AI agent governance requires clear ownership. Learn how IT leaders can manage sensitive data access, preserve audit trails, and test shutdown controls.
The post AI Agent Governance: Who Owns Access and Accountability? appeared first on TechRepublic.
For ten days, auditors appointed by the Korea Internet & Security Agency (KISA) sat together with us and worked through 80 controls. That is what it took for a company headquartered in the United States, operating a global network serving Korean users, to be certified in South Korea. Cloudflare has now obtained South Korea's Information Security Management System (ISMS) certification under the ISMS-P framework.
For customers in Korea, this is more than a compliance checkbox. It is evidence that Cloudflare's security and privacy program has been examined not only for whether our controls exist, but for how they operate in the context of Korean law, the Korean language, and the particular expectations of Korean regulators.
The most visible result of this work is the Cloudflare account sign-up page. In most parts of the world, the line that sits above the sign-up button reads: "By continuing, I agree to Cloudflare's terms, privacy policy, and cookie policy."
A user signing up from South Korea sees something different. The Korean experience is triggered by the country selected at sign-up and by IP geolocation from within South Korea, and it breaks the same agreement into four separately labeled items, each marked required or optional, each linking to its full text, with an option to agree to all of them at once:
The three required items are hard gates. The sign-up button stays disabled until all three are checked, so there is no path through the form that creates an account without an affirmative action on each one. The optional item governs marketing permission only, and leaving it unchecked has no effect on the account creation (it merely opts the user out of receiving marketing communications).
Itemizing consent on a form we control is straightforward. The difficulty was the sign-up paths that skip that form entirely.
Globally, you can create a Cloudflare account with Google, Apple, or GitHub. Those flows hand the user to an identity provider and return with an authenticated identity, and they never render our own sign-up form, which is precisely where the four consent items live. There is no step in that handoff where we can present three required items, link each to its full Korean text, and require an affirmative action on each before the account exists. The identity provider's screen is not ours to change.
We could either build a separate post-authentication consent gate for one country, or remove the paths that bypass the gate we already had. We chose the second. Social sign-up is not offered in South Korea, so every account created there goes through Cloudflare’s sign-up form, which enforces the required consents.
The country signal is the same one available to any Cloudflare customer. Cloudflare derives a two-letter country code from the client IP address and exposes it on the request, as the CF-IPCountry header at the origin and as request.cf.country inside a Worker. Reduced to its essentials, the branch is a string comparison:
Entrar
// Illustrative: the shape of the check, not Cloudflare's own dashboard code.
export default {
async fetch(request) {
// Two-letter country code derived from the client IP.
// Same value as the CF-IPCountry request header.
// Cloudflare's network populates this on the incoming request, so there is
// no geolocation database, lookup service, or extra round trip of our own.
const country = request.cf?.country;
if (country === "KR") {
return renderSignUp({
locale: "ko-KR",
consent: "itemized", // four separate items, three of them required
socialLogin: false, // no path that skips the consent form
});
}
return renderSignUp({ locale: "en-US", consent: "combined", socialLogin: true });
},
};What that does not show is why the country code is not the whole trigger. We document the limits of IP geolocation: it is an estimate rather than an exact science, addresses rotate and change ownership, and it should not be the only signal where the use case is critical to meeting the objectives of a local requirement. A Korean resident traveling abroad, or behind a VPN or a mobile carrier's NAT, may not arrive with a Korean address. So IP-based geolocation decides which form appears by default, but the country a user selects at sign-up overrides that and carries the decision from there. The IP address tells us where a request came from; only the user can tell us where they reside. Keeping those two apart is what makes the consent meaningful rather than presumed.
It is a small feature. It took a country-level product decision, and a change to the account creation path.
ISMS is a detailed, localized certification standard. It covers security policy, access control, authentication and permission management, encryption, incident response, risk management, and disaster recovery, all assessed against how personal data actually moves through an organization's systems, and against Korea's Personal Information Protection Act and its associated regulatory guidelines.
Certification requires an independent audit by an auditor appointed by KISA, a governmental institution affiliated with the Ministry of Science and ICT (MSIT), followed by review from a special committee. It is valid for three years, with an annual audit required to maintain it.
The ISMS certification is primarily established under Article 47 of Korea's Act on Promotion of Information and Communications Network Utilization and Information Protection, etc., with the certification criteria and procedure set out in its Enforcement Decree and in the public notification on ISMS certification issued by MSIT.
Cloudflare is already certified against ISO/IEC 27001, ISO/IEC 27701, ISO/IEC 27017, ISO/IEC 27018 and many other globally recognized frameworks. ISMS does not replace any of them. It is a localization of the same principles, layered with Korean regulatory requirements, and that changes what auditors look for and how they look for it.
The controls in scope started with the review of data flows. We presented detailed data flow diagrams showing every path by which employees could access personal information that Cloudflare collects, processes, and stores. The flows themselves are not Korea-specific. What was different was the form the evidence had to take: the auditors were not willing to work from a narrative description of how data moves, they wanted diagrams they could read and interrogate. For each one, they examined every access control layer and tested its effectiveness, across our internal systems, our public-facing websites, event pages, and the Cloudflare dashboard, covering the full lifecycle of a user's data from first interaction through to destruction. Those diagrams are not published here due to confidentiality.
The audit also scrutinized the language and terminology of our consent collection: the exact wording at sign-up, the structure of each notification, and whether the items were presented separately and clearly. That is the kind of detail the ISMS framework is designed to surface.
Part of the answer is how audit cycles work. An ISMS audit covers a single annual period, and all evidence, documentation, and systems must reflect that period. Our preparation ran past one audit year and into the next, which meant retranslating updated policies for the new audit year, re-collecting and reassessing evidence, republishing an updated privacy policy, and absorbing formatting and design changes our marketing and website teams had introduced in the meantime.
KISA defines the certified scope as a service boundary rather than as an enumerated list of in-scope products. The Statement of Scope submitted to KISA describes that boundary in three parts:
If a customer-consumed Cloudflare product is delivered through that certified service boundary, meaning it runs on the same certified platform, is operated by the same certified teams, and is governed by the same ISMS, it is covered by the certificate. The certificate is held by Cloudflare, Inc.
That is a different shape from the reports most procurement teams work with. A SOC 2 report or an ISO 27001 certificate describes the system it covers and names the services included, so coverage is confirmed by finding the product in that list. The ISMS certificate carries no such list. Coverage follows the delivery path instead, whether or not a product is named anywhere.
For organizations operating in Korea, this gives legal, security, and procurement teams a local assurance benchmark alongside Cloudflare's broader compliance portfolio. ISO/IEC 27001 and SOC 2 demonstrate a general security posture. ISMS reflects Korea-specific legal and regulatory expectations. That distinction matters in third-party risk reviews and in preparing for a team’s own compliance assessments.
Cloudflare’s entry can be found on KISA's public register of certified organizations, which is the independent, verifiable confirmation to cite in a risk review. Broader privacy and data protection material sits on the Cloudflare Trust Hub.
The question that usually stalls a vendor review of Cloudflare is whether a particular product in use is in scope. The certificate does not answer that by name, because it lists no products. It answers by boundary, meaning that the product is in scope if it is delivered through the certified service.
For multinational teams managing security across regions, the certification confirms that Cloudflare's program has been reviewed against local requirements in one of Asia's most important digital markets, not just designed for global scale.
ISMS is not a harder certification than the other assurance audits we go through. It is a more nuanced one. It is built around the regulatory needs of one specific region, and it asks for genuine investment in understanding and embedding those needs, rather than mapping them onto a common control framework.
Going through it made Cloudflare more global, not less. It pushed us to think carefully about what it means to serve users in a specific local context, with local language, local consent expectations, and local data protection requirements, and to put that into how the product behaves rather than only into a document.
That is consistent with what we are working toward: helping build a better Internet for everyone, not just in the regions where regulatory requirements are straightforward, but everywhere.
To learn more about Cloudflare's compliance and assurance programs, visit our Trust Hub.
The legal disputes between Germany’s largest software company, SAP, and the Munich-based process mining specialist Celonis took another turn last week. After the German Federal Cartel Office most recently dismissed a complaint filed by Celonis in July, the Munich I Regional Court ruled entirely in favor of Celonis in a case regarding the infringement of a European patent held by Celonis.
Case No. 7 O 12849/25 concerned patent EP 3 139 274 B1 describing a method for determining a net lead time between process steps using process data stored in a structured manner in main memory (in-memory).
Celonis had filed a lawsuit alleging that the patent was infringed by a feature of the SAP Signavio Process Intelligence software solution — SAP acquired Celonis’s rival Signavio in March 2021.
The court ruling prohibits SAP from offering the patent-protected method in Germany or using it itself. SAP must also provide Celonis with information regarding the extent to which it has infringed the patent since April 22, 2020, including details on:
In addition, SAP must provide a transparent account of the extent of the patent infringements based on its financial figures. The company is obligated to pay appropriate compensation or damages.
“The ruling by the Munich Regional Court confirms our legal position: SAP Signavio’s technology infringes on Celonis’s patent rights. We consistently protect our intellectual property and remain committed to fair competition,” explained a Celonis spokesperson.
SAP, however, points out that the court ruling pertains to a single, specific feature within SAP Signavio Process Intelligence, not to the product as a whole. SAP Signavio Process Intelligence remains available to customers, according to a company spokesperson.
The spokesperson also dismissed concerns that the ruling could hinder companies’ migration to SAP S/4HANA Cloud. Migrations to SAP S/4HANA Cloud are not affected by this, he said. SAP is working to ensure that there are no disruptions for its customers.
The concern is not entirely unfounded: SAP Signavio is part of Rise with SAP, a SaaS solution from the Walldorf-based company designed to support migration to the S/4HANA Cloud. SAP Signavio’s process mining tools are designed to provide insight into actual process flows and identify inefficiencies and bottlenecks.
The Regional Court’s ruling does not mean the matter is by any means settled: As the spokesperson for the Walldorf-based software giant explained, SAP does not share the Munich court’s legal opinion and will file an appeal against the ruling. In addition, SAP has challenged the validity of the patent in question before the Federal Patent Court.
“SAP’s top priority is to ensure that customers are not affected by this. All other issues will be resolved through the appropriate legal channels,” said the spokesperson for the Walldorf-based company.
This article first appeared on Computerwoche on Oct. 13, 2026.
AI agents expose gaps in enterprise access controls and audit trails. Here's how security leaders can rethink identity, data governance, and oversight.
The post Your Security Stack Knows Who Logged In. But Does It Know What AI Agents Do Next? appeared first on TechRepublic.
Regulated industries have been dealing with the equivalent of sovereign data for a long time. And as the geopolitical situation makes it more broadly relevant, it doesn’t make it any easier to deal with.
From concerns about the reach of the US CLOUD Act and what telemetry or sensitive business data gen AI models might collect, to implications of the US government taking part ownership of a range of technology companies and the impact of EU regulations, the state of the world means more organizations need to think about where data is located.
The result is a flood of announcements from hyperscalers about new EU cloud regions, as well as pitches from regional and private cloud providers. The promised sovereignty may be anything from a local availability zone to more sophisticated approaches to ownership structure, compliance frameworks, where logs are stored, or where support staff work.
Actual data sovereignty involves legal, technical, contractual, governance, and infrastructure questions, but all too often, what’s on offer is what IDC research director Rahiel Nasir calls sovereignty washing. “When you look under the lid, all they’re really offering is a solution for data residency and data localization, keeping data in country,” he says. “That’s part of sovereignty, but not all of sovereignty.”
In his experience, in-country data centers are the first thing organizations ask for to support data localization and data residency, but they also require enhanced controls over identity and access management. That’s critical because data sovereignty is as much about who has access to the data and why, as where it lives.
“It’s really important the only people who touch my data in what is supposedly a sovereign cloud environment are those I give permission to,” he adds. “Because it’s my data, and I’m the only one who can give the authority to grant access to it. That also applies to support and admin staff.”
Companies want control through where they store data but also to restrict how users can interact with it that might expose that information outside an approved environment or jurisdiction, adds Acceldata SVP Ali Afsar.
Don’t confuse the regulatory requirements of data residency with data sovereignty, Scality CMO Paul Speciale warns. “Residency is about geography,” he says. “Sovereignty is about control, jurisdiction, and who ultimately has the legal authority to access data.”
For CIOs, the question is no longer simply where the data is but who can access it, who controls the encryption keys, under which legal framework it operates, and can that control be proven. That includes being able to show who accesses data, from where, and for what purpose, which requires verifiable controls like jurisdiction-aware data placement, immutable backups, tightly governed admin access, and clear audit trails.
The UK government’s recent call for evidence on the impact of international data flows on sovereignty makes this explicit, referring to transfer by access where personal data remains in the UK but is accessed from overseas, including by a user located in another country. Access transfers include administrative access, backups, disaster recovery, support incidents and sometimes — depending on the specific regulations — processing the data.
GDPR doesn’t mean data has to stay in the EU but it does require data to be protected to EU standards wherever it goes. Data transfer obligations for other jurisdictions can be far more restrictive, so multinational organizations may need access controls limiting who can see what regulated data from different locations.
RBI-regulated payment-system data, for instance, must be stored in India, but can be processed outside India, Afsar explains, as long as it’s deleted from overseas systems within 24 hours. And with limited exceptions, personal data in Saudi Arabia must be processed within the Kingdom, and China treats overseas access to some categories of data stored in China as a cross-border data activity. Russian laws require similar strict data localization, and personal data of Russian citizens has to be stored, processed, and kept within the country’s borders at all times, which is why LinkedIn was blocked there.
Elsewhere, regulations are most restrictive for specific markets like healthcare, financial, and public services. Not everything needs to be transferred to a sovereign cloud, Nasir points out, as use of that data is subject to regulatory compliance, and the increasing need for AI training.
“This is the data that’s going to have catastrophic business impacts if leaked,” he says. “To give enhanced controls and security for that data, you’d consider wrapping sovereign controls around it. Everything else not subject to compliance nor sensitive data can be accessed by whomever you want and from wherever.”
Organizations typically know data sovereignty rules well but still experience incidents like data breaches, government data access requests, and unauthorized cross-border transfers caused by, for example, traveling employees or excessive admin access, according to Kiteworks’ 2026 Data Security and Compliance Risk report.
“Location only tells a regulator where the data rests, not who can still reach it,” says Kiteworks’ EMEA GM Dario Perfettibile. “Every real exposure we’ve seen so far happens through access not geography.”
Thinking data needs to stay in region because then it’s safe gives a false sense of security if practiced as a substitute for proper data management. Access, data labelling, and retention polices take more work but are what can prevent incidents. “If you have a data policy in place, it can force a reapproval of the access,” he adds. “It can restrict access to you only, or it can block you out immediately.”
Using a service closer to home doesn’t automatically make any of that easier. “Many organizations still assume sovereignty can be achieved by moving data from one cloud provider to another, or by replacing one hyperscaler with another,” says Keepit Group CISO Kim Larsen. “That misses the bigger picture.” CIOs should treat sovereignty as an operational capability not a compliance exercise, he adds, since sovereignty isn’t about scale or ownership of infrastructure for its own sake, but maintaining control.
“If an organization doesn’t know who can access its data, which legal frameworks govern that access, or whether it can recover its data independently, simply changing where the servers are located does little to reduce risk,” he says.
Just because something is based in your region doesn’t automatically make it a good choice. The EC, for instance, has set up accounts on W Social, an independent social media platform based on the AT protocol designed for data mobility and user migration, which Bluesky uses but is hosted in Europe.
The Commission’s own open source strategy suggests open source promises more control over digital infrastructure by avoiding vendor lock in, and a recent policy brief positions digital sovereignty as a form of digital independence. But having servers in the EU isn’t the same as freedom of digital movement since unlike Eurosky, based in Europe and using the same protocol, W limits interoperability so it can require identity verification, and has closed its source code after security researchers pointed out vulnerabilities.
Most organizations will continue to use both global and local providers, though they might prioritize what Nasir called glocal options built on partnerships between the two. “Organizations want to use a mixture of local and global providers,” he says. “They want all the innovation capabilities that the Microsofts, AWSs, and Googles of the world give us, that they consider local providers can’t match.”
IDC figures suggest only 4% of European organizations plan to switch to purely local options. “We can’t live without US technology today and there’s no appetite to do that,” says Nasir. Availability matters and local providers may not have the same level of infrastructure as global options. They can offer low hanging fruit like video conferencing solutions, but not more complicated directory and database services, or productivity software that’s intertwined with those US-provided services.
Choices about where to store data, and the technical controls to enforce that, have their own operational implications.
“Redundancy and resiliency are key tenets of sovereignty,” he adds. “You want to make sure your operations are always available. In order to enable that, you want to spread the risk.”
For the past half century or more, the teams running enterprise software stacks have nurtured a vast ecosystem of tools to keep software humming along. They’ve built CI/CD pipelines, elaborate test suites, code repositories, and tools galore, all with the goal of keeping the systems up and running.
Now AI is throwing a wrench into the whole endeavor. Software is now more complex and sometimes mysteriously unpredictable. Expectations are sky high, but no one is certain what to expect in good conscience.
Luckily, dozens of companies are rushing to build new tools designed to keep agentic stacks on the straight and narrow, delivering value to everyone. The field is rapidly evolving, probably having changed since you started reading this article.
Some of the tools involved in the emerging agent stack aren’t that different from what enterprise teams already have in store. In the end, LLMs are just piles of bits that need to be loaded into a processing chip, just like old-fashioned software. Many of the old tools that watch for overloaded nodes or overpacked disk drives are just as valuable as ever, perhaps more so because LLMs chew through storage even faster. And some of the companies tackling these problems are the same steadfast suppliers who have earned the trust of your DevOps teams; they’ve just extended their own offerings to handle LLMs and AI.
Other challenges, however, are quite different. For example, LLMs are terrifyingly non-deterministic, a real challenge for belts-and-suspenders engineers who traditionally tend the software. Tool vendors are building entirely new systems to handle these somewhat random deviations so that traditional DevOps teams — and their C-suites — don’t have heart attacks.
The field is also rapidly expanding in wildly divergent ways. Some vendors are building tools for developers who are creating new LLMs. Others are concentrating on the challenges that come from worrying about an LLM, day in and day out, in large scale production.
We’ve compiled lists introducing the most intriguing companies developing tools for this rapidly altering space, including tools aimed at AI orchestration; AI observability, aka AgentOps; AI evaluation and benchmarking; and AI trust, guardrail, and governance. We’ve even thrown in some vibe-coding tools for citizen development and AI workflow tools for business processes.
While it was relatively easy to split the field into distinct lists, that process will only grow more challenging because the tools — and categories — are starting to overlap. As vendors evolve their strategies, this overlap will grow further, with a variety of entries tackling a wider range of challenges, vying for a greater percentage of CIOs’ AI middleware and operational budgets.
To help you make sense of this complex tool landscape, here are the most common categories vendors are using to identify what their products do, each of which maps to what are becoming the key components IT needs to keep their AI and agentic stacks productive and humming.
Vendors often use the term “observability” to refer to the most basic of data collection work — that is, testing to make sure the various machines are running, the RAM isn’t too full, latency is acceptable, and the logs aren’t filled with error codes.
Watching these metrics isn’t much different from caring for an old-school collection of microservices, and often the tools aren’t much different, either. Many of the most popular tools are the same dominant market leaders that have been extended to collect data from the various GPUs, too.
Leading vendors: DataDog, Dynatrace, New Relic, Splunk
Upstarts: Ariz, LangSmith, Braintrust, Galileo
Open-source alternatives: OpenTelemetry, Phoenix, Langfuse
Many AI pipelines are often more complex than regular microservice architectures, and that means they need someone to carefully watch the bill. Plus, as attention to AI ROI rises, capturing spend is essential — especially given how quickly AI tokens can add up.
Cost engineering tools can integrate information from various portals like OpenRouter and compare it against internal hardware. Sometimes breaking down these comparisons is difficult because the right way to allocate costs to each user isn’t as obvious, even though they’re often just one number. These accounting operations tools will become even more important as LLM bills grow.
Leading vendors: CloudZero, Finout
Upstarts: Amnic, Bifrost, Portkey
Open-source alternatives: OpenCost, Langfuse
When metrics and telemetry begin to focus on the LLM, the word “AgentOps” starts to appear. It’s just like DevOps but it’s concerned with watching token counts, tracking the performance of RAG databases, and collecting traces for debugging purposes.
When the work is truly agentic, AgentOps must also juggle the state that agents generate while looping through their various activities. Agents aren’t just a one-and-done call to an LLM. They’re software packages that need to store information as they work toward a final answer.
This job of an AgentsOps team gets trickier because these areas are where the models often behave non-deterministically. Is some model hallucinating? Are an agent’s prompt chains running to completion? The tools in this space track all these metrics, often in a dashboard with nice graphs that make problems stand out.
Leading vendors: Databricks, Datadog, Dynatrace
Upstarts: Arize, Braintrust, Comet
Open-source alternatives: Langfus, LlamaIndex
The buzzword “evaluation” starts to appear alongside tools that are used in the earlier stages of development, when various models and prompt combinations need to be tested again and again.
In many cases, these tools use another model to evaluate the quality of the answer from the first model, as well as to keep an eye out for potential hallucinations or other failures. In some cases, the tools query humans who sit in the evaluation loop to give their opinions of how well the model is performing. Good tools can watch the agents continuously and reroute any sketchy behavior to the human-in-the-loop.
Many of the vendors use the word “evaluation” to describe measuring just how well a model is performing for a particular business application. That is, how well it’s working for what your boss wants it to do.
Leading vendors: Databricks, SuperAnnotate, Scale AI
Upstarts: Braintrust, Galileo AI, MaximAI
Open-source alternatives: Langfuse, Prompfoo, Tagas
The word “benchmarking” is similar to “evaluation” in AI vendor literature, but it is usually found more in the tools used by the creators of the models. There are a number of public benchmarks filled with standard queries, and the model developers rank themselves on how well they do solving these problems. This often generates a raw score that is then compared to another’s raw number. Some teams create their own benchmarking problem sets and use them during evaluation to assess how well models might meet their needs.
Leading vendors: Hugging Face, Databricks
Upstarts: Reka AI, Patronus AI
Open-source alternatives: Promptfoo, DeepEval
The tools that wear the “trust” benchmark are often meant to help evaluate how well a model is protecting the needs of any business that is deploying it. That is, can they trust it to deliver accurate and useful answers without hallucinations, data leakage, inappropriate behavior, or worse? Prompts with malicious instructions are especially tricky to detect. Some enterprises want a trust score that measures the consistency of the answers. Overall, tools that target the “trust” metric are often utilized more during development and early deployment.
Leading vendors: Azure AI Content Safety, Bedrock Guardrails, Vertex AI Search
Upstarts: Patronus AI, Arthur AI
Open-source alternatives: NeMo Guardrails, Llama Guard
The word “guardrails” is usually applied to tools that are part of the deployment stack. That is, they sit as watchdogs and make sure the LLM doesn’t spin out of control. They also ensure the model is trustworthy, but they’re more tuned to operating in real-time than those aimed at trust, as outlined above.
These tools are often filled with fixed rules, such as scanning for social security numbers or watching for noxious words. The challenges get trickier because agents are executing software, and that means the guardrails must do more than analyze outputs. They also need to manage the execution environment, often running in a sandbox, and watch for exploits and other malicious behavior. They need to validate and double-check not just code, but the OS-level commands for manipulating files and processes.
Leading vendors: Azure AI Content Safety, Bedrock Guardrails, Vertex AI Search
Upstarts: Patronus AI, Arthur AI
Open-source alternatives: NeMo Guardrails, Llama Guard
Many systems rely on a vector database to store embedded data to chunks of trustworthy documents. These RAG databases need much of the same care as regular databases, and the tools for their care are often similar. PostgreSQL, for example, has a vector addition that needs the same kind of scrutiny from a database administrator as a regular PostgreSQL database.
Leading vendors: MongoDB, Elasticsearch
Upstarts: Pinecone, Weaviate
Open-source alternatives: Milvus, PostgreSQL
Increasingly, AI systems employ models in constellations, and a gateway router is what examines a prompt to determine which model or agent is best for answering the query. Moreover, as agents undertake their work, the router can distribute the agent’s various subcalls to the fastest, cheapest, or most accurate LLM or subagent.
Watching over this stage in the pipeline requires a different set of intelligence because the questions can often involve both applicability and cost. Sometimes this layer must balance the extra cost versus the need for a better answer.
Leading vendors: Cloudflare, AWS, Google Cloud, Azure
Upstarts: OpenRouter, ModelsLab, Respan
Open-source alternatives: LangChain, Bifrost, LiteLLM
Who gets to use the model? Who is paying? Many access control tools are the same ones that were part of standard APIs or web services. Is there an API key? Is the account below its budget? The tools watch for overspending because both the customer and the boss want to make sure the money keeps flowing and no tokens are wasted.
Leading vendors: Auth0, Apigee
Upstarts: Amnic, Portfoundry
Open-source alternatives: LiteLLM, Bifrost
Some industries have explicit compliance requirements dictated by law. Some have their own internal controls. Tools devoted to compliance are often a subset of the ones devoted to guardrails. But they’re often treated separately from guardrail tools because they’re more likely to be of interest to lawyers and that makes the stakes higher.
Leading vendors: ServiceNow, IBM
Upstarts: VerifyWise, Norm AI
Open-source alternatives: Aether, Giskard
A reported leak of 13,000 screenshots shows how AI agents can bypass weak approval and audit controls even when organizations have written policies.
The post AI Agents Leaked 13,000 Screenshots: Why Enterprise Approval Controls Failed appeared first on TechRepublic.
Alternative clouds have emerged amid major cloud providers such as AWS, Google Cloud, and Microsoft Azure, and often specialize in niche areas like AI-native computing, and sovereign and edge deployments, while professing to provide cost reductions and best-of-breed performance.
“Many organizations are rebalancing away from all-in hyperscaler strategies to avoid lock-in and concentration risk,” says Kyle Campos, CTPO at CloudBolt, a cloud management platform. “At the same time, alternative clouds are often purpose-built for specific advantages.” To him, benefits include lower-cost object storage at scale, better edge performance for latency-sensitive apps, and faster access to dedicated GPUs for AI workloads. Data sovereignty is also pushing adoption of localized providers.
But as alternative clouds, also called neoclouds, make headlines and amass considerable funding rounds, their use in enterprise environments remains relatively nascent. While enterprise executives see the potential in using alternative clouds, especially for GPU workloads, many are skeptical, taking a balanced approach to assessing maturity, costs, and whether it’s worth sacrificing continuity with existing clouds.
Smartsheet CIO and CISO Ravi Soin is one of these executives taking a measured approach. “We’ll grow our use of alternative clouds, but within a clearly defined perimeter,” he says. “That discipline is what separates considered adoption from sprawl.” For Soin, many neoclouds still fail early in the evaluation process, especially for regulated workloads where a mature compliance posture is non-negotiable.
Cloud Computing Survey
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In order to fully evaluate alternative clouds, the platforms must be treated with the same vigilance as any other IT acquisition. “This remains consistent across any tech stack: fit, form, and function,” says Nigel Gibbons, director and senior advisor at the NCC Group, a cybersecurity consulting firm. “This means alignment of the cloud to workload performance, security, and sovereignty needs.”
Overall, CIOs aren’t rushing into alternative clouds. It’ll take a serious proof spanning regulatory impact, auditability, resilience, and total cost planning in order to convince large organizations to migrate away from well-established cloud infrastructure. More realistically, such clouds will be evaluated on a per-workload basis.
When evaluating neoclouds, compliance is top of mind for enterprise executives. “Compliance posture such as SOC 2, ISO 27001, and sovereign-specific certifications like FedRAMP or IRAP is the first filter and, for most neoclouds, an early exit,” says Soin.
Smartsheet runs AI on enterprise customer data and therefore requires strict compliance and sovereignty frameworks. “That defines a hard boundary where regulated workloads stay with certified providers,” he adds. “Workload identity doesn’t federate natively across clouds, so every trust relationship must be hand-built and audited. For a platform where data sensitivity varies enormously, that governance gap isn’t theoretical.”
Gibbons adds that trust validation is becoming a pressing requirement from regulators and the overall market. “The uncomfortable truth is that most organizations have operated on deferred risk captured in registers, softened in board narratives, and tolerated due to limited visibility,” he says. The pattern of tumultuous changes in the AI market, he adds, is encouraging more of a resilience mindset among technical executives assessing new technologies.
Operational transparency is another pressing area to evaluate. For Soin, the infrastructure that supports AI workloads requires granular auditability. “Can the provider give you end-to-end observability across the inference layer: tamper-evident logs, model versioning, the ability to trace what happened to customer data from input to output?” he asks.
Smartsheet’s enterprise customers also ask how AI is applied to their data and what controls exist, and that answer has to be defensible. “A neocloud that can’t support it isn’t just an operations risk, it’s a risk to the customer trust our business is built on,” he says.
Although neoclouds are often framed as a replacement to hyperscalers, they’re more often complementary infrastructure, purpose-built for individual use cases. “A neocloud isn’t a type of cloud, but more a design principle,” says Gibbons. “We can think of it as infrastructure optimized for a specific workload, trust model or control requirement, rather than general-purpose scale.”
Their usage hinges on the project at hand, which typically involves AI/ML projects. “We work with a mix of alternative providers depending on workload fit,” says CloudBolt’s Campos. “We’ve used alternative cloud providers for VMware as part of a cloud migration strategy.” Their customers use alternative clouds for object storage, edge and low-latency needs, AI/ML GPU capacity, and legacy virtualization workloads that don’t map cleanly to hyperscaler-native services.
Cloud Computing Survey
Foundry
Executives must determine which environment makes sense for the workload at hand, and act accordingly. “CIOs should begin by clarifying the specific workload opportunity an alternative cloud is meant to accelerate, then evaluate providers against developer and operator experience inclusive of ability to scale with business need,” adds Campos. “From there, the priorities are whether the platform can be governed and operated alongside existing clouds, with strong visibility into usage and unit economics. Security, compliance posture, and credible SLAs for reliability and performance should be evaluated at the same bar as hyperscalers. The goal is to add flexibility without creating a new operational silo.”
Not all workloads are a fit for neoclouds or alternative providers, however. While these platforms benefit numerous workload-specific options, they’re not viewed as wholesale replacements for hyperscalers. For general-purpose enterprise functions, hyperscalers may still retain advantages around integrated services, discounts, operational maturity, and the availability of relevant job skills.
For this reason, many technology leaders are still in an exploratory phase. “Our infrastructure today runs on hyperscalers, and that’s been the right choice for where we’ve been,” says Smit Shanker, global CIO of Xebia, a global IT consulting and software engineering company. Still, he encourages CIOs to begin actively evaluating alternatives. “We’re now in that evaluation phase, looking at where specialized providers, sovereign options, or hybrid approaches make more sense for specific workloads.”
CIOs require a high-degree of enterprise-grade trust that must be codified beyond empty promises and proven under real-world stress tests. As such, before diving headfirst into a newfangled cloud, Smartsheet’s Soin advocates verifying its shared responsibility model, which stipulates commitments the cloud provider has to uphold, and where responsibility lies with consumers.
For Soin, it’s especially critical to understand how a cloud provider acts when incidents occur. “Request post-incident reviews before signing anything, not templated RCAs but the real communication timeline,” he says. “Shared responsibility models are well-documented until they’re tested. Find out what happened the last time they were tested.”
Ultimately, alternative clouds need to meet the same enterprise maturity bar as established cloud providers. “Assurances must include auditability, compliance, resilience, transparent SLAs, interoperability, portability, and independently validated trust, not vendor assertions,” says NCC Group’s Gibbons.
Understanding the economic impact is necessary to determine whether an alternative cloud is worth it for the business. This is an area where alternative clouds shouldshine, with reports estimating savings of up to 70% compared with hyperscaler GPU instances. Traditional cloud computing pricing models are often opaque, and charges related to add-ons, upsells, and hidden fees around egress and ingress are notoriously known to surprise cloud computing consumers.
For certain workload categories, the economics can favor alternative clouds. “Traditional cloud providers often impose substantial data egress fees that inflate the total cost of ownership for data-heavy architectures,” says Dave McCarthy, VP of cloud and infrastructure services at global market intelligence and advisory firm IDC. “Alternative providers frequently minimize or eliminate these bandwidth penalties entirely, offering a more transparent cost structure,” he says.
Still, a full cost audit is necessary before going all-in on an alternative cloud. “What I’d recommend to anyone is do the full-cost model before you commit,” says Shanker. He suggests conducting a comprehensive analysis of cloud compute, inference, API volumes, and maintenance costs for things like infrastructure upgrades projected against the actual demand curve. When viewed together, he says, they create compounding costs that most C-suites haven’t modeled.
“Most enterprises are still modeling cloud economics on implementation costs alone, and that’s incomplete,” he adds. “The organizations getting AI right are the ones treating infrastructure economics as a first-class design decision, not a footnote.”
As cloud infrastructure choices can produce vendor lock-in, CIOs should use all the criteria at their disposal to plan and inform a neutral decision-making process. “Whatever path you choose — hyperscaler, alternative, sovereign, or some combination — the discipline that matters is vendor-agnostic, framework-led design,” adds Shanker. “Don’t let infrastructure choices constrain what’s possible.”
Neoclouds have made a mark for themselves by offering direct access to latest-generation hardware, which is important for AI-focused workloads requiring high performance. There’s also the argument that opting for alternative clouds aids a distributed multi-cloud strategy, which can benefit resilience and meet certain regional sovereign cloud mandates.
Nearly 90% of IT leaders say an organization should never commit to one cloud provider for their entire architecture, according to a HostingAdvice survey from last year. The same study found 73% of leaders use two or more alternative cloud providers, underscoring a clear interest in alternative clouds.
Still, while some industry reports are favorable, enterprise executives express more of a cautious reality of selective evaluation, not wholesale migration. For Soin, a top concern is the compliance posture and observability capabilities for alternative clouds, especially when hosting workloads that run AI inference. “The question isn’t just where inference happens but whether we can see what happened, explain it, and stand behind it,” he says. “That obligation shapes which providers are even in the conversation.”
While state-of-the-art cheap GPU compute is alluring, CIOs should keep an eye on the full governance picture when evaluating alternative clouds. “The neoclouds that earn more of our workload won’t just be the ones with the best GPUs,” says Soin. “They’ll be the ones that have seriously invested in model governance infrastructure and can demonstrate it. That’s a higher bar than most currently clear, but it’s where the market needs to go.”
IDC forecasts that by next year, the computational demands of AI will force 80% of organizations to modernize legacy cloud environments by switching to platforms designed for AI workloads, with half of this being processed locally on endpoints or edge nodes by 2030.
“Enterprises are increasingly looking beyond major hyperscalers to avoid vendor lock-in and optimize specialized workloads,” says IDC’s McCarthy. “Rather than relying on a single, centralized infrastructure, organizations are adopting these alternatives into a broader portfolio.”
Much of this new computing paradigm will center on inference, or the post-training execution of AI models in production, using live customer or enterprise data. As inference moves into more business-critical workflows, decisions about where those workloads run, and what criteria guide those decisions, will have long-term implications.
Alt and neo clouds will likely have their place in inference, as well as in future sovereign and decentralized cloud models, and it’s not a decision CIOs should take lightly or without an informed evaluation framework. “Where workloads run becomes one of the most consequential decisions a leader makes,” says Shanker.
Researchers found that seven of nine tested Hugging Face image-editing tools produced sexualized alterations, highlighting gaps in model oversight, provenance, and enterprise vendor controls.
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framework · compliance & lgpd
Estrutura em 8 pilares para construir (ou auditar) um programa de compliance com a LGPD, do mapeamento de dados até a cultura contínua. Marque o progresso por área ou processo avaliado.
Este framework organiza a metodologia de um programa de compliance com a LGPD, mas não substitui a avaliação de um advogado ou DPO qualificado para o seu caso concreto — cada setor e modelo de negócio tem nuances específicas.
Antes de se proteger, é essencial saber que golpes digitais exploram pressa, distração e confiança. Criminosos usam mensagens falsas, sites clonados e engenharia social para roubar dados e dinheiro.
Passe o mouse sobre o link antes de clicar — veja se o endereço parece legítimo.
Desconfie de e-mails com erros de ortografia ou domínios estranhos.
Nunca baixe anexos de remetentes desconhecidos.
Habilite o 2FA em redes sociais, bancos e e-mails.
Prefira aplicativos autenticadores (como Microsoft Authenticator ou Google Authenticator) em vez de SMS.
Isso bloqueia invasões mesmo que alguém descubra sua senha.
Golpistas simulam familiares ou empresas pedindo transferências imediatas.
Confirme por telefone ou outro canal antes de enviar dinheiro.
Lembre-se: urgência é sinal de golpe.
Atualizações corrigem falhas que hackers exploram.
Use antivírus confiável e mantenha o firewall ativo.
Evite instalar programas de fontes desconhecidas.
Códigos de verificação são pessoais e temporários.
Nenhum suporte técnico legítimo pedirá esse código.
Compartilhar pode permitir que o golpista acesse sua conta.
Leia blogs confiáveis como osintbrasil.blogspot.com.
Participe de cursos gratuitos sobre segurança cibernética.
Ensine familiares e colegas — proteção é coletiva.
Em um cenário cada vez mais vulnerável a ataques digitais, proteger dados e sistemas deixou de ser opcional — é uma necessidade estratégica. Contratar um profissional de segurança da informação garante que sua empresa esteja preparada para prevenir, detectar e responder a ameaças cibernéticas com eficiência. Esse especialista implementa políticas de proteção, monitora vulnerabilidades e assegura conformidade com normas como LGPD e ISO 27001. Investir em segurança é investir na continuidade e credibilidade do seu negócio.
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