Latest news with #BitsAI
Time of India
11-06-2025
- Business
- Time of India
US based Datadog unveils new AI security tools to tackle emerging risks at DASH 2025
New York: Datadog, the New York-based cloud monitoring and security company, announced a series of new tools on June 10 to help businesses identify and resolve security threats in their artificial intelligence (AI) systems. The unveiling took place on the opening day of DASH Conference 2025 , Datadog's annual two-day flagship event. With AI becoming central to how software is developed and operated, Datadog is seeking to play a leading role in ensuring that businesses can safely adopt the technology. The company introduced several products aimed at improving observability, developer productivity, and security across enterprise AI environments. One of the highlights of the launch was Bits AI , a suite of intelligent agents designed to automate key tasks across site reliability engineering (SRE), security operations, and software development. The agents are capable of troubleshooting incidents, managing alerts, and recommending fixes, reducing the burden on human teams. Also introduced were new capabilities such as GPU monitoring, AI agent monitoring, and the APM Investigator, each aimed at helping enterprises optimise performance, control costs, and detect latency bottlenecks. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Memperdagangkan CFD Emas dengan salah satu spread terendah? IC Markets Mendaftar Undo 'We can all agree that change is happening much faster today with AI than ever before,' said Olivier Pommel, co-founder and CEO of Datadog. 'Our job at Datadog is to make sure that you can tame that complexity, that you can get those risks out of the way, so that you can happily and productively ride those technology waves all the way to success.' Pommel highlighted that Datadog is making substantial investments in research and development to keep up with the rapid advancements in AI. One such result is a new AI model named TOTO , created by Datadog's AI Lab for time series analysis. The company is releasing it as open-weight on the Hugging Face platform to foster transparency and innovation. Alexey, co-founder of Datadog, said the new solutions were designed to enhance the day-to-day experience of developers and engineers. 'We ask ourselves, how can we apply these new techniques to make a difference in your daily work?' he said. In addition, Datadog announced a voice interface for its oncall platform to streamline incident response for support teams. The company also spotlighted its expanding partnerships with AI pioneers such as OpenAI and Cursor, with plans to embed more third-party agents into enterprise workflows. A key concern addressed at the conference was the security challenges unique to AI-native applications. As AI systems increasingly act autonomously—writing code, making decisions, and interacting with other software—they introduce new vulnerabilities that traditional security tools struggle to detect. 'AI has exponentially increased the ever-expanding backlog of security risks and vulnerabilities organisations deal with,' said Prashant Prahlad, Vice President of Security Products at Datadog. 'This is because AI-native apps are not deterministic; they're more of a black box and have an increased surface area that leaves them open to vulnerabilities like prompt or code injection.' To mitigate these risks, Datadog unveiled tools across three core areas: development, application usage, and real-time operations. These include a code security feature that scans external code for hidden threats and suggests fixes using AI, and a LLM Observability tool that tracks unusual behavior in large language models. The Cloud Security module now ensures compliance with standards like those from the U.S. National Institute of Standards and Technology (NIST), while a sensitive data scanner prevents personal data from being accidentally included in AI training datasets. To protect live systems, Datadog also launched the Bits AI security analyst , which helps teams swiftly investigate alerts and anomalies, providing actionable insights to reduce both risk and downtime. (This correspondent was in NY to attend the DASH conference on invitation.) AI Masterclass for Students. Upskill Young Ones Today!– Join Now
Techday NZ
11-06-2025
- Business
- Techday NZ
Datadog launches domain-specific AI agents & LLM tools
Datadog has announced the addition of three domain-specific AI agents to its generative AI assistant, Bits AI, together with new tools for monitoring and managing large language model (LLM) and agentic AI deployments. New AI agents The company has introduced Bits AI SRE, Bits AI Dev Agent, and Bits AI Security Analyst, each configured to serve specific engineering, operations, and security functions. These agents are designed to support real-time incident response, DevOps tasks, and security workflows for development, security, and operations teams. The AI agents operate on a shared system of core tasks, including data querying, anomaly analysis, and infrastructure scaling. This architecture allows Datadog to roll out new agents efficiently while maintaining consistency in the user experience. The system integrates a broad set of observability data, enabling precise insights and actions for managing risks within cloud-based applications. Yanbing Li, Chief Product Officer at Datadog, commented on the company's approach: Datadog is uniquely positioned to deliver value with AI as a platform that has a wealth of clean, rich data—we process trillions of data points and are embedded in our customers' critical engineering, developer and security workflows. With these advancements in AI reasoning and multi-modality, we've gone beyond helping organizations understand their availability, security, performance and reliability. We now enable human-in-the-middle workflows by guiding customers on what to look for and where to start looking, and augment their ability to take action. Bits AI SRE, which is now in limited availability, acts as an on-call responder for incidents by performing early triage and providing investigation findings before human responders intervene. It allocates incidents, produces real-time summaries, and generates initial post-mortem drafts to save teams time. Bits AI Dev Agent, currently in preview, identifies code issues, suggests fixes, and can open pull requests directly within the source control management systems organisations use. Bits AI Security Analyst, also in preview, automatically investigates cloud security signals, conducts in-depth threat investigations, and produces actionable resolution recommendations, aiming to reduce response times for security incidents. Darren Trzynka, Senior Cloud Architect at Thomson Reuters, commented on Bits AI's impact: At Thomson Reuters, we're focused on maximizing operational efficiency and accelerating innovation at scale through generative AI solutions. Bits AI allows operations and downstream platform teams to receive the full context of the investigation—from the initial monitor trigger to conclusion—driving down resolution time significantly freeing them up to do more. Additional Applied AI features The updates include two new features in preview. Proactive App Recommendations analyses telemetry collected by Datadog to suggest performance improvements or actions, such as optimising slow queries and addressing code issues, before users are impacted. The APM Investigator helps engineers troubleshoot latency spikes by automating bottleneck identification and recommending fixes. LLM Observability suite announced Datadog has also released a suite of tools designed to provide observability for agentic AI—software agents built with LLMs and similar technologies—in production environments. The new products include AI Agent Monitoring, LLM Experiments, and AI Agents Console. Yrieix Garnier, Vice President of Product at Datadog, addressed the motivations behind these offerings: A recent study found only 25 percent of AI initiatives are currently delivering on their promised ROI—a troubling stat given the sheer volume of AI projects companies are pursuing globally. Today's launches aim to help improve that number by providing accountability for companies pushing huge budgets toward AI projects. The addition of AI Agent Monitoring, LLM Experiments and AI Agents Console to our LLM Observability suite gives our customers the tools to understand, optimize and scale their AI investments. AI Agent Monitoring, now generally available, provides a mapped overview of each agent's decision-making route, including inputs, tool calls, and outputs, displayed in an interactive graph. This enables engineers to diagnose latency spikes or unexpected behaviours and connect them to quality, security, and cost measures across distributed systems. Mistral AI's Co-founder and CTO, Timothée Lacroix, provided further industry perspective: Agents represent the evolution beyond chat assistants, unlocking the potential of generative AI. As we equip these agents with more tools, comprehensive observability is essential to confidently transition use cases into production. Our partnership with Datadog ensures teams have the visibility and insights needed to deploy agentic solutions at scale. LLM Experiments, in preview, enables users to compare the effects of changes to prompts or models using datasets from live or uploaded sources. This aims to support quantifiable improvements in cost, response accuracy, and throughput, and prevent unintended regressions in AI application performance. Michael Gerstenhaber, Vice President of Product at Anthropic, commented: AI agents are quickly graduating from concept to production. Applications powered by Claude 4 are already helping teams handle real-world tasks in many domains, from customer support to software development and R&D. As these agents take on more responsibility, observability becomes key to ensuring they behave safely, deliver value, and stay aligned with user and business goals. We're very excited about Datadog's new LLM Observability capabilities that provide the visibility needed to scale these systems with confidence. Datadog has also introduced AI Agents Console, currently in preview, to allow organisations to centrally oversee both in-house and third-party AI agents, track their usage and impact, and monitor for potential security or compliance issues as external agents are embedded into critical business workflows. Armita Peymandoust, Senior Vice President, Software Engineering at Salesforce, said: As enterprises scale digital labour, having clear visibility into how AI agents drive business impact has become mission critical. Customers are already seeing strong success with their AI deployments using Salesforce's Agentforce, which is built on a foundation of openness and trust. That foundation is further strengthened by our partner ecosystem that provides our customers even greater availability to tailored solutions that help them manage their AI agents confidently. Datadog's latest advances in deep observability will further support our vision and unlock another level of AI agent transparency and scale for organizations.
Yahoo
10-06-2025
- Business
- Yahoo
Datadog Unveils Latest AI Agents to Rapidly Resolve Application Issues
Bits AI now delivers domain-specific AI agents and Applied AI capabilities that accelerate incident resolution for development, security and operations teams New York, New York--(Newsfile Corp. - June 10, 2025) - Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams. Today's launch of the Bits AI SRE, Bits AI Dev Agent and Bits AI Security Analyst agents, alongside the new Proactive App Recommendations and APM Investigator capabilities, marks the continued evolution of Bits AI, Datadog's generative AI assistant that helps engineers resolve application issues in real time. Datadog's new domain-specific AI agents, unveiled at DASH, are each trained to be experts in incident response, product development and security. The agents are built on a flexible system of shared tasks-core capabilities such as querying data, analyzing anomalies or scaling infrastructure that can be reused across agents. The architecture allows Datadog to build and deploy new agents quickly while maintaining a consistent and powerful user experience. This is combined with expansive, high-quality observability data, enabling Datadog's AI capabilities to operate with context and precision, and deliver insights and actions to eliminate risk. "Datadog is uniquely positioned to deliver value with AI as a platform that has a wealth of clean, rich data-we process trillions of data points and are embedded in our customers' critical engineering, developer and security workflows," said Yanbing Li, Chief Product Officer at Datadog. "With these advancements in AI reasoning and multi-modality, we've gone beyond helping organizations understand their availability, security, performance and reliability. We now enable human-in-the-middle workflows by guiding customers on what to look for and where to start looking, and augment their ability to take action." The new AI agents announced at DASH are: Bits AI SRE, a 24x7 on-call responder that is now in Limited Availability. For all alerts, Bits AI SRE performs early triage using telemetry and service context to surface initial investigation findings all before responders log in. It assigns appropriate owners, aligns all parties with real-time incident summaries and status updates, and proactively suggests next steps. It also generates a first draft of the incident post-mortem to save responders time. Bits AI Dev Agent, now in Preview, which detects issues, generates code fixes, and opens pull requests tailored to organizations' technology stack to allow users to quickly review and merge changes directly within their SCM. As a result, engineers don't just have software that surfaces errors-they have an AI teammate that helps fix the issue and improve productivity for human resources. Bits AI Security Analyst, which autonomously triages Cloud SIEM (security information and event management) signals, conducts in-depth investigations of potential threats and delivers reasoned resolution recommendations without human prompting. Bits AI Security Analyst, now in Preview, automates investigations and reduces response times, fundamentally transforming how organizations process security signals. "At Thomson Reuters, we're focused on maximizing operational efficiency and accelerating innovation at scale through generative AI solutions," said Darren Trzynka, Senior Cloud Architect at Thomson Reuters. "Bits AI allows operations and downstream platform teams to receive the full context of the investigation-from the initial monitor trigger to conclusion-driving down resolution time significantly freeing them up to do more." Additional Applied AI capabilities in preview include: Proactive App Recommendations, which continuously analyzes telemetry Datadog already collects to suggest high-impact fixes and the next best action. Whether it's optimizing a slow query, addressing inefficient code paths or catching recurring exceptions, APM Recommendations shows developers exactly where to improve performance, reduce errors and cut down resource usage-all before users are affected. APM Investigator, to help engineers troubleshoot and resolve latency spikes faster. It automates a previously manual process by identifying bottlenecks, scoping impact, highlighting patterns across slow traces, suggesting likely causes and proposing a fix. To learn more about Datadog's latest Applied AI capabilities, please visit: Bits AI SRE, Bits AI Dev Agent, Bits AI Security Analyst, Proactive App Recommendations and APM Investigator were announced during the DASH keynote. The replay is available here. During DASH, Datadog also announced launches in AI Observability, AI Security, Log Management and released its Internal Developer Portal. 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 may include certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended including statements on the benefits of new products and features. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control, including those risks detailed under the caption "Risk Factors" and elsewhere in our Securities and Exchange Commission filings and reports, including the Annual Report on Form 10-K filed with the Securities and Exchange Commission on May 6, 2025, as well as future filings and reports by us. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise. ContactDan Haggertypress@ To view the source version of this press release, please visit Sign in to access your portfolio
Yahoo
12-05-2025
- Business
- Yahoo
3 Reasons Datadog Stock Is Still a Top Artificial Intelligence Buy Right Now
Datadog reported first-quarter earnings that exceeded Wall Street expectations. The company's new artificial intelligence-powered cloud monitoring and observability features are generating strong growth. Datadog's significant opportunity within the rapidly expanding cloud services market supports a bullish outlook for the stock. 10 stocks we like better than Datadog › For Datadog (NASDAQ: DDOG) shareholders, the past few years must have felt like treading water. The volatile stock shed approximately 38% from its 52-week high at the time of writing and is nowat levels first reached back in 2020. This frustrating performance stands in contrast to the impressive growth momentum from the cloud-computing leader in observability and monitoring. The company is capitalizing on strong demand for solutions that address the increasingly complex data demands generated by artificial intelligence (AI) applications. Several trends support a positive long-term outlook. Here are three reasons Datadog stock is still a top AI stock to buy right now. The Datadog platform acts as a central data hub for organizations, providing real-time visibility across their entire technology stack, including key cloud performance metrics, analytics, security, and system bottlenecks. Its unified approach uses integrates data from more than 900 software applications to identify problems and increase efficiency. New data-intensive AI workflows add to the need for comprehensive observability, representing a major growth driver. Datadog isn't just benefiting from the rise of AI -- it actively integrates AI tools into its platform, including through its Bits AI generative AI assistant. Solutions enhancing automation and intelligent analysis further bolster the company's value proposition for its customers. According to estimates from the industry research group Gartner, the public cloud services market is currently valued at $600 billion and is projected to nearly double in the coming years, with a 20% compound annual growth rate (CAGR) through 2028. Moreover, companies are allocating an increasing percentage of their total IT spending to the cloud. This significant tailwind underscores the substantial opportunity for Datadog and its attractiveness as an investment. In the recently reported first quarter, revenue grew by 25% year over year to $762 million, surpassing Wall Street's expectation of $741.5 million. Similarly, adjusted earnings per share (EPS) of $0.46 came in above the $0.43 market estimate. Datadog has approximately 30,500 customers, including 3,770 that each generate more than $100,000 in annual recurring revenue (ARR) in software-as-a-service subscriptions. Perhaps the most encouraging metric is the 110% dollar-based net retention rate over the past year, as the company's customer base increases spending on the platform by adopting additional products. Strong demand for AI solutions is a key part of the growth story. The number of customers using its large language model (LLM) Observability product more than doubled in just the past six months. Datadog continues to strengthen its platform through strategic bolt-on acquisitions, including Metaplane, an AI-powered data observability specialist acquired in April, and Eppo, an AI experimentation platform purchased just this month. These deals enhance Datadog's reach in data monitoring and real-time AI analytics, boosting its competitive edge. For the full year 2025, Datadog targets revenue between $3.215 billion and $3.235 billion, reflecting a robust 20% to 21% growth rate from the prior year. While ongoing investments in research and development, particularly in AI capabilities, create some operating margin pressure, EPS estimates of $1.67 to $1.71 for the year demonstrate strong underlying profitability. Even more encouraging is the free-cash-flow trend, which reached $833 million over the past year, surging 39% from year-end 2023. This dynamic supports the stock's premium valuation. Datadog shares trade at a forward price-to-earnings (P/E) ratio of 64 -- high compared to the broader stock market, but still attractive relative to other high-growth software infrastructure peers. Compared to stocks like CrowdStrike, Cloudflare, Zscaler, CyberArk Software, and SentinelOne, which collectively average a forward P/E above 100, Datadog stands out with its unique blend of observability and cybersecurity capabilities, offering broader organizational use cases than pure-play cybersecurity companies. Investors who believe Datadog is just beginning to realize its potential have compelling reasons to buy and hold the stock for the long run. Datadog's AI-fueled growth captures high-level themes, technology, and cloud computing to complement diversified portfolios. I'm bullish and expect shares to be trading at a higher price by this time next year. Before you buy stock in Datadog, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Datadog wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $614,911!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $714,958!* Now, it's worth noting Stock Advisor's total average return is 907% — a market-crushing outperformance compared to 163% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of May 5, 2025 Dan Victor has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Cloudflare, CrowdStrike, Datadog, and Zscaler. The Motley Fool recommends Gartner. The Motley Fool has a disclosure policy. 3 Reasons Datadog Stock Is Still a Top Artificial Intelligence Buy Right Now was originally published by The Motley Fool Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Globe and Mail
11-05-2025
- Business
- Globe and Mail
3 Reasons Datadog Stock Is Still a Top Artificial Intelligence Buy Right Now
For Datadog (NASDAQ: DDOG) shareholders, the past few years must have felt like treading water. The volatile stock shed approximately 38% from its 52-week high at the time of writing and is nowat levels first reached back in 2020. This frustrating performance stands in contrast to the impressive growth momentum from the cloud-computing leader in observability and monitoring. The company is capitalizing on strong demand for solutions that address the increasingly complex data demands generated by artificial intelligence (AI) applications. Several trends support a positive long-term outlook. Here are three reasons Datadog stock is still a top AI stock to buy right now. 1. AI-powered growth opportunity The Datadog platform acts as a central data hub for organizations, providing real-time visibility across their entire technology stack, including key cloud performance metrics, analytics, security, and system bottlenecks. Its unified approach uses integrates data from more than 900 software applications to identify problems and increase efficiency. New data-intensive AI workflows add to the need for comprehensive observability, representing a major growth driver. Datadog isn't just benefiting from the rise of AI -- it actively integrates AI tools into its platform, including through its Bits AI generative AI assistant. Solutions enhancing automation and intelligent analysis further bolster the company's value proposition for its customers. According to estimates from the industry research group Gartner, the public cloud services market is currently valued at $600 billion and is projected to nearly double in the coming years, with a 20% compound annual growth rate (CAGR) through 2028. Moreover, companies are allocating an increasing percentage of their total IT spending to the cloud. This significant tailwind underscores the substantial opportunity for Datadog and its attractiveness as an investment. 2. Robust operating tailwinds In the recently reported first quarter, revenue grew by 25% year over year to $762 million, surpassing Wall Street's expectation of $741.5 million. Similarly, adjusted earnings per share (EPS) of $0.46 came in above the $0.43 market estimate. Datadog has approximately 30,500 customers, including 3,770 that each generate more than $100,000 in annual recurring revenue (ARR) in software-as-a-service subscriptions. Perhaps the most encouraging metric is the 110% dollar-based net retention rate over the past year, as the company's customer base increases spending on the platform by adopting additional products. Strong demand for AI solutions is a key part of the growth story. The number of customers using its large language model (LLM) Observability product more than doubled in just the past six months. Datadog continues to strengthen its platform through strategic bolt-on acquisitions, including Metaplane, an AI-powered data observability specialist acquired in April, and Eppo, an AI experimentation platform purchased just this month. These deals enhance Datadog's reach in data monitoring and real-time AI analytics, boosting its competitive edge. 3. Free-cash-flow momentum For the full year 2025, Datadog targets revenue between $3.215 billion and $3.235 billion, reflecting a robust 20% to 21% growth rate from the prior year. While ongoing investments in research and development, particularly in AI capabilities, create some operating margin pressure, EPS estimates of $1.67 to $1.71 for the year demonstrate strong underlying profitability. Even more encouraging is the free-cash-flow trend, which reached $833 million over the past year, surging 39% from year-end 2023. This dynamic supports the stock's premium valuation. Datadog shares trade at a forward price-to-earnings (P/E) ratio of 64 -- high compared to the broader stock market, but still attractive relative to other high-growth software infrastructure peers. Compared to stocks like CrowdStrike, Cloudflare, Zscaler, CyberArk Software, and SentinelOne, which collectively average a forward P/E above 100, Datadog stands out with its unique blend of observability and cybersecurity capabilities, offering broader organizational use cases than pure-play cybersecurity companies. Investors who believe Datadog is just beginning to realize its potential have compelling reasons to buy and hold the stock for the long run. DDOG PE Ratio (Forward) data by YCharts Final thoughts Datadog's AI-fueled growth captures high-level themes, technology, and cloud computing to complement diversified portfolios. I'm bullish and expect shares to be trading at a higher price by this time next year. Should you invest $1,000 in Datadog right now? Before you buy stock in Datadog, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Datadog wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $614,911!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $714,958!* Now, it's worth noting Stock Advisor 's total average return is907% — a market-crushing outperformance compared to163%for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of May 5, 2025
