Andrew Dzurak, founder and CEO of Australian startup Diraq, holds one of the company’s projects. Image credit: Diraq DARPA has awarded two Australian startups, Diraq and Silicon Quantum Computing (SQC), contracts for quantum computing research, the U.S. agency announced on April 4. Both Sydney-based companies will participate in the Quantum Benchmarking Initiative (QBI) program, designed to assess other companies to find which might have the potential to reach useful quantum computing within the next decade. “For the chosen companies, now the real work begins,” said Joe Altepeter, DARPA QBI program manager, in a press release. “Stage A is a six-month sprint in which they’ll provide comprehensive technical details of their concepts to show that they hold water and could plausibly lead to a transformative, fault-tolerant quantum computer in under 10 years.” Useful quantum computing (or utility-scale operation) is defined as a method in which computational value exceeds the build and operational costs. Diraq teams up with other companies to manufacture quantum chips Diraq entered into the QBI its silicon spin qubits approach to quantum computing, which is based on the CMOS manufacturing methods used to make computer chips. Diraq will place its method under more intense scrutiny as part of the program, testing its robustness. “We are confident that our combined expertise, designs, and technologies can rapidly deliver a commercially viable quantum system concept in terms of capex per system, plus realistic considerations around equipment footprint, scalability, sustainability and operating costs,” wrote Diraq founder and CEO Andrew Dzurak in a press release. To do so, Diraq has teamed up with other organizations: Emergence Quantum, which provides system architecture design, classical cryo-CMOS electronics, and qubit readout and control. Riverlane, which makes quantum error correction (QEC) technology. Semiconductor manufacturers Global Foundries and IMEC. SQC brings intrinsically quantum qubits in silicon Under the DARPA contract, SQC will work on intrinsically quantum qubits embedded in silicon chips. SQC performs its own manufacturing and said the company can iterate on new designs within one to two weeks. “Not only is the associated funding incredibly useful, DARPA’s third-party interrogation of our path to a utility-scale quantum computer will be immensely valuable,” wrote SQC Founder and CEO Michelle Simmons in a press release. SEE: Amazon showed a prototype of a quantum chip, Ocelot, that reduces errors with specially designed qubits. More Australia coverage Quantum program looks ahead 10 years to possible commercialization The QBI program will have three stages. Stage A is the assessment step and involves 16 companies from the U.S., U.K., Canada, and France, including IBM and Hewlett Packard Enterprise, as well as the two Australian businesses. Stage B will be a year-long program, during which DARPA will assess each company’s research and development approach. Stage C: An independent firm will assess each company’s hardware. As InnovationAus pointed out, DARPA chose Australian company PsiQuantum for the Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program, the group of companies the QBI program will assess. The program is not a competition between companies, DARPA pointed out. Instead; it is a survey of all companies deemed likely to produce a useful quantum computer. Quantum computing is highly sought after as a commercial product, with its remarkable processing speed that could prove critical for drug discovery, materials science simulation, and other calculations. However, it has proven challenging to monetize and scale due to difficulties in scaling up the number of qubits able to be used in a computer; cost, especially of cooling the hardware to nearly absolute zero; and high error rates or noise. source

Siemens has agreed to acquire Dotmatics, the developer of a data platform for scientific research, taking it into the life sciences market. Siemens plans to combine Dotmatics’ drug research and development applications with its manufacturing industry expertise to create an AI-powered research-to-manufacturing digital thread for the life sciences vertical, the company said in a slide deck aimed at investors. Rohit K, practice director at Everest Group, said the companies’ combined offering will provide their joint customers with predictive modeling, faster iteration cycles, and stronger regulatory compliance—ultimately accelerating time-to-market. source

By Elliot Weld ( April 9, 2025, 2:44 PM EDT) — A federal jury in San Diego has found a former executive at Qualcomm guilty of defrauding the chipmaker by creating a fake company, concealing his connection to it and selling it to Qualcomm for $180 million…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

IT executives are under ever-increasing levels of strain. Chief information officers, chief information security officers, and chief technology officers are responsible for managing growing threat levels while juggling skill gaps and talent shortages. Even as awareness of the very real threats cyberattacks pose grows, the average C-suite remains indifferent until a crisis occurs.   Studies indicate that people in leadership positions are expected to be more resistant — perhaps even immune — to the stressors that result in mental health problems. But IT execs appear to be particularly vulnerable given the novel and tenuous nature of their roles.   The narrative emerging from both academic research and media reports suggests that they are being crushed by unrealistic job expectations.   According to one report, 78% of CISOs were seeking a new role due to the stresses of their job. Depression, anxiety, substance abuse and even suicidality are rampant at both the executive level and among their subordinates.   Industry leaders and external observers are now looking at how to address these issues — through both systemic change and individual effort. Here, InformationWeek investigates the state of mental health among IT execs and their teams. Andrew Shatté, chief knowledge officer and co-founder of meQuilibrium; and Lincoln Stoller, a software company founder and psychotherapist, offer their insights on the nature of the problem and how to address it.  Related:How Today’s CIOs are Upskilling The State of IT Exec Mental health  IT execs have begun to raise the alarm — they are not OK. A toxic conflagration of factors has resulted in a typical work environment that frequently results in severe mental strain.  An onslaught of cyberattacks, severe staffing, and skills shortages combined with indifferent C-suites have created a set of stressors that are nearly impossible to cope with.   A 2024 report on CISO burnout released by Vendict found that 80% of CISOs were highly stressed and 61% felt overwhelmed by the expectations placed on them. The problem has been brewing for some time — even a 2020 report by Nominet found that 91% of CISOs were suffering from moderate to severe job stress.   These problems run downhill — 50% of respondents in the Vendict report said that team members had left due to stress. A 2024 Hack the Box report found that 90% of CISOs were concerned about stress affecting their teams. Per a report by Yerbo, 42% of IT professionals are burning out and considering quitting their jobs.   Causes of Mental Health Decline  Related:Why IT Leaders Must Prioritize Leading Over Contributing to Projects An enormous suite of issues have contributed to the mental health crisis among IT execs.   Working conditions are of course a major factor. Their leadership positions are often lonely. They are part of the C-suite but often have little in common with their executive peers — who are more likely than not to dismiss their concerns. And they are responsible for hugely consequential aspects of the business, keeping it secure from threats and managing highly technical projects with little support.   “We may understand that they’re more important than we thought they were,” Shatté says. “But the distance between them and the rest of the organization creates a greater mental health risk.”  Their personalities also play into the equation. CIOs, CISOs, and CTOs are highly independent people — and some lack interpersonal skills. And they may view their ability to meet punishing deadlines and crushing workloads as a badge of honor.  “I see the CIO — and the whole tech department — as needing to become more personally capable in dealing with people, because they’re not really able to be isolated behind a computer anymore,” Stoller says. “Too many people are involved. If you go to school to be a computer engineer, they don’t teach you about mental health, they don’t teach you about management.”  Related:How to Handle a Runaway IT Development Team “They’re probably less ‘people’ people than most others in the organization. They’re more perfectionistic. They have to be very precise in what they do,” Shatté adds. “That can put them at greater risk of burnout, because they’re really giving more resources than they have.”  Vendict’s report suggests that funding and staffing difficulties play a huge role in driving mental health decline — both for these execs and their subordinates. The challenges of maintaining functional technological ecosystems are complicated by resource shortages, leading to long hours and an increased likelihood of errors.  Easy solutions are in short supply, but a number of steps can be taken to address this crisis.  Increased Funding and Staffing  While it is likely the most challenging ask for current CIOs, CISOs and CTOs, increasing their funding and staff resources would likely go the furthest in mitigating the factors afflicting their mental health. According to Vendict’s report, 45% of respondents said that increasing their resources would alleviate some of their stress.   Funding for parsimonious solutions, such as AI programs that might be able to automate tasks that must be done manually by analysts, might serve as a compromise. If AI programs are able to eliminate the need to analyze every report manually, cyber teams are then able to turn their attention to the most pressing issues.   Investment in both technological and human resources has a cascading effect. Alleviating strain on staff by improving the tools they have to execute their tasks and compensating them at fair rates reduces turnover rate. Encouraging them to stay through regular training opportunities can further facilitate a cooperative and enthusiastic workforce.  Their bosses can then concentrate on big-picture issues.   Open Discussion  IT execs can start the conversation themselves — encouraging the discussion of mental health issues among their peers and subordinates. By sharing their own struggles, they can create an atmosphere where others can do the same.  A CIO at a Minnesota insurance company shared a video describing his mental health challenges and found that his colleagues began sharing theirs as well.   These discussions need not be limited to mental health — dialogue about working conditions, conflicts and management of projects

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As we step fully into the era of autonomous transformation, AI agents are transforming how businesses operate and create value. But with hundreds of vendors claiming to offer “AI agents,” how do we cut through the hype and understand what these systems can truly accomplish and, more importantly, how we should use them? The answer is more complicated than creating a list of tasks that could be automated and testing whether an AI agent can achieve those tasks against benchmarks. A jet can move faster than a car, but it’s the wrong choice for a trip to the grocery store. Why we shouldn’t be trying to replace our work with AI agents Every organization creates a certain amount of value for their customers, partners and employees. This amount is a fraction of the total addressable value creation (that is, the total amount of value the organization is capable of creating that would be welcomed by its customers, partners and employees). If every employee leaves the workday with a long list of to-dos for the next day and another list of to-dos to deprioritize altogether — items that would have created value if they could have been prioritized — there is an imbalance of value, time and effort, leaving value on the table. The easiest place to start with AI agents is looking at the work already being done and the value being created. This makes the initial mental math easy, as you can map the value that already exists and analyze opportunities to create the same value faster or more reliably. There’s nothing wrong with this exercise as a phase in a transformation process, but where most organizations and AI initiatives fail is in only considering how AI can apply to value already being created. This narrows their focus and investments to the narrow overlapping sliver in the Venn diagram below, leaving the majority of the addressable value on the table. Humans and machines inherently have different strengths and weaknesses. Organizations that collaboratively reinvent work with their business, technology and industry partners will outplay those who merely focus on one body of value and endlessly pursue greater degrees of automation without increasing total value output. Understanding AI agent capabilities through the SPAR framework To help explain how AI agents work, we’ve created what we call the SPAR framework: sense, plan, act and reflect. This framework mirrors how humans achieve our own goals and provides a natural way to understand how AI agents operate. Sensing: Just as we use our senses to gather information about the world around us, AI agents collect signals from their environment. They track triggers, gather relevant information and monitor their operating context. Planning: Once an agent has collected signals about its environment, it doesn’t just jump into execution. Like humans considering their options before acting, AI agents are developed to process available information in the context of their objectives and rules to make informed decisions about achieving their goals. Acting: The ability to take concrete action sets AI agents apart from simple analytical systems. They can coordinate multiple tools and systems to execute tasks, monitor their actions in real-time, and make adjustments to stay on course. Reflecting: Perhaps the most sophisticated capability is learning from experience. Advanced AI agents can evaluate their performance, analyze outcomes and refine their approaches based on what works best — creating a continuous improvement cycle. What makes AI agents powerful is how these four capabilities work together in an integrated cycle, creating a system that can pursue complex goals with increasing sophistication. This exploratory capability can be contrasted against existing processes that have already been optimized several times through digital transformation. Their reinvention might yield small short-term gains, but exploring new methods of creating value and making new markets could yield exponential growth. 5 Steps to build your AI agent strategy Most technologists, consultants and business leaders follow a traditional approach when introducing AI (accounting for an 87% failure rate): Create a list of problems; or Examine your data; Pick a set of potential use cases; Analyze use cases for return on investment (ROI), feasibility, cost, timeline; Choose a subset of use cases and invest in execution. This approach may seem defensible because it’s commonly understood to be best practice, but the data shows that it isn’t working. It’s time for a new approach. Map the total addressable value creation your organization could provide to your customers and partners given your core competencies and the regulatory and geopolitical conditions of the market. Assess the current value creation of your organization. Choose the top five most valuable and market-making opportunities for your organization to create new value. Analyze for ROI, feasibility, cost and timeline to engineer AI agent solutions (repeat steps 3 and 4 as necessary). Choose a subset of value cases and invest in execution. Creating new value with AI The journey into the era of autonomous transformation (with more autonomous systems creating value continuously) isn’t a sprint — it’s a strategic progression, building organizational capability alongside technological advancement. By initially identifying value and growing ambitions methodically, you’ll position your organization to thrive in the era of AI agents. Brian Evergreen is the author of Autonomous Transformation: Creating a More Human Future in the Era of Artificial Intelligence  Pascal Bornet is the author of Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work and Life Evergreen and Bornet are teaching a new online course on AI agents with Cassie Kozyrkov: Agentic Artificial Intelligence for Leaders source

Hospitality software firm Mews raised Dutch tech’s biggest funding round in the first quarter of 2025, in what was a tough start to the year for the sector. Dutch startups raised around €460mn in the quarter, with a 59% decline in growth-stage funding raising alarm bells, according to the Quarterly Startup Report. Together, the top 10 deals accounted for over €320mn — more than 75% of all funding raised last quarter. Here are the biggest Dutch deals of Q1 2025: 1. Mews — €68mn ($75mn)  Mews, based at TNW City in Amsterdam, has built a cloud-based system that helps hotels and other hospitality businesses streamline tasks like booking rooms, checking guests in and out, and processing payments.  The 💜 of EU tech The latest rumblings from the EU tech scene, a story from our wise ol’ founder Boris, and some questionable AI art. It’s free, every week, in your inbox. Sign up now! This round follows a raise of $100mn in credit financing in September and a $110mn equity round in March 2024 — when the scaleup became a unicorn.  2. Alesta Therapeutics — €65mn Alesta Therapeutics, based in Leiden, Netherlands, is a biotechnology company focused on developing novel oral small-molecule therapies for rare diseases.  3. Leyden Labs — €63mn ($70mn) Leyden Labs is another biotech startup from Leiden — home to one of Europe’s leading life science hubs. The company is developing intranasal medicines to protect against respiratory viruses.  4. Vivici — €32.5mn Vivici is a Dutch foodtech startup using precision fermentation to produce animal-free dairy proteins. Its proteins are designed to replace traditional dairy ingredients like whey and casein.  5. QuantWare — €20mn Quantware designs and manufactures superconducting quantum processors. The startup claims to have created a 3D chip architecture that offers the fastest route to a 1-million qubit quantum computer — and plans to sell it to Big Tech companies.    6. Thorizon – €16mn Deep tech startup Thorizon is developing modular molten salt reactors (MSRs) that utilise long-lived nuclear waste as fuel.  7. Varmx — €15mn Varmx is a biotech startup developing a treatment to reverse bleeding in patients taking blood thinners. 8. Workwize — €12mn ($13mn) Workwize provides cloud-based software for managing IT hardware in remote and hybrid workplaces. 9. Sirius Medical — €10mn Another biotech startup, Sirius Medical has developed a tumour localisation technology that helps surgeons to precisely locate and remove breast tumours. 10. Stacks — €9mn ($10mn)  ​Amsterdam-based Stacks provides an AI-driven platform that streamlines financial closing processes for businesses. Despite several eye-catching deals, a significant drop in growth-stage funding and fewer deals overall are raising concerns about the long-term health of the  Dutch tech ecosystem.  Fewer deals, fewer growth rounds for Dutch tech In total, just 79 deals were recorded in Q1 2025 — an 11% drop compared to the same period last year. It marked the fifth consecutive quarter in which deal count has fallen. Most striking is the sharp decline in later-stage funding. Series B+ rounds halved from 14 in Q1 2024 to just seven this year. In total, late-stage startups raised €287mn — down an eye-watering €609mn from the previous year.  Equally telling, for the second quarter in a row, there were no Dutch mega-deals above €100mn — a stark contrast to previous years when such rounds were relatively common, the report found. Early-stage startups, on the other hand, were a rare bright spot in an otherwise poor outlook. Seed deals (typically €1mn-€4mn) accounted for nearly half of all investments in Q1 2025, with total funding in this category growing over 15% year-on-year to €58.4mn. That’s a healthy sign for future innovation, but without sufficient late-stage capital, there’s a risk that promising Dutch startups will be forced to look abroad for growth funding. What’s next? The outlook for the rest of 2025 is mixed. On the one hand, the resilience of seed investment and a growing interest in deep tech and hardware — areas where Dutch startups like QuantWare and Thorizon excel — provide reasons for optimism. “We can be proud of the Dutch entrepreneurs who, together with investors, realise world-class deep tech innovations,” said Myrthe Hooijman, director of ecosystem change and governmental affairs at Techleap.  On the other hand, several issues are causing concern. Global trade tensions, a sluggish exit market, and the increasing caution of international investors could slow down growth-stage funding even further, according to the report. “We are not yet sounding the alarm, but standing still means going backwards,” said Lucien Burm, chairman of the Dutch Startup Association. “Not only did Europe lose its position internationally, but within Europe, the Netherlands is now losing importance.” “With the geopolitical and economic unrest of the moment, instead of reactive measures, broad and deep investment in the business and investment climate is the recipe.” The Quarterly Startup Report was put together by Dealroom.co, Golden Egg Check, KPMG, the Regional Development Companies (ROMs), the Dutch Association of Private Equity Companies (NVP), the Dutch Startup Association (dSa), and Techleap. The future of Dutch tech is a key theme at TNW Conference, which takes place on June 19-20 in Amsterdam. Tickets for the event are now on sale. Use the code TNWXMEDIA2025 at the check-out to get 30% off the price tag. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The general-purpose AI agent landscape is suddenly much more crowded and ambitious. This week, Palo Alto-based startup Genspark released what it calls Super Agent, a fast-moving autonomous system designed to handle real-world tasks across a wide range of domains – including some that raise eyebrows, like making phone calls to restaurants using a realistic synthetic voice. The launch adds fuel to what’s shaping up to be an important new front in the AI competition: Who will build the first reliable, flexible and truly useful general-purpose agent? Perhaps more urgently, what does that mean for enterprises? Genspark’s launch of Super Agent comes just three weeks after a different Chinese-founded startup, Manus, gained attention for its ability to coordinate tools and data sources to complete asynchronous cloud tasks like travel booking, resume screening and stock analysis – all without the hand-holding typical of most current agents. Genspark now claims to go even further. According to co-founder Eric Jing, Super Agent is built on three pillars: a concert of nine different LLMs, more than 80 tools and over 10 proprietary datasets – all working together in a coordinated flow. It moves well beyond traditional chatbots, handling complex workflows and returning fully executed outcomes. In a demo, Genspark’s agent planned a complete five-day San Diego trip, calculated walking distances between attractions, mapped public transit options and then used a voice-calling agent to book restaurants, including handling food allergies and seating preferences. Another demo showed the agent creating a cooking video reel by generating recipe steps, video scenes and audio overlays. In a third, it wrote and produced a South Park-style animated episode, riffing on the recent Signalgate political scandal involving sharing war plans with a political reporter. These may sound consumer-focused, but they showcase where the tech is headed – toward multi-modal, multi-step task automation that blurs the line between creative generation and execution. “Solving these real-world problems is much harder than we thought,” Jing says in the video, “but we’re excited about the progress we’ve made.” One compelling feature: Super Agent clearly visualizes its thought process, tracing how it reasons through each step, which tools it invokes and why. Watching that logic play out in real time makes the system feel less like a black box and more like a collaborative partner. It could also inspire enterprise developers to build similar traceable reasoning paths into their own AI systems, making applications more transparent and trustworthy. Super Agent was also impressively easy to try. The interface launched smoothly in a browser with no technical setup required. Genspark lets users begin testing without requiring personal credentials. In contrast, Manus still requires applicants to join a waitlist and disclose social accounts and other private information, adding friction to experimentation. We first wrote about Genspark back in November, when it launched Claude-powered financial reports. It has raised at least $160 million across two rounds, and is backed by U.S and Singapore based investors. Watch the latest video discussion between AI agent developer Sam Witteveen and me here for a deeper dive into how Genspark’s approach compares to other agent frameworks and why it matters for enterprise AI teams. How is Genspark pulling this off? Genspark’s approach stands out because it navigates a long-standing AI engineering challenge: tool orchestration at scale. Most current agents break down when juggling more than a handful of external APIs or tools. Genspark’s Super Agent appears to manage this better, likely by using model routing and retrieval-based selection to choose tools and sub-models dynamically based on the task. This strategy echoes the emerging research around CoTools, a new framework from Soochow University in China that enhances how LLMs use extensive and evolving toolsets. Unlike older approaches that rely heavily on prompt engineering or rigid fine-tuning, CoTools keeps the base model “frozen” while training smaller components to judge, retrieve, and call tools efficiently. Another enabler is the Model Context Protocol (MCP), a lesser-known but increasingly adopted standard that allows agents to carry richer tool and memory contexts across steps. Combined with Genspark’s proprietary datasets, MCP may be one reason their agent appears more “steerable” than alternatives. How does this compare to Manus? Genspark isn’t the first startup to promote general agents. Manus, launched last month by the China-based company Monica, made waves with its multi-agent system, which autonomously runs tools like a web browser, code editor or spreadsheet engine to complete multi-step tasks. Manus’s efficient integration of open-source parts, including web tools and LLMs like Claude from Anthropic, was surprising. Despite not building a proprietary model stack, it still outperformed OpenAI on the GAIA benchmark — a synthetic test designed to evaluate real-world task automation by agents. Genspark, however, claims to have leapfrogged Manus, scoring 87.8% on GAIA—ahead of Manus’s reported 86%—and doing so with an architecture that includes proprietary components and more extensive tool coverage. The big tech players: Still playing it safe? Meanwhile, the largest U.S.-based AI companies have been cautious. Microsoft’s main AI agent offering, Copilot Studio, focuses on fine-tuned vertical agents that align closely with enterprise apps like Excel and Outlook. OpenAI’s Agent SDK provides building blocks but stops short of shipping its own full-featured, general-purpose agent. Amazon’s recently announced Nova Act takes a developer-first approach, offering atomic browser-based actions via SDK but tightly tied to its Nova LLM and cloud infrastructure. These approaches are more modular, more secure and clearly targeted toward enterprise use. But they lack the ambition—or autonomy—shown in Genspark’s demo. One reason may be risk aversion. The reputational cost could be high if a general agent from Google or Microsoft books the wrong flight or says something odd on a voice call. These companies are also locked into their own model ecosystems, limiting their flexibility to experiment with multi-model orchestration. Startups like Genspark, by contrast, have the freedom to mix and match LLMs – and to move fast. Should enterprises care? That’s the strategic question. Most enterprises don’t need a

As organizations embrace hybrid and remote work models, the surge in online accounts supporting workflows has led to a growing challenge of managing numerous login credentials. This not only escalates the complexity of password management but also gives rise to potential security issues. A single incident of compromise in one account can put an entire organization — and even partnering vendors — at serious risk. To simplify the password management process and mitigate password-related breaches, organizations leverage enterprise password managers. Enterprise password managers offer a secure, efficient and centralized platform to create, store and manage passwords, reducing the risk of unauthorized access and fostering regulatory compliance. This article will explore the top enterprise password managers, examining their key features, pricing, benefits and drawbacks. 1 NordPass Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Micro, Small, Medium, Large, Enterprise Features Activity Log, Business Admin Panel for user management, Company-wide settings, and more 2 Dashlane Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Micro, Small, Medium, Large, Enterprise Features Automated Provisioning 3 ManageEngine ADSelfService Plus Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Access Management, Compliance Management, Credential Management, and more Top enterprise password managers: Comparison table The table below is a comparison of the key features that can be found in every top-quality enterprise password manager. Browser extension Encryption type Password sharing Biometric access Free version Pricing Keeper Brave, Chrome, Firefox, Opera, Edge and Safari. AES 256-bit, Elliptic-Curve cryptography (EC) Yes Yes, on macOS. Yes Starts at $2/user per month. Dashlane Chrome, Firefox, Opera, Brave, Edge and Safari. Argon2 Yes Yes Yes Starts at $8/seat per month. 1Password Chrome, Brave, Firefox, Edge and Safari. 256-bit AES Yes Yes No Starts at $7.99/user per month. Bitwarden Chrome, Firefox, Opera, Edge and Safari. AES-CBC 256-bit, PBKDF2 SHA-256 or Argon2. Yes Yes Yes Starts at $6/user per month. Enpass Opera, Vivaldi, Brave, Chrome, Firefox, Edge, Safari and Tor. 256-bit AES 256-bit, PBKDF2-HMAC-SHA512 on SQLCipher engine. Yes Yes Yes Starts at $9.99/user per month for enterprise users. ManageEngine Password Manager Pro Chrome, Edge, Firefox, Opera, Brave and Safari. AES-256 encryption Yes Yes No Enterprise pricing starts at $3,995 for 10 admins. Zoho Vault Ulaa, Chrome, Firefox, Safari, Edge, Vivaldi, Brave, Opera. AES-256 bit Yes Limited Yes Starts at $7.20/user per month for enterprise users. NordPass Opera, Vivaldi, Brave, Chrome, Firefox, Edge, Safari. XChaCha20 Yes Yes Yes Starts at $1.79/user per month. Top enterprise password managers Here are our picks for the eight best enterprise password managers in 2024. Keeper: Best overall enterprise password manager Image: Keeper Keeper is a password management solution that offers encrypted vaults for every user. It provides users with an organizational structure with folders and subfolders, along with shared team folders. With Keeper, users can access their encrypted vaults from an unlimited number of devices. In addition, Keeper has a policy engine and enforcement feature that guarantees compliance with security protocols, while its Security Audit and Activity Reporting features offer insights into password usage and user actions. I particularly liked Keeper’s BreachWatch feature — a dark web monitoring tool that constantly scans employees’ password vaults for passwords that have been exposed to the dark web and alerts security teams for immediate response. For organizations which have hundreds to thousands of employees, this is a must-have feature to keep internal credentials secure. Why I chose Keeper I was impressed with Keeper’s emphasis on ease of use, combined with strong security measures like secure file storage, secrets manager and role-based access controls for large organizations. In my opinion, its balance of usability and management-focused features helps it stand out as my top option for enterprises looking for a password management solution. Features Command Line Provisioning. Multi-factor authentication. Event log and notification. Security audits. Active Directory and LDAP synchronization. Single sign-on (SAML 2.0) authentication. Keeper dark web monitoring. Image: Keeper Keeper pros and cons Pros Cons Easy to set up. Automatically notifies users of any vulnerability issues. Offers developer APIs. Offers compliance reporting. Secret manager capability. KeeperChat for encrypted workplace messaging. Slow customer support response time. Pricing Keeper offers three pricing plans for its business and enterprise users. Business Starter: Starts at $2 per user per month, minimum 5 users and max of 10 users (billed annually). Business: Starts at $3.75 per user per month (billed annually). Enterprise: Contact Keeper for a custom quote and availability. If you want to learn more, read our full Keeper review here. Dashlane: Best for cross-platform compatibility Image: Dashlane Dashlane is a password management tool that allows users to access and manage passwords across different devices and platforms. It has an unlimited, secure password-sharing feature that allows users to share passwords while maintaining total control. This means that access to shared passwords can be revoked at any time. For enhanced security, the tool includes dark web monitoring and the ability to auto-send alerts in case of a data breach. Additionally, Dashlane allows users to generate strong passwords with a single click and automatically fills them in whenever needed, streamlining the log-in process. Personally, I like how Dashlane integrates with popular identity management solutions like Okta, Duo and OneLogin. This offers organizations a well-rounded and multi-layered security posture to ward off against attacks and vulnerabilities. Why I chose Dashlane Dashlane made it to our list for its inclusion of a VPN feature for Wi-Fi protection and a limitless secure password-sharing feature. Features Unlimited secure password sharing. Cross-platform accessibility. One-click passwords and forms. Dark web monitoring and alerts. Password generator. Cross-platform accessibility in Dashlane. Image: Dashlane Dashlane pros and cons Pros Cons Personalized security alerts. Real-time phishing alert. Integrates with popular IAM providers like Okta and Duo. Supports role-based permissions. Provides contextual breach alerts.