Its goal is to deliver reliable, scalable enterprise AI inference with predictable performance and straightforward deployment at scale.
Industries
Hardware
Industrial & Manufacturing
AI & Machine Learning
Company Size
1-10
Company Stage
Early VC
Total Funding
$100M
Headquarters
Palo Alto, California
Founded
2025
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Total Funding
$100M
Above
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Funded Over
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Delos Data targets heterogeneous AI with data interface. Delos's Apollo chiplet is designed to bridge different endpoint semantics and interconnects, creating a low-latency domain spanning GPUs, accelerators, CPUs and memory. SANTA CLARA, Calif. - Delos Data is adding silicon to its portfolio, the startup announced at the AI Infra Summit. Delos previously announced data center orchestration software, Mosaic, and a new server architecture, Asterion, for huge scale-up domains, but is now working on Apollo, a data interface chiplet. Apollo comes either as a 30+ Tbps I/O chiplet that sits next to an XPU, as a 10+ Tbps near-packaged optical interface, or on a 400+ Gbps card for CPUs and memory endpoints. It provides endpoints with guaranteed bandwidth and latency, handling load balancing, topology, and failure handling so the endpoint doesn't have to do it. Delos is targeting order-of-magnitude improvements in speed, resiliency, and scale versus what endpoints can do today. The company also announced that it has raised more than $100 million in venture capital. New AI infrastructure will cater to either regular inference, agentic AI, or both, Delos Data CTO Dan Daly told EE Times. Partner Content
Delos Data raises $100M+ for inference hardware and AI clusters. Application Infrastructure September 16, 2026 Highlights. * Delos Data has raised more than $100 million in funding from Matrix, Playground, Socratic Partners, Capricorn, Matter Venture Partners, and IAG. * The startup introduced its first product three months ago and also announced the Delos Nonstop AI Data Interface. * Delos said the new funding will support hiring more engineers and expanding sales efforts. Delos Data Inc., a startup that develops hardware for artificial intelligence clusters, has raised more than $100 million in funding. The capital came from Matrix, Playground, Socratic Partners, Capricorn, Matter Venture Partners, and IAG, with angel investors from the data center hardware industry also contributing. The raise was announced on Tuesday and arrived three months after the company debuted its first product. The Delos Nonstop AI Server is a computing appliance optimized for inference. Customers can equip it with up to four graphics cards from external suppliers, and the accelerators attach to the system's motherboard through an open-source interconnect called OAM. Customers can also link multiple Nonstop AI Servers into a cluster. The machines exchange data via OSFP, an open-source routing technology. Delos said each of the server's four chips has nine OSFP ports with 1.6 terabits per second of bandwidth apiece, which it said gives the system network capacity comparable to Nvidia Corp.'s Rubin appliances. Delos also announced the Delos Nonstop AI Data Interface, a chip designed to work with the Nonstop AI Server and connect it to the network of the inference cluster. The company said the chip provides 10 times lower latency than rival products and is more efficient and scalable. It also monitors the host cluster for malfunctions, including graphics card crashes and network link outages, and automates some recovery tasks. Delos said the funding will be used to hire more engineers and accelerate sales efforts. The company sells the technology in three forms, including a PCIe card, a chiplet that can process more than 30 terabits of traffic per second, and a near-packaged optics version with a capacity of over 10 terabits per second. company spotlight SoftIron. SoftIron makes the products that underpin the next evolution of IT infrastructure. Its blueprint is radical. Taking full control over design and manufacture of platforms optimised to transform IT infrastructure, its highly integrated products reduce space and energy footprints while delivering extraordinary performance. Challenging traditional IT manufacturing & organisational strategy, IT Infrastructure has developed a model that enables IT Infrastructure to create a more resilient and connected business for the customers IT Infrastructure serve. A commitment to openness, transparency, and simplicity helps address emerging multi-faceted threats while eliminating the vendor "lock-in" so common elsewhere. more top stories Infrastructure as a Service (IaaS) September 19, 2026 * GDT executive Chris Kapusta said the company has built a strong neocloud presence through 30 years of systems integration experience. * Kapusta said GDT has been selling AI infrastructure and related services to roughly 20 neoclouds. * He said about 25% of those neoclouds have received backing from Nvidia in the form of equity investments. Before Softcat announced its acquisition of GDT, an executive at the Dallas-based solution provider described how Nvidia-backed funding helped the company win AI infrastructure deals with neocloud customers. Chris Kapusta, vice president of advisory and transformation, said GDT has a strong neocloud presence built on 30 years of systems integration work. Softcat is buying GDT for an enterprise value of $1.05 billion, gaining a U.S. systems integration business that has sold AI infrastructure and related services to roughly 20 neoclouds. Kapusta said these customers are focused almost entirely on meeting demand for AI compute. He also said the company has been selling infrastructure into neoclouds that are trying to build rapidly for enterprise demand. Kapusta said Nvidia has played a significant role by providing investments that help some neoclouds gain access to AI systems. He said about 25% of GDT's neocloud customers have received Nvidia backing through equity investments. According to him, those customers tend to be more qualified and better funded than some newer entrants. He added that some neoclouds are still struggling to secure financing for expensive AI infrastructure. Kapusta also said a couple of GDT's neocloud customers are in very early discussions about more complex financing arrangements involving Nvidia. He said the market is large and there is room for the channel to play a role. He added that Nvidia's activity is meant to support existing demand and help accelerate GPU- and AI-driven infrastructure coming online. Application Infrastructure September 18, 2026 * Dbt Labs and Fivetran completed their merger on June 1 and are operating as "Fivetran + dbt Labs" for now. * The combined company plans to merge its partner programs and partner portals in February 2027. * Executives said the new company is focusing on AI data infrastructure, partner enablement and simplified deal registration. Dbt Labs and Fivetran have completed their merger and are moving ahead with plans to combine their partner programs as they target the AI data infrastructure market. The new company, which does not yet have a name, is already operating under a single board and leadership team and is using the temporary name "Fivetran + dbt Labs." At the dbt Summit in Las Vegas, executives outlined plans to merge the partner programs and partner portals in February 2027. The company also said it will introduce a new partner tier system and a unified partner portal. More immediate changes include updates to deal registration, reporting and enablement designed to improve the partner experience. Shawn Toldo, vice president of the company's worldwide partner organization, said the company is looking to simplify partner operations through October and November, including improving partner enablement and streamlining co-selling efforts. The company is also offering a virtual educational series to help solution providers deliver the dbt Labs-Fivetran platform. Tristan Handy, founder and CEO of dbt Labs and now president of the combined company, said the two technologies already work together at the platform level. He said the company is now largely finished combining internal systems and processes, including human resource management and benefits. Fivetran CEO George Fraser is serving as CEO of the new entity. Brooklyn Data executive vice president of data and AI David Gelman said partners and customers will benefit from simplified go-to-market operations and fewer vendors to coordinate with. He said the combined company could make it easier to operate and ingest the data and metadata needed for agentic AI use cases.
Delos Data tries to loosen Nvidia's networking grip. Delos Data has unveiled a new interconnect architecture designed to keep AI builders from becoming permanently locked into one vendor's networking stack. According to HPCwire the outfit was founded in 2025 by Delos Data chief executive Ed Doe and chief technology officer Dan Daly. Their backgrounds include Broadcom, Intel, Fulcrum Microsystems and Barefoot Networks. At the AI Infra Summit on 15 September 2026, Delos unveiled its Nonstop AI reference architecture, dubbed MoXI. The name covers its mixture of interconnects, XPUs, memory, storage, physical layers, topologies, networks and models. The hardware will come in three forms. An I/O chiplet offers more than 30 Tbps, near-packaged optics provide more than 10 Tbps, and a PCIe card delivers more than 400 Gbps. Delos wants interfaces that work across copper, pluggable optics, and emerging co-packaged optics. Protocol support includes Nvidia's NVLink, UALink, Ethernet and InfiniBand across scale-up, scale-out and larger distributed systems. The company claims its Nonstop AI products can operate at about 100 nanoseconds of latency, compared with microseconds for a conventional NIC. "The data interface to endpoints in AI workloads is a critical enabler of performance. It stitches everything together in the right way," Daly said. Delos claims its Data Interface targets 10x faster performance, 10x stronger resiliency and 10x greater scale than endpoints can achieve today. Hardware handles recovery from dead accelerators, broken links and routine software updates. The bigger idea is to let expensive compute from different suppliers talk without years of joint engineering. Delos says its interface can bridge different data semantics between GPUs, dataflow engines, CPUs, memory and flash. That could matter as AI infrastructure becomes less uniform. Nvidia Blackwell GPUs provide huge low-precision compute performance, while machines such as Cerebras' Wafer-Scale Engine take a very different approach to shifting and processing data. Delos has meanwhile released Morpheus, a PCIe development and testing card for validating IP against real workloads and different network topologies. Its Mosaic software is already in production, while the Asterion AI server is scheduled to begin customer sampling at the end of 2026. The company has raised more than $100 million from investors including Matrix, Playground, Socratic Partners, Capricorn's Technology Impact Fund, Matter Venture Partners and IAG. Delos plans to spend the cash to expand its hardware and software engineering teams and accelerate product development and sales. Sep 16, 2026
AI networking startups race to replace Nvidia's NVLink. Intel spin-off Cornelis and newcomer Delos Data pitch open alternatives for scaling AI beyond the rack Published Tue 15 Sept 2026 // 20:56 UTC As Nvidia expands its influence through its NVLink Fusion tech, rival networking vendors are scrambling to bring alternative interconnects and switches to market. At the AI Infra Summit this week, Delos Data and Cornelis Networks officially entered the scale up networking race. Scale-up fabrics, like NVLink, are what have allowed Nvidia to make eight, 72, and now 576 GPUs behave as one enormous AI accelerator. To catch up, rivals like AMD have embraced emerging protocols like Ultra Accelerator Link. Today, these protocols are largely being tunneled over standard Ethernet switches. For instance, AMD is using Broadcom's 102.4 Tbps Tomahawk 6-based switches connecting to custom I/O dies on the MI455X. Purpose-built UALink switches and physical interconnects remain elusive, but that won't be the case for long if Cornelis and Delos have their way. The two companies are approaching this challenge from a few different angles, including standardization, software optimization, and physical hardware. Setting the standard for the Never-Nvidia network. At AI Infra on Monday, HPC-centric networking vendor Cornelis introduced the Active Compute Fabric (ACF), which seeks to establish an open architecture for scale up and scale out networking that integrates programmable compute into the fabric. The standard signals Cornelis' entry into the scale up networking arena. Spun out of Intel in 2020, Cornelis' Omni-Path tech was originally designed as a scale-out interconnect for high-performance computing applications, including supercomputers like Trinity and Lynx. With the imminent launch of the company's 800 Gbps-capable CN6000-series switches and NICs, the company has its sights set not only on bringing its tech to a broader audience through the open Ultra Ethernet protocol, but also on scale-up networking. ACF expands on the mission of technologies like UALink and the Ethernet for Scale-Up Networking, another scale up networking protocol, to set a baseline for in-network compute capabilities across a wide range of hardware, not just Cornelis' own CN-series parts. One of the key technologies behind Nvidia's NVSwitch ASICs is support for SHARP, which allows for things like in-network collectives to be offloaded to the switch ASICs, freeing up GPU compute and cutting down on communication overheads. Collective acceleration isn't new by any means, with major networking vendors from Broadcom to Cisco having implemented it in some capacity. As an open architecture, ACF appears to set a least common denominator so that customers deploying these systems know exactly what they're getting. However, it doesn't stop there. Cornelis sees opportunities to accelerate a variety of other functions. Hypriot has detailed a few below: * KV cache offloading used to store and retrieve model state across multiple sessions. * MoE expert dispatch to reduce duplicate transfers and communication overhead for mixture-of-experts models during inference and training. * Message passing interface offload for HPC-centric applications. * In fabric checkpointing for failure recovery during training and other large workloads. "Communications overhead and synchronization can leave expensive accelerators underutilized," the company explained. These in-network accelerators "allow the network to operate on data as it moves through the system." According to Cornelis, the savings potential from reclaiming that idle compute is significant. "In a 100,000 GPU system, Cornelis modeling of public data shows that roughly half of all GPU hours are spent waiting for data, worth about $1.68 billion a year in wasted capacity and 500 GWh of power." As usual, take these claims with a grain of salt. However, reclaiming GPU idle time would equate to significant savings. Eliminating all the bottlenecks that contribute to them is easier said than done. A new kind of NIC for the AI age. While Cornelis champions its ACF architecture, Delos Data, a startup founded by former Barefoot Networks and Intel execs, aims to tackle the physical layer with a series of new network reference designs. Marketed under its Nonstop AI portfolio, the network interfaces span the full gamut of connectivity from co-packaged interconnects to more traditional NICs. The idea, the company explains, is to provide customers with a system-level blueprint for speeding up data movement between endpoints and enabling larger compute domains scaling beyond a single rack. Delos' data interface will be offered in three form factors. The first is an I/O die capable of more than 30 Tbps of aggregate bandwidth or about 8 TB/s in either direction. That's more than double the interconnect bandwidth of either Nvidia's or AMD's latest accelerators, which cap out at 3.6 TB/s. Just how competitive that ends up being will depend on when Delos' I/O chiplets actually see deployment. That timeline is going to depend heavily on integration since those I/O dies need to be integrated directly into the accelerator package, which requires a high-degree of co-design. Critically, Delos isn't trying to trap its customers in a walled garden to the same extent that Nvidia does with its NVLink Fusion I/O dies or IP. At least as of writing, NVLink Fusion still requires customers to buy NVSwitches for scale up networking. Delos' chiplets are protocol agnostic. They don't care whether you're using ESUN, UALink, or something else. Chip designers that'd rather focus their efforts and capital on the AI bits of their accelerators - which, it turns out, applies to most hyperscalers - could simply license Delos' chiplet design. This protocol agnosticism also extends to Delos' near-packaged optics (NPO) tech, which will integrate a 10-plus Tbps data interface - that's 2.5 TB/s bidirectional bandwidth in Nvidia speak - with optics engines from leading optics suppliers. Rack scale systems, like Nvidia's NVL72, have largely relied on copper interconnects up to this point due to power constraints. As systems grow from 72 GPU rack systems to row-scale clusters with 576 and eventually 1,152 GPUs, optics become unavoidable. While integrating optics directly into the accelerators is possible using tech available today, the blast radius of a failed optical module is considerable. NPO offers an alternative. Copper interconnects are used within the rack, with optics provided via user-serviceable NPO modules between racks. Finally, Delos is working on a 400-plus Gbps NIC, which like the rest of its data interface offerings is protocol agnostic. This is arguably the least surprising entry in the entire lineup. Scale out networks are still going to be required for large training clusters as well as for front-end access and storage networks. These interfaces build on Delos' existing compute reference design, which Hypriot looked at during Computex, as well as its Nonstop AI software platform, which is designed to facilitate the configuration and monitoring of these switched fabrics or meshes in order to enable dynamic rerouting of traffic in the event of a link failure. Telemetry gathered by its data interface offerings allows for even greater visibility into the network, allowing for faster rerouting and recovery. Fueling competition. Investors appear more than eager for more competition in the scale up arena. Alongside its product announcements, Cornelis announced approximately $205 million in funding to bring its next generation of scale up and scale out networking products to market. Meanwhile, Delos Data announced Tuesday that it's now raised more than $100 million in funding with support from venture capital firms Matrix, Playground, and Socratic Partners among others.(R)
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Industries
Hardware
Industrial & Manufacturing
AI & Machine Learning
Company Size
1-10
Company Stage
Early VC
Total Funding
$100M
Headquarters
Palo Alto, California
Founded
2025
Find jobs on Simplify and start your career today