For businesses already using an AI gateway<\/a>, the acquisition raises several important questions. Will their gateway remain flexible across different providers? Will security features become closely tied to a larger vendor’s products? Could pricing, support or product development change? And should organisations choose a large security platform or an independent AI gateway?<\/p>\n\n\n\n These questions matter because an AI gateway is becoming an important part of enterprise infrastructure. Choosing one affects how developers build applications, how security teams apply controls and how finance teams understand AI costs.<\/p>\n\n\n\n In this article, we explain what happened in the Palo Alto Portkey acquisition, why it matters for the AI gateway market and what organisations should consider before making their next gateway decision.<\/p>\n\n\n On 30 April 2026, Palo Alto Networks announced its intention to acquire Portkey, a company known for its AI gateway and observability technology.<\/p>\n\n\n\n The acquisition was officially completed on 29 May 2026. Palo Alto Networks confirmed that Portkey would become a central part of its Prisma AIRS AI security platform.<\/p>\n\n\n\n The company later announced the general availability of Prisma AIRS AI Gateway in July 2026, bringing gateway capabilities into its wider enterprise AI security offering.<\/p>\n\n\n\n According to Palo Alto Networks’ fiscal 2026 annual report, the total purchase consideration for Portkey was approximately $117 million.<\/p>\n\n\n\n The acquisition highlights how AI gateways are moving from useful developer tools towards important enterprise control systems.<\/p>\n\n\n\n Palo Alto Networks already offered cybersecurity products for networks, cloud systems and AI applications. However, businesses are increasingly deploying AI agents that can connect to internal systems, access sensitive information and carry out tasks without constant human involvement.<\/p>\n\n\n\n These agents create new security and operational challenges.<\/p>\n\n\n\n Portkey provides a gateway layer that sits between AI applications and the models they use. This allows organisations to route requests, monitor activity and apply controls through a central system.<\/p>\n\n\n\n By adding Portkey to Prisma AIRS, Palo Alto Networks aims to bring AI gateway management and runtime security closer together.<\/p>\n\n\n\n This makes sense from a security perspective. If a company can monitor AI requests as they happen, it has another opportunity to identify risks and enforce rules before those requests reach a model or return to an application.<\/p>\n\n\n\n However, the acquisition also creates questions about how much of the AI gateway market will become part of larger cybersecurity platforms.<\/p>\n\n\n\n An AI gateway is a central layer that manages communication between applications and artificial intelligence models.<\/p>\n\n\n\n Instead of connecting every application directly to different AI providers, businesses can send supported requests through a gateway.<\/p>\n\n\n\n The gateway can then route those requests, apply access rules, monitor usage and collect information about costs and performance.<\/p>\n\n\n\n Consider a business using several AI models across customer support, software development and internal reporting.<\/p>\n\n\n\n Without a gateway, each application may have its own provider connections, API keys, spending records and security settings.<\/p>\n\n\n\n This creates a fragmented environment that becomes harder to manage as AI adoption grows.<\/p>\n\n\n\n With an AI gateway, the organisation can bring supported AI traffic through a shared management layer.<\/p>\n\n\n\n For example, the gateway may direct a request to one model, apply a spending limit, record token usage and use another model if the first provider becomes unavailable.<\/p>\n\n\n\n The exact capabilities depend on the platform and how it is configured.<\/p>\n\n\n\n AI systems are no longer limited to employees asking questions through a chatbot.<\/p>\n\n\n\n Businesses are developing AI applications that process large amounts of information, connect to different models and perform tasks automatically.<\/p>\n\n\n\n AI agents may also call external tools, interact with business systems and make repeated requests without direct human input.<\/p>\n\n\n\n This increases the need for central visibility and control.<\/p>\n\n\n\n An AI gateway can help organisations manage the AI traffic passing through it, but it cannot automatically monitor every AI tool or employee account outside that environment.<\/p>\n\n\n\n Businesses should understand this difference when evaluating gateway security and governance claims.<\/p>\n\n\n\n Quick link:<\/strong> Top AI Observability Platforms of All Time<\/a><\/em><\/p>\n\n\n\n The acquisition sends an important message to enterprise buyers: AI gateways are becoming part of the wider security and governance market.<\/p>\n\n\n\n This development may influence how organisations compare vendors, structure their AI systems and plan future investments.<\/p>\n\n\n\n Early AI gateway discussions often focused on developer convenience.<\/p>\n\n\n\n Businesses wanted one connection to multiple AI models, better request routing and easier management of API keys.<\/p>\n\n\n\n Those features remain important, but enterprise requirements are expanding.<\/p>\n\n\n\n Security teams now want to understand which applications and agents are accessing models, what permissions they have and whether sensitive information is being exposed.<\/p>\n\n\n\n The Palo Alto Portkey acquisition reflects this growing demand.<\/p>\n\n\n\n By combining gateway functions with Prisma AIRS, Palo Alto Networks is positioning AI traffic management as part of a broader security system.<\/p>\n\n\n\n For organisations, this means security should be a central part of gateway selection rather than an additional feature considered later.<\/p>\n\n\n\n Palo Alto Networks is following a wider technology strategy in which multiple capabilities are brought together under one platform.<\/p>\n\n\n\n For some enterprises, this can simplify vendor management and make it easier to connect related security products.<\/p>\n\n\n\n A company already using Palo Alto Networks may find value in managing AI gateway security alongside other security operations.<\/p>\n\n\n\n However, larger platforms are not automatically the best option for every organisation.<\/p>\n\n\n\n Businesses should assess whether the combined product meets their actual needs, whether integration adds complexity and whether they will pay for capabilities they do not require.<\/p>\n\n\n\n The right decision depends on the organisation’s AI environment, existing systems and long-term plans.<\/p>\n\n\n\n The acquisition does not mean every business needs an AI gateway owned by a large cybersecurity company.<\/p>\n\n\n\n Independent platforms may appeal to organisations that want focused AI operations, flexible model access, transparent spending controls or a gateway that works alongside different security products.<\/p>\n\n\n\n Some businesses may also prefer to keep AI infrastructure management separate from their main cybersecurity vendor.<\/p>\n\n\n\n This can help teams evaluate products based on specific operational requirements rather than existing supplier relationships.<\/p>\n\n\n\n The important question is whether the gateway provides the control, visibility and flexibility the business needs.<\/p>\n\n\n\n For organisations already using Portkey, the acquisition creates both opportunities and questions.<\/p>\n\n\n\n Palo Alto Networks stated that it would continue supporting existing and new Portkey customers following the acquisition.<\/p>\n\n\n\n The integration with Prisma AIRS may also give customers access to a wider range of enterprise security capabilities.<\/p>\n\n\n\n However, customers should review the product’s current terms, available features and future development plans rather than assume that every aspect of the original service will remain unchanged.<\/p>\n\n\n\n The acquisition has already resulted in Portkey technology becoming part of Prisma AIRS AI Gateway.<\/p>\n\n\n\n The wider platform includes capabilities for model access, request routing, usage monitoring, security policies and access management.<\/p>\n\n\n\n Existing customers should review which features are available under their current agreements and whether moving to the integrated platform requires technical or commercial changes.<\/p>\n\n\n\n They should also ask about API compatibility, deployment options, logging, support arrangements and product migration.<\/p>\n\n\n\n Acquisitions can lead to changes in product packaging, licensing and commercial terms.<\/p>\n\n\n\n However, the Palo Alto Portkey acquisition does not, by itself, prove that every customer’s pricing will increase or that particular features will become unavailable.<\/p>\n\n\n\n Organisations should request current pricing information and compare the full cost of ownership.<\/p>\n\n\n\n This should include gateway fees, security features, support, deployment costs and any additional services required.<\/p>\n\n\n\n A gateway that appears affordable at low usage may become more expensive as AI traffic grows.<\/p>\n\n\n\n Integration stability is another important consideration.<\/p>\n\n\n\n Businesses may have applications that depend on specific gateway APIs, routing rules, logging formats or authentication methods.<\/p>\n\n\n\n Before making changes, technical teams should test their existing workflows against the supported platform.<\/p>\n\n\n\n This reduces the risk of unexpected disruption to production AI applications.<\/p>\n\n\n\n The Palo Alto Portkey acquisition provides a useful reason to review AI gateway requirements.<\/p>\n\n\n\n Rather than choosing a platform based only on brand recognition, organisations should evaluate how well it supports their AI operations.<\/p>\n\n\n\n Many businesses use more than one AI provider.<\/p>\n\n\n\n A customer support application may use one model, while software development and internal analysis use different services.<\/p>\n\n\n\n An effective gateway should support the models and providers the organisation needs without creating unnecessary technical barriers.<\/p>\n\n\n\n AI models continue to change in price, performance and capability.<\/p>\n\n\n\n A business that can switch between supported providers may be better placed to manage costs, improve reliability and adopt new technology.<\/p>\n\n\n\n Before selecting a gateway, confirm which providers are supported and how difficult it is to change models.<\/p>\n\n\n\n AI spending can become difficult to manage when applications use different providers, accounts and API keys.<\/p>\n\n\n\n A gateway should help teams understand how much AI is being consumed and where the costs originate.<\/p>\n\n\n\n Useful information includes token usage, model selection, application activity, request volume and spending by team or workload.<\/p>\n\n\n\n A monthly AI bill does not explain whether the spending is productive.<\/p>\n\n\n\n Organisations should also consider whether they can connect AI usage to business applications, teams and expected outcomes.<\/p>\n\n\n\n This makes it easier to identify expensive workloads and improve how models are used.<\/p>\n\n\n\n Security should be evaluated according to the organisation’s actual risks.<\/p>\n\n\n\n Important considerations include API key management, access permissions, policy enforcement, sensitive data handling and audit records.<\/p>\n\n\n\n For AI agents, businesses should also review how the gateway works with agent identity, tool permissions and approval requirements.<\/p>\n\n\n\n A gateway may provide useful controls over model requests without securing every action an agent performs elsewhere.<\/p>\n\n\n\n Organisations should avoid assuming that gateway monitoring replaces wider application security.<\/p>\n\n\n\n Production AI applications need reliable access to models.<\/p>\n\n\n\n If a provider becomes unavailable, the gateway may need to direct requests to another approved model.<\/p>\n\n\n\n However, switching models can affect output quality, data handling and application behaviour.<\/p>\n\n\n\n Businesses should assess latency, availability, fallback rules and the effect of failures on real workloads.<\/p>\n\n\n\n Vendor performance claims should be checked against the organisation’s own requirements.<\/p>\n\n\n\n A gateway used for internal experimentation may have different reliability needs from one supporting customer-facing applications.<\/p>\n\n\n\n Different organisations have different requirements for where AI traffic is processed.<\/p>\n\n\n\n Some may prefer a managed cloud gateway, while others may need greater control over the gateway’s data processing environment.<\/p>\n\n\n\n Palo Alto Networks documents both SaaS and hybrid deployment options for Prisma AIRS AI Gateway.<\/p>\n\n\n\n Businesses should compare available deployment models, data retention settings, regional availability and security responsibilities before choosing a platform.<\/p>\n\n\n\n Gateway costs should be assessed alongside the wider cost of AI consumption.<\/p>\n\n\n\n For example, organisations may need to pay for model usage, gateway services, security features, infrastructure and support.<\/p>\n\n\n\n The total cost can change as applications grow or autonomous agents generate more requests.<\/p>\n\n\n\n A good evaluation should include realistic usage forecasts and tests of how costs change under higher demand.<\/p>\n\n\n\n Vendor lock-in occurs when changing a technology provider becomes difficult or expensive.<\/p>\n\n\n\n For AI gateways, this may happen when applications depend heavily on vendor-specific APIs, policies or monitoring systems.<\/p>\n\n\n\n Organisations should consider how easily they can export configuration data, migrate routing rules and move workloads to another platform.<\/p>\n\n\n\n This does not mean large integrated platforms should be avoided.<\/p>\n\n\n\n It means businesses should understand the trade-offs before making a long-term commitment.<\/p>\n\n\n\n The acquisition creates an important choice between a gateway closely connected to a broader cybersecurity platform and an independent AI operations solution.<\/p>\n\n\n\n Neither approach is automatically better.<\/p>\n\n\n\n A large enterprise with an established Palo Alto Networks environment may benefit from closer links between AI gateway management and existing security operations.<\/p>\n\n\n\n This may be particularly relevant when the organisation wants to combine AI request monitoring with runtime security, identity controls and wider threat management.<\/p>\n\n\n\n The value depends on how well these capabilities work together in the customer’s actual environment.<\/p>\n\n\n\n An independent gateway may suit an organisation that places greater importance on focused AI operations, provider flexibility, cost management or integration with an existing mix of security tools.<\/p>\n\n\n\n It may also appeal to teams that want to avoid making their AI architecture dependent on one larger technology provider.<\/p>\n\n\n\n However, independent platforms should still be evaluated for security, reliability, support and operational maturity.<\/p>\n\n\n\n The decision should be based on tested capabilities, not assumptions about vendor size.<\/p>\n\n\n\n AI gateway selection is no longer only a developer decision.<\/p>\n\n\n\n It affects security teams, finance leaders, platform engineers and the people responsible for AI governance.<\/p>\n\n\n\n A gateway determines how supported AI requests are routed, what information can be monitored and which controls can be applied centrally.<\/p>\n\n\n\n This makes it an important part of an organisation’s wider AI management approach.<\/p>\n\n\n\n An organisation cannot manage AI spending or enforce useful policies without understanding how its systems are being used.<\/p>\n\n\n\n Teams need to know which applications connect to which models, who owns those workloads and what resources they consume.<\/p>\n\n\n\n Without that information, governance can become a collection of written policies with limited operational value.<\/p>\n\n\n\n Security and control should not make approved AI tools unnecessarily difficult to use.<\/p>\n\n\n\n When employees and developers cannot access suitable tools, they may look for alternatives outside official systems.<\/p>\n\n\n\n An effective gateway strategy should therefore balance clear rules with practical access to approved AI services.<\/p>\n\n\n\n This allows organisations to support innovation while maintaining appropriate oversight.<\/p>\n\n\n\n The acquisition places strong attention on AI security, but businesses should not overlook financial control.<\/p>\n\n\n\n As AI agents become more common, organisations may face rising costs from repeated requests, large context windows, unnecessary model usage and poorly managed workloads.<\/p>\n\n\n\n A gateway should help teams understand consumption and apply appropriate controls before costs become difficult to manage.<\/p>\n\n\n\n This is especially important for businesses using several AI providers across different departments.<\/p>\n\n\n\n The Palo Alto Portkey acquisition shows that AI gateways are becoming an important part of enterprise infrastructure. However, organisations should remember that AI security, usage governance and cost management are connected requirements.<\/p>\n\n\n\n WrangleAI focuses on helping businesses gain better visibility and control over how AI is used across their operations.<\/a><\/p>\n\n\n\n Its capabilities include AI usage monitoring<\/a>, cost governance<\/a>, Optimised AI Keys<\/a>, spending alerts, budget controls and tools designed to improve how organisations manage AI consumption.<\/p>\n\n\n\n For businesses using multiple AI models and providers, this approach can help teams understand where AI resources are being consumed and identify opportunities to improve efficiency.<\/p>\n\n\n\n An organisation may have strong security controls but still struggle to explain why its AI spending is increasing.<\/p>\n\n\n\n Another business may have access to several powerful models without understanding which applications, teams or workflows are responsible for consumption.<\/p>\n\n\n\n WrangleAI addresses this operational challenge by helping organisations bring greater structure to AI usage and spending.<\/p>\n\n\n\n This makes it relevant for teams evaluating how an AI gateway fits into their wider AI governance strategy.<\/p>\n\n\n\n Businesses should still compare supported integrations, security features, deployment requirements and technical capabilities before selecting any platform.<\/p>\n\n\n\n The Palo Alto Portkey acquisition<\/strong> marks an important development in the AI gateway market.<\/p>\n\n\n\n By bringing Portkey into Prisma AIRS, Palo Alto Networks has strengthened its position in enterprise AI security and demonstrated the growing importance of managing AI traffic through a central control layer.<\/p>\n\n\n\n For businesses choosing an AI gateway, the message is clear. Gateway selection should not focus only on connecting applications to language models.<\/p>\n\n\n\n Organisations also need to consider security, governance, provider flexibility, operational reliability, spending visibility and long-term control over their AI infrastructure.<\/p>\n\n\n\n Large integrated security platforms may offer advantages for some enterprises, while independent AI management solutions may better suit other operational needs.<\/p>\n\n\n\n The best choice is the one that supports the organisation’s current requirements without creating unnecessary limits as its AI strategy develops.<\/p>\n\n\n\n WrangleAI helps organisations take greater control of AI usage and costs, making it a valuable platform to consider when building a more visible, accountable and cost-aware AI environment.<\/p>\n\n\n\n As the AI gateway market continues to evolve, businesses that prioritise visibility, flexibility and measurable value will be better prepared to manage AI at scale.<\/p>\n\n\n\n The Palo Alto Portkey acquisition refers to Palo Alto Networks’ purchase of AI gateway company Portkey, completed on 29 May 2026. The acquisition brought Portkey’s gateway technology into the Prisma AIRS AI security platform to support AI traffic management, governance and security.<\/p>\n<\/div><\/div>\n\n\n\n Palo Alto Networks acquired Portkey to strengthen its AI security offering with a gateway capable of routing, monitoring and applying controls to AI interactions. The acquisition supports its wider strategy of securing enterprise AI applications and autonomous agents.<\/p>\n<\/div><\/div>\n\n\n\n Not necessarily. Businesses should review their current gateway’s security, reliability, provider support, costs and governance features before deciding whether to switch. The acquisition is a reason to reassess requirements, not proof that existing independent gateways are unsuitable.<\/p>\n<\/div><\/div>\n\n\n\n An AI gateway manages supported requests between applications and AI models, including routing, usage monitoring and access controls. An AI security platform may provide wider protection across models, applications, agents, data and runtime activity. Some products combine both types of capabilities.<\/p>\n<\/div><\/div>\n\n\n\n Businesses should evaluate multi-model support, security controls, cost visibility, API compatibility, reliability, deployment options, vendor independence and long-term pricing. They should also test the gateway against their actual applications before making a final decision.<\/p>\n<\/div><\/div>\n\n\n\n WrangleAI helps organisations monitor AI consumption, improve cost visibility and apply usage management controls across supported AI environments. Its approach supports teams that want greater accountability and more effective management of AI resources.<\/p>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":" The AI gateway market is changing, and one of the clearest signs came when Palo Alto Networks acquired Portkey in […]<\/p>\n","protected":false},"author":1,"featured_media":483,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[4,6],"tags":[],"class_list":["post-482","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-cost-controls","category-ai-performance-optimisation"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\tWhat Happened in the Palo Alto Portkey Acquisition?<\/h2>\n\n\n\n
Why Did Palo Alto Networks Acquire Portkey?<\/h3>\n\n\n\n
What Is an AI Gateway and Why Does It Matter?<\/h2>\n\n\n\n
How Does an AI Gateway Work?<\/h3>\n\n\n\n
Why Are AI Gateways Becoming More Important?<\/h3>\n\n\n\n
Why the Palo Alto Portkey Acquisition Matters for the AI Gateway Market<\/h2>\n\n\n\n
1. AI Gateway Security Is Becoming a Major Priority<\/h3>\n\n\n\n
2. The Market Is Moving Towards Larger Platforms<\/h3>\n\n\n\n
3. Independent AI Gateway Providers Still Have a Role<\/h3>\n\n\n\n
![\"CTA\"](\"https:\/\/wrangleai.com\/blog\/wp-content\/uploads\/2025\/09\/WrangleAI-CTA-2-1024x171.png\")
<\/a><\/figure>\n\n\n\nWhat Does the Acquisition Mean for Existing Portkey Customers?<\/h2>\n\n\n\n
Will Portkey’s Features Change?<\/h3>\n\n\n\n
Could Pricing and Licensing Change?<\/h3>\n\n\n\n
What About Existing Integrations?<\/h3>\n\n\n\n
What Should Businesses Look for When Choosing an AI Gateway?<\/h2>\n\n\n\n
1. Multi-Model and Multi-Provider Support<\/h2>\n\n\n\n
Why Provider Flexibility Matters<\/h3>\n\n\n\n
2. Clear AI Usage and Cost Visibility<\/h2>\n\n\n\n
Look Beyond Total AI Spending<\/h3>\n\n\n\n
3. Strong Security and Governance Controls<\/h2>\n\n\n\n
4. Reliable Routing and Failover<\/h2>\n\n\n\n
Test Reliability Before Deployment<\/h3>\n\n\n\n
5. Flexible Deployment and Data Control<\/h2>\n\n\n\n
6. Transparent Pricing and Long-Term Costs<\/h2>\n\n\n\n
7. Avoiding Unnecessary Vendor Lock-In<\/h2>\n\n\n\n
Palo Alto Prisma AIRS AI Gateway vs Independent AI Gateways<\/h2>\n\n\n\n
When an Integrated Security Platform May Make Sense<\/h3>\n\n\n\n
When an Independent AI Gateway May Be a Better Fit<\/h3>\n\n\n\n
Why AI Gateway Choice Is Also an AI Governance Decision<\/h2>\n\n\n\n
Visibility Must Come Before Control<\/h3>\n\n\n\n
Governance Should Support Innovation<\/h3>\n\n\n\n
AI Cost Governance Deserves Equal Attention<\/h3>\n\n\n\n
How WrangleAI Supports a Flexible AI Gateway Strategy<\/h2>\n\n\n\n
Why WrangleAI’s Approach Matters<\/h3>\n\n\n\n
Conclusion: What the Palo Alto Portkey Acquisition Means for Your Business<\/h2>\n\n\n\n
FAQs<\/h2>\n\n\n\n
What is the Palo Alto Portkey acquisition?<\/h3>
Why did Palo Alto Networks acquire Portkey?<\/h3>
Does the Palo Alto Portkey acquisition mean businesses should change AI gateways?<\/h3>
What is the difference between an AI gateway and an AI security platform?<\/h3>
What should businesses consider before choosing an AI gateway?<\/h3>
How does WrangleAI help with AI governance?<\/h3>