CompaniesInvestorsPeople
Home
Loading

aVenture is in Beta: research coverage is expanding as we build, so please independently verify key details before making investment decisions.

aVenture is in Beta: research coverage is expanding as we build, so please independently verify key details before making investment decisions.

Get in Touch

  • Contact

  • Request a Demo

  • Request Data Updates

  • Add a Company

Research

  • Companies

  • Investors

  • People

aVenture

  • Download App

  • Pricing

Download the aVenture Research beta for iOS and iPadOSDownload aVenture Research on the Mac App Store

Resources

  • Documentation

  • Use Cases

  • CLI

  • MCP

  • Feature Requests

  • Sitemap

Member

Backed by

Ask AI about aVenture

© aVenture Investment Company, 2026. All rights reserved.

San Francisco, CA, USA

Privacy · Terms of Service

aVenture Investment Company ("aVenture") is an independent research platform providing detailed analysis and data on startups, venture capital investments, and key industry individuals. It is not a registered investment adviser, broker-dealer, or investment advisor and does not provide investment advice or recommendations. The data provided by aVenture does not constitute recommendations or advice, whether by methodology, analysis, AI-generated content, or a statement written by a staff member of aVenture.

aVenture is not affiliated with any of the people, companies, organizations, government agencies, regulatory bodies, or investment funds we provide coverage for on this site unless explicitly stated otherwise. Users assume full responsibility for decisions made based on information obtained from this platform. Links to external websites do not imply endorsement or affiliation with aVenture. Any links that provide the ability to invest in a primary or secondary transaction in a company are for convenience only and do not constitute solicitations or offers to buy or sell an investment. Investors should exercise heightened precaution and due diligence when investing in private companies, especially those not independently audited.

While we strive to provide valuable insights with objectivity and professional diligence, we cannot guarantee the accuracy of the information provided on our platform. Before making any investment decisions, you should verify the accuracy of all pertinent details for your decision. To the fullest extent permitted by law, aVenture shall not be liable for any direct, indirect, incidental, consequential, or financial damages arising from use of this site, whether by consumers of its contents directly or by persons or organizations covered by our research, even if we are advised of the possibility. Our best-efforts processes and correction request forms do not create a warranty or duty of care.

Profiles on this platform may include content generated in part by large language models (LLMs, artificial intelligence) that aggregate publicly available sources (e.g., SEC EDGAR, public filings, press releases). Source attribution is provided where known; always verify statements and claims here against original sources before relying on any data. Content on our site may contain inaccuracies, omissions, or what are commonly called 'hallucinations' if generated in part or in full by AI / LLMs. The risk can also exist even when content is written by a human, as internal and third-party sources may also have inaccuracies for the same or different reasons. While we randomly audit a proportion of content, this is not exhaustive.

We recommend that an independent auditor be hired to verify the accuracy of the information before relying on it for any sensitive decisions. By accessing this platform, you agree not to rely solely on any information generated by AI, aggregated, or sourced or written otherwise on this site, for investment, financial, or other decisions. aVenture assumes no responsibility for inaccuracies, omissions, or hallucinations. You must independently verify all data from primary sources. Use of this platform constitutes your waiver of claims for reliance-based damages, including negligent misrepresentation. To report an error, request a correction, or dispute information about a company or individual, contact us via our request data updates form.

Loading
Loading
Home
News
Celestial AI raises $100M to transfer data using light-based interconnects

From TechCrunch

By Kyle Wiggers

June 28, 2023

Celestial AI raises $100M to transfer data using light-based interconnects

Celestial AI raises $100M to transfer data using light-based interconnects

David Lazovsky and Preet Virk, technologists with backgrounds in semiconductor engineering and photonics, came to the joint realization several years ago that AI and machine learning workloads would quickly encounter a “data movement” problem. Increasingly, they predicted, it would become challenging to move data to and from compute hardware as AI models scaled past what could be kept on the die of any one memory chip.

Their solution — architected by Phil Winterbottom, previously a researcher at the distinguished Bell Labs — was an optical interconnect technology for compute-to-compute, compute-to-memory and on-chip data transmission. Along with Winterbottom, Lazovsky and Virk founded a startup, Celestial AI, to commercialize the tech. And now, that startup is attracting big backers.

Celestial AI today announced that it raised $100 million in a Series B round led by by IAG Capital Partners, Koch Disruptive Technologies and Temasek’s Xora Innovation fund. The tranche, which brings Celestial AI’s total raised to more than $165 million, will be used to support the production of Celestial’s photonics platform by expanding the company’s engineering, sales and technical marketing departments, according to CEO Lazovsky.

Celestial has around 100 employees at present — a number that Lazovsky expects will grow to 130 by the end of the year.

“Today, compute and memory are closely coupled. The only way to add more high bandwidth memory is to add more compute, whether the additional compute is required or not,” Lazovsky told TechCrunch via email. “Celestial’s tech enables memory disaggregation.”

In a data center, memory is often one of the most expensive resources — in part because it’s not always used efficiently. Because memory is tied to compute, it’s challenging — and sometimes impossible, due to bandwidth constraints and sky-high latency — for operators to “disaggregate” and pool the memory across hardware within the data center.

According to an internal Microsoft study, up to 25% of memory in Azure is “stranded,” or left over, after the servers’ cores have been rented to virtual machines. Reducing this stranded memory could cut data center costs by 4% to 5%, the company estimated — potentially significant savings in the context of a multibillion-dollar operation.

Celestial — which began as a portfolio company of The Engine, the VC firm spun out of MIT in 2016 — developed an ostensible solution in its photonics-based architecture, which scales across multiple-chip systems. Using light to transfer data, Celestial’s tech can beam information both within chips and chip-to-chip, making both memory and compute available for AI — and other — workloads.

Celestial

Image Credits: Celestial

Celestial also claims that its tech can reduce the amount of electricity necessary for data movement, indirectly boosting a chip’s performance. Typically, chips devote a portion of the electricity they draw to data movement between their circuits, which takes away from the electricity that the chip can direct to computing tasks. Celestial’s photonics reduce the power required for data movement, allowing a chip to — at least in theory — increase its compute power.

Celestial’s photonics tech, which is compatible with most industry interconnect standards (e.g. CXL, PCIe), delivers 25x higher bandwidth and 10x lower latency and power consumption than optical alternatives, the company asserts.

“With the growth in AI , especially large language models (LLMs) and recommendation engine workloads, there is a shift towards accelerated compute,” Lazovsky said. “The key problem going forward is memory capacity, memory bandwidth and data movement — i.e. chip-to-chip interconnectivity — which is what we are addressing with Celestial’s photonic fabric.”

Celestial is offering its interconnect product through a licensing program, and says that it’s engaged with several “tier-one” customer including hyperscalers and processor and memory companies.

The interconnect product appears to be priority number one for Celestial. Celestial sells its own AI accelerator chip, dubbed Orion, built on the company’s photonics architecture. But as investors told TechCrunch in a recent piece for TC+, AI photonics chips have yet to overcome engineering challenges that would make them practical at scale. Unless Celestial stumbled upon breakthroughs in the areas of data-to-analog conversion and signal regeneration — top stumbling blocks for today’s photonics chips — it’s unlikely that Orion is much further along than the competition.

Chip aside, Celestial has a number of competitors in a photonic integrated circuit market that could be worth $26.42 billion by 2027.

Ayar Labs, which makes chip solutions based on optical networking principles, has raised over $200 million in venture capital since its founding in 2015. Ravonus, another rival, recently landed a $73.9 million investment.

There could be consolidation ahead in the broader optical interconnection space, though. Around three years ago, Marvell bought Inphi, an optical networking specialist, for $10 billion. After a period of quiet, Microsoft last year acquired Lumenisity, a startup developing high-speed optical cables for data center and carrier networks.

Both Inphi and Luminensity were targeting different use cases with their tech. But the enthusiasm from Big Tech around optics and photonics is worth making a note of.

“Our photonics technology is truly differentiated and is unique with superior characteristics,” Lazovsky said. “Given the growth in generative AI workloads due to LLMs and the pressures it puts on current data center architectures, demand is increasing rapidly for optical connectivity to support the transition from general computing data center infrastructure to accelerating computing.”

Samsung Catalyst, Smart Global Holdings, Porsche Automobil Holding SE, The Engine Fund, imec.xpand, M Ventures and Tyche Partners also participated in Celestial’s Series B.

Celestial AI raises $100M to transfer data using light-based interconnects by Kyle Wiggers originally published on TechCrunch

Most Recent

Always on, always listening: New AI devices are pushing legal limits and could put users in jeopardy

AI always-listening wearables from Apple, Amazon, Meta and other startups are getting creative with privacy rules and fueling concerns about covert recordings.

Oct 18, 2026

47+ large US data center projects were delayed, withdrawn, or blocked in 2026; Bernstein says ~35% of the planned US data center pipeline is credible

A vast bet on the future of the technology is running into the unforgiving economics of the physical world

Oct 17, 2026

AI debt worries mount as CoreWeave's bond yield tops 15%, insuring SoftBank debt gets pricier, and some Oracle debt trades near 80 to 90 cents on the dollar

Debt trouble at CoreWeave, Oracle and SoftBank raises questions about whether there are broader problems with the data center build-out.

Oct 17, 2026

Exclusive: ‘I’ve seen this movie before’: A Michigan-raised ex-Tesla exec raises $45 million to break China’s grip on batteries

Steven Prast is old enough to remember when a mobile phone came in a bag. It was too heavy to carry around, so most people mounted it in the car.

Oct 17, 2026

Similar Posts

Cornelis Networks raises $205M and scales up and out with its new Active Compute Fabric

Data center infrastructure startup Cornelis Networks Inc. is taking a major leap forward with the launch of a new Active Compute Fabric architecture to support scale-up and scale-out networks for artificial intelligence workloads. The new fabric was announced alongside a strategy collaboration with

Sep 14, 2026

Nvidia’s next multibillion-dollar market: Breaking the AI factory out of the data center

Nvidia's next multibillion-dollar market: Breaking the AI factory out of the data center - SiliconANGLE

Aug 26, 2026

Xscape is building multicolor lasers to connect chips within datacenters

The GPUs and other chips used to train AI communicate with each other inside datacenters through “interconnects.” But those interconnects have limited bandwidth, which limits AI training performance. A 2022 survey found that AI developers typically struggle to use more than 25% of a GPU’s capacity. One solution could be new interconnects with much higher bandwidth, according to Vivek Raghunathan, the CEO and co-founder of startup Xscape Photonics. The secret sauce, he says, is silicon photonics

Oct 15, 2024

As AI data centers hit power limits, Peak XV backs Indian startup C2i to fix the bottleneck

C2i has raised $15 million as it tests a grid-to-GPU approach to reducing power losses in AI data centers.

Feb 15, 2026