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Datadog Announces Proposed Private Offering of $775 Million of Convertible Senior Notes

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NEW YORK, Dec. 9, 2024 /PRNewswire/ — Datadog, Inc. (Nasdaq: DDOG) (“Datadog”), the monitoring and security platform for cloud applications, today announced that it intends to offer, subject to market conditions and other factors, $775 million aggregate principal amount of Convertible Senior Notes due 2029 (the “notes”) in a private placement (the “offering”) to persons reasonably believed to be qualified institutional buyers pursuant to Rule 144A under the Securities Act of 1933, as amended (the “Securities Act”). Datadog also intends to grant the initial purchasers of the notes an option to purchase, within a 13-day period beginning on, and including, the date on which the notes are first issued, up to an additional $116.25 million aggregate principal amount of notes.

The notes will be general unsecured obligations of Datadog, will accrue interest payable semiannually in arrears and will mature on December 1, 2029, unless earlier converted, redeemed or repurchased. Upon conversion, Datadog will pay or deliver, as the case may be, cash, shares of Datadog’s Class A common stock, par value $0.00001 per share (“Class A common stock”), or a combination of cash and shares of Class A common stock, at its election. The interest rate, initial conversion rate, repurchase or redemption rights and other terms of the notes will be determined at the time of pricing of the offering.

Datadog expects to use a portion of the net proceeds from the offering to pay the cost of the capped call transactions described below and to repurchase for cash a portion of Datadog’s outstanding 0.125% Convertible Senior Notes due 2025 (the “2025 notes”) as described below. Datadog expects to use the remaining net proceeds from the offering for general corporate purposes, which may include acquisitions or strategic investments in complementary businesses or technologies, although Datadog does not currently have any plans for any such acquisitions or investments, additional repurchases or repayment of the 2025 notes and working capital, operating expenses and capital expenditures. If the initial purchasers exercise their option to purchase additional notes, Datadog expects to use a portion of the net proceeds from the sale of the additional notes to enter into additional capped call transactions with the option counterparties as described below and the remainder for general corporate purposes as described above. 

In connection with the pricing of the notes, Datadog expects to enter into privately negotiated capped call transactions with one or more of the initial purchasers or affiliates thereof and/or other financial institutions (the “option counterparties”). The capped call transactions will cover, subject to customary adjustments substantially similar to those applicable to the notes, the number of shares of Class A common stock initially underlying the notes. The capped call transactions are generally expected to reduce the potential dilution to the Class A common stock upon any conversion of notes and/or offset any cash payments Datadog is required to make in excess of the principal amount of converted notes, as the case may be, with such reduction and/or offset subject to a cap.

In connection with establishing their initial hedges of the capped call transactions, Datadog expects the option counterparties or their respective affiliates will enter into various derivative transactions with respect to the Class A common stock and/or purchase shares of Class A common stock concurrently with or shortly after the pricing of the notes, including with, or from, certain investors in the notes. This activity could increase (or reduce the size of any decrease in) the market price of the Class A common stock or the trading price of the notes at that time.

In addition, the option counterparties or their respective affiliates may modify their hedge positions by entering into or unwinding various derivatives with respect to the Class A common stock and/or purchasing or selling shares of Class A common stock or other securities of Datadog in secondary market transactions following the pricing of the notes and prior to the maturity of the notes (and are likely to do so during any observation period related to a conversion of notes or, to the extent Datadog exercises the relevant election under the capped call transactions, following any repurchase or redemption of the notes). This activity could also cause or avoid an increase or a decrease in the market price of the Class A common stock or the trading price of the notes, which could affect a holder’s ability to convert the notes and, to the extent the activity occurs during any observation period related to a conversion of notes, it could affect the number of shares, if any, and value of the consideration that a holder will receive upon conversion of its notes.

Additionally, Datadog expects to repurchase for cash a portion of its 2025 notes in privately negotiated transactions to be entered into concurrently with the pricing of the notes in the offering with or through one of the initial purchasers or its affiliate (the “note repurchase transactions”). The terms of the note repurchase transactions are anticipated to be individually negotiated with each holder of the 2025 notes and will depend on several factors, including the market price of the Class A common stock and the trading price of the 2025 notes at the time of such note repurchase transactions. No assurance can be given as to how much, if any, of the 2025 notes will be repurchased or the terms on which they will be repurchased. Datadog may also repurchase additional outstanding 2025 notes following completion of the offering. This press release is not an offer to repurchase the 2025 notes and the offering of the notes is not contingent upon the repurchase of any 2025 notes.

In connection with any note repurchase transaction, Datadog expects that holders of the 2025 notes who agree to have their 2025 notes repurchased and who have hedged their equity price risk with respect to such 2025 notes (the “hedged holders”) will unwind all or part of their hedge positions by buying the Class A common stock and/or entering into or unwinding various derivative transactions with respect to the Class A common stock or other securities of Datadog. The amount of the Class A common stock to be purchased by the hedged holders or in connection with such derivative transactions may be substantial in relation to the historic average daily trading volume of the Class A common stock. This activity by the hedged holders could increase (or reduce the size of any decrease in) the market price of the Class A common stock, including concurrently with the pricing of the notes, which could result in a higher effective conversion price of the notes. Datadog cannot predict the magnitude of such market activity or the overall effect it will have on the price of the notes or the Class A common stock.

Additionally, in connection with the issuance of the 2025 notes, Datadog entered into capped call transactions (the “existing capped call transactions”) with certain financial institutions (the “existing option counterparties”).  To the extent Datadog effects any note repurchase transactions, it intends to enter into agreements with the existing option counterparties to terminate a portion of the existing capped call transactions in a notional amount corresponding to the number of shares of the Class A common stock underlying the 2025 notes repurchased (such terminations, the “unwind transactions”).  In connection with any such terminations of the existing capped call transactions, Datadog expects such existing option counterparties and/or their respective affiliates will unwind various derivatives with respect to the Class A common stock and/or sell shares of the Class A common stock or other securities of Datadog in the secondary market.  This activity could decrease (or reduce the size of any increase in) the market price of the Class A common stock at that time and could decrease (or reduce the size of any increase in) the trading price of the notes.

Neither the notes, nor any shares of Class A common stock issuable upon conversion of the notes, if any, have been, or will be, registered under the Securities Act or any state securities laws, and unless so registered, may not be offered or sold in the United States absent registration or an applicable exemption from, or in a transaction not subject to, the registration requirements of the Securities Act and other applicable securities laws.

This press release is neither an offer to sell nor a solicitation of an offer to buy any securities, nor shall it constitute an offer, solicitation or sale of any securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to the registration or qualification under the securities laws of any such jurisdiction.

About Datadog

Datadog is the observability and security platform for cloud applications. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for our customers’ entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.

Forward-Looking Statements

This press release contains “forward-looking” statements, as that term is defined under the federal securities laws, including statements concerning the proposed terms and the anticipated completion, timing and size of the proposed offering of the notes, the capped call transactions, the note repurchase transactions and any unwind transactions, the anticipated use of proceeds from the offering, and the potential impact of the foregoing or related transactions on dilution to holders of the Class A common stock and the market price of the Class A common stock, the trading price of the notes or the conversion price of the notes. These forward-looking statements are based on Datadog’s current assumptions, expectations and beliefs and are subject to substantial risks, uncertainties, assumptions and changes in circumstances that may cause Datadog’s actual results, performance or achievements to differ materially from those expressed or implied in any forward-looking statement. These risks include, but are not limited to market risks, trends and conditions. These and other risks are more fully described in Datadog’s filings with the Securities and Exchange Commission (“SEC”), including in the section entitled “Risk Factors” in its Quarterly Report on Form 10-Q for the quarterly period ended September 30, 2024 and other filings and reports that Datadog may file from time to time with the SEC.  Forward-looking statements represent Datadog’s beliefs and assumptions only as of the date of this press release. Datadog disclaims any obligation to update forward-looking statements.

CONTACT INFORMATION

Yuka Broderick
Datadog Investor Relations
IR@datadoghq.com

Dan Haggerty
Datadog Corporate Communications
press@datadoghq.com

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SOURCE Datadog, Inc.

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Jtibot Showcases Autonomous Outdoor Sweeping Innovation at Interclean Amsterdam 2026, Accelerating European Market Expansion

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AMSTERDAM, April 24, 2026 /PRNewswire/ — Jtibot, a developer of autonomous outdoor cleaning solutions, concluded a successful showcase at Interclean Amsterdam 2026, highlighting its focus on large-scale, AI-driven sweeping for industrial, municipal, and campus environments.

At Hall 8, Booth 538, Jtibot presented its autonomous outdoor sweeper designed for environments exceeding 10,000 sqm. Positioned between traditional equipment and emerging robotics, the system addresses the growing demand for more efficient and less labor-dependent outdoor cleaning operations.

During the exhibition, Jtibot attracted strong interest from European distributors and facility management professionals seeking scalable solutions for large-area maintenance. The company was also featured in an official media interview at the event, reflecting increasing attention toward autonomous technologies in the cleaning industry.

Jtibot’s approach centers on human-machine collaboration. By reducing repetitive manual work while maintaining operational flexibility, its systems support more sustainable and efficient facility management practices. This aligns with broader ESG (Environmental, Social, and Governance) priorities, including improved resource efficiency and enhanced working conditions.

Building on its presence at Interclean, Jtibot is currently advancing discussions with multiple European partners for regional distribution and deployment. The company is also in the final stage of a fleet procurement agreement valued at approximately $1.4 million, signaling early commercial traction in large-scale applications scenarios.

“As outdoor environments continue to grow in scale and complexity, automation is becoming essential,” said Steven, VP at Jtibot. “Our goal is not to replace people, but to empower them—making operations more efficient and labor more sustainable.”

Following Interclean Amsterdam 2026, Jtibot is actively expanding its European partner network and preparing for broader market deployment across key regions, as it accelerates its global commercialization strategy.

About Jtibot
Jtibot specializes in autonomous outdoor sweepers designed for large-scale environments. By combining AI-driven navigation with industrial-grade hardware, the company enables efficient, scalable, and sustainable cleaning operations worldwide.

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2U Refinances and Raises Growth Capital

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ARLINGTON, Va., April 24, 2026 /PRNewswire/ — Many education technology companies spent 2024 and 2025 scaling back. New university partnerships slowed as institutions built internal capacity. Against that backdrop, 2U completed a growth recapitalization, with its existing owners putting growth capital into the business alongside a refinancing of its current credit facilities.

The question worth asking is: why now, and what did they see?

2U operates edX, a global online learning platform originally co-founded by Harvard and MIT that now reaches more than 100 million people through over 5,300 programs with 250-plus institutional and enterprise partners. Employees from more than 60% of Fortune 500 companies use edX for professional development. To date, over 76,000 people have graduated from 2U-powered degree programs from leading institutions, including UC Berkeley, Howard University, and Georgetown. The company has been privately held since completing a financial reorganization in 2024, and Kees Bol has served as CEO since January 2025.

Lincoln International, which advised 2U on the transaction exclusively, described the refinancing outcome: extended credit maturities, improved capital structure, and financial flexibility to continue executing on 2U’s long-range plan. Managing Director Alex Stevenson said the deal “reflects the confidence of 2U’s owners in the long-term value of the business.”

Confidence in what, exactly? The AI workforce training market. Skills in AI-affected roles are evolving 66% faster than average according to PwC research, and IDC has estimated that unfilled AI skills gaps could cost the global economy $5.5 trillion. Universities and enterprises are both trying to solve that problem, and both are looking for platforms with the breadth and accreditation backing to do it credibly.

2U’s partnerships are designed for exactly that. IBM’s six technical microcredentials on edX train the engineers and data scientists who build AI systems. Microsoft’s CxO Edge program, launched in late 2025, targets the C-suite executives who need to move from AI pilots to enterprise-wide adoption, part of a Microsoft presence on edX that has drawn over 40,000 learners in the past six months alone.. Oxford’s Faculty of Law program addresses governance: what board members and legal advisors need to understand about AI liability, compliance, and fiduciary responsibility. UC Berkeley’s Master of Information and Data Science (MIDS) online program prepares learners to shape the future of AI and data science with human-centered values and focuses on solving the world’s most pressing data challenges. Each program exists because a specific employer community identified a specific gap.

That’s the differentiation investors are backing. Generic online courses are abundant. Programs designed in partnership with IBM, Microsoft, UC Berkeley, and Oxford’s Faculty of Law and delivered on a platform with proven Fortune 500 adoption are not.

Credentials earned on 2U’s edX platform carry the academic standing of the issuing partner institutions. Its programs span executive education, professional certificates, microcredentials, and accredited online degree programs, all powered by 2U’s infrastructure but conferred by partner universities and institutions with their own accreditation.

HolonIQ data puts the broader trend in context: microcredentials grew from 7% of global online program offerings in 2022 to 19% by 2025. The shift toward stackable, job-aligned credentials, in addition to traditional degrees,  is real and accelerating. The global online education market is projected to exceed $200 billion as that trend matures. 2U’s decision to build depth in short-form, employer-designed AI training aligns directly with where learner demand is heading.

None of this is abstract for the organizations that use edX at scale. When a company needs to certify 500 engineers on AI development, or prepare its entire C-suite for a board presentation on AI governance, the platform’s reach and credential quality both matter. A certification backed by IBM and a degree from institutions such as Berkeley carries weight with hiring managers in a way a generic online course does not.

The refinancing extends 2U’s ability to keep building that catalog and the partnerships behind it. Stevenson framed it as giving the management team “the financial foundation to keep executing on its mission.” The mission, under Bol’s leadership, is straightforward: help universities and enterprises close the AI skills gap by meeting learners where they are, at the pace the market demands.

The investors who contributed growth capital made a bet that a platform that reaches 100 million people and has 250-plus partners, including IBM, Microsoft, UC Berkeley, and Oxford in its program portfolio, is better positioned to close that gap than any platform that would need to build from scratch.

Media Contact:
Kees Bol
social@2u.com 

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Autonomous Resource Corporation and Oak Ridge National Laboratory Partner to Accelerate AI-Enabled Defense Manufacturing at National Scale

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Strategic partnership combines ORNL’s supercomputing and advanced manufacturing expertise with ARC’s autonomous production platform to address critical defense industrial base shortfalls

OAK RIDGE, Tenn. and NEW YORK, April 24, 2026 /PRNewswire/ — Autonomous Resource Corporation (ARC), a Delaware corporation, and Oak Ridge National Laboratory (ORNL), the U.S. Department of Energy’s largest multi-program science and energy laboratory, today announced a Memorandum of Understanding (MOU) establishing a strategic public-private partnership to accelerate the on-demand manufacture of qualified, mission-critical components for U.S. national security applications.

The partnership combines ORNL’s HPC and manufacturing capability with ARC’s ARCNet distributed AI-manufacturing platform

The partnership — known as the Exascale Foundry — will combine ORNL’s computing and manufacturing capabilities with ARC’s ARCNet distributed manufacturing platform to create a closed-loop system for AI-enabled materials and manufacturing qualification and autonomous production at defense-relevant scale.

“The United States faces an urgent need to rebuild its manufacturing capacity for critical defense components,” said Bryan Wisk, CEO of ARC. “By combining ORNL’s world-leading computational, materials science, and manufacturing capabilities with our autonomous production infrastructure, we can compress manufacturing and qualification timelines from years to months and deliver manufactured parts at the volumes the warfighter needs.”

Partnership Highlights

Under the MOU, ARC will deploy advanced manufacturing equipment organized into seven production nodes connected to ORNL via ARC’s secure ARCNet infrastructure. ARC will expand capability through ORNL’s high-performance computing (HPC) resources.

ORNL will provide access to HPC expertise for simulation-driven materials characterization and qualification, along with technologies developed at the Manufacturing Demonstration Facility (MDF), the Department of Energy’s only large-scale, open-access advanced manufacturing facility. ORNL’s Peregrine AI software, which has analyzed over 1.9 million additive manufacturing layers, will be integrated into ARC’s production nodes for real-time adaptive control and quality assurance.

This partnership also supports DOE’s Genesis Mission, a national initiative to build the world’s most powerful scientific platform to accelerate discovery science, strengthen national security and drive energy innovation. ARC and ORNL’s collective capabilities will help reenvision advanced manufacturing and industrial productivity, accelerate defense production and qualification, and secure critical supply chain elements.

“ORNL’s advanced manufacturing and computing capabilities are uniquely positioned to help accelerate the transition of laboratory-proven technologies into production-scale defense manufacturing,” said Moe Khaleel, ORNL associate laboratory director for National Security Sciences. “Partnering with ARC ensures we are transitioning our research into real production outcomes.”

The initial implementation will focus on high-temperature nickel superalloy turbine components for autonomous air vehicle engines using metal binder jetting technology, directly addressing demonstrated production bottlenecks in the U.S. defense supply chain.

ORNL Chief Manufacturing Officer Craig Blue added, “This partnership exemplifies the type of relationship necessary to build and grow domestic supply chains for our national security.”

About Autonomous Resource Corporation

ARC is a New York–headquartered corporation building and operating an AI-enabled, autonomous manufacturing platform for national security and critical infrastructure applications. ARC’s Autonomous Resource Controller Network (ARCNet) connects distributed production cells into a secure, federated manufacturing grid capable of producing qualified components at scale. ARC’s leadership team brings deep experience across defense technology, capital markets, materials science, and additive manufacturing at production scale.

About Oak Ridge National Laboratory

Oak Ridge National Laboratory is the largest U.S. Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. DOE’s Manufacturing Demonstration Facility at ORNL partners with more than 300 companies, spurring over $5.5 billion in economic growth. ORNL is managed by UT-Battelle, LLC for the U.S. Department of Energy’s Office of Science.

Media Contacts:

ARC: Bryan Wisk, Chief Executive Officer | bryan@autonomousresource.com | 929-523-3953

ORNL: Eric Swanson, National Security Sciences Communications Lead | swansonej@ornl.gov | 865-206-5794

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SOURCE Autonomous Resource Corporation

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