Zoho Corporation, a global technology company, today announced major enhancements to Catalyst by Zoho, its Platform-as-a-Service (PaaS), now weaving agentic development capabilities directly into the coding environments developers already use. Additions include Agent Skills, a non-interactive command-line interface (CLI), and Model Context Protocol (MCP) support to Catalyst’s platform, along with new integrations for agentic AI coding assistants including Anthropic’s Claude Code and OpenAI’s Codex. To enhance accessibility and empower future developers, the platform is also offering a free student program that includes full-stack hosting, functions, database, and AI tooling.
Catalyst by Zoho bridges the gap between code generation and reliable deployment by giving agentic AI coding assistants a structured, deterministic way to build and deploy applications. Developers can use the AI coding assistants of their choice while Catalyst provides the underlying full-stack serverless infrastructure and controls, eliminating the need to stitch together multiple cloud services and vendors. This approach simplifies development and future iterations while reducing operational complexity,positioning Catalyst as a reliable partner as technical capabilities and customer needs evolve.
Turning AI-Generated Code Into Production-Ready Applications
AI coding assistants can generate code quickly, but getting it to production requires deep platform knowledge, cloud services, and deployment workflows. Catalyst brings these together on a single serverless full-stack cloud, offering AI coding assistants what they need to build, test, and deploy applications. These capabilities make this possible:
Catalyst Agent Skills gives coding assistants the context they need to understand Catalyst services, architecture, and recommended development patterns. Rather than relying on the model to determine how Catalyst should be used, the Skill guides the assistant toward the appropriate capabilities and workflows. By surfacing only the capabilities relevant to the task, they help assistants make the right application and service choices, optimize token use, and generate accurate, verified output even with lighter models.
The non-interactive CLI allows AI coding assistants to execute multi-step workflows in Catalyst from start to finish without requiring human input at every step. This reduces manual intervention and helps developers move faster from coding to deployment.
The Catalyst MCP server provides AI coding assistants direct access to Catalyst capabilities from the developer’s existing environment. Actions such as creating a database table or adding a column can be performed directly from VS Code, Claude Code, Cursor, or any AI IDE without switching to the Catalyst console, keeping development in one workflow and accelerating delivery.
Orchestration, built into the Skill, ties the three capabilities together. When an AI coding assistant faces a decision about how to execute a request, the Skill routes it deterministically down the CLI or MCP path rather than leaving that choice to the model. This approach lowers the developer’s cognitive load, reduces the risk of incorrect tool selection, and helps produce more reliable, production-ready applications.
Built on Zoho’s Platform with Humans in Mind
While each service may work well independently, managing a fragmented stack can add operational complexity and make security, privacy, and governance harder to maintain. Applications built on Catalyst run inside Zoho’s own data centers and inherit Zoho’s robust security infrastructure, including DDoS protection, SOC compliance, regular vulnerability assessment and penetration testing (VAPT), a web application firewall, and more.
Human oversight is built into the deployment process rather than added afterward, giving organizations greater control as AI becomes part of application development:
Decoupled environments keep development and production separate. Code moves to production by manual promotion only—ensuring the AI agent never touches production, eliminating the risk for error.
Scoped collaborator controls define who—or what—can participate in development and what actions they can perform.
Full audit trails provide records to assist with oversight, including application logs, platform logs and MCP tool-call logs. From this data, developers can track precisely what actions the AI agent took, and when. Every change after launch is versioned, attributable, and reversible.
What’s Next
Catalyst is advancing towards a new era of agentic software development, where developers can collaborate with increasingly capable AI agents to execute sophisticated workflows across the software development lifecycle—all on a governed, full-stack cloud foundation. Forthcoming changes include multi-agent hosting, AI tool connectors, agentic SDLC, and more.
Disclaimer: All trademarks, product names, and company names cited herein are the property of their respective owners.
Pricing and Availability
Catalyst by Zoho offers a monthly free tier for developers to explore the platform, plus $250 in free credits for users who want to go deeper over a six-month period. Catalyst is available for immediate use.
Catalyst continues to offer a straightforward pay-as-you-go pricing model, with every feature bearing a per-unit cost rather than a license fee layered on top of usage. Developers get full visibility into usage from the Catalyst console and can set budget alerts and ceilings to prevent unexpected bills. A structured subscription option is also available for teams that prefer predictable costs.
Catalyst remains completely free for students, no subscription or credit card required to deploy non-commercial applications.
Zoho’s Privacy Pledge
Zoho respects user privacy and does not run on an ad-revenue model in any part of its business, including its free products. The company owns and operates its own data centers, giving it full oversight of customer data privacy and security. More than 150 million users worldwide, across more than 1 million paying organizations, rely on Zoho to run their businesses, including Zoho itself. For more information, visit zoho.com/privacy-commitment.html.
Anthropic’s new enterprise safeguards only cover one piece of a company’s AI stack
Posted in Commentary on September 2, 2026 by itnerdAnthropic just rolled out Enterprise Frontier Safeguards, giving enterprise customers zero data retention, customer-managed encryption keys, and misuse monitoring that routes flags to the customer’s own review team instead of Anthropic’s, built with input from over 100 customers including Goldman Sachs, Citi, and Wells Fargo, and it comes right after Anthropic disclosed that Claude Mythos 5 took unauthorized action against real people and organizations once it was given live internet access during testing without safeguards.
Arti Raman, CEO, Portal26
“The root cause Anthropic identified is the most interesting part of this. Claude Mythos 5 was told its environment was simulated, then discounted evidence that it actually had live internet access, and acted on that access anyway. That’s a model behaving exactly as designed, in an environment nobody was watching closely enough. It’s the same failure mode we see inside enterprises every day, just at the model layer instead of the employee layer: people, and now agents, will do a lot with access nobody is actively monitoring.
What’s notable about Enterprise Frontier Safeguards is where the flags go. Anthropic is routing misuse detection to the customer’s own review team, not keeping it internal. A vendor watching its own product for misuse is useful, but real governance means the organization actually using the tool can see what’s happening inside it, in their own environment, on their own terms. That’s exactly the gap most companies still have with the AI tools already running inside their organizations today.
This also only covers Claude. Anthropic can protect what happens inside its own model, but most organizations run Claude alongside GPT, Gemini, home-grown agents, and whatever tool an employee signed up for on their own. Enterprise Frontier Safeguards fixes visibility into one instance in a stack that usually has five or six others. Someone still has to be watching every model and every agent running inside the organization, and this only covers one of them.
Zero data retention and customer-managed encryption keys are going to matter most to the banks and healthcare systems on that customer list, because those are the organizations that couldn’t have adopted a tool like this at all without them. But the bigger signal is that even the company building the model needed a live incident, involving real people and organizations, before it built serious monitoring into the product. That’s the pattern everywhere in enterprise AI right now: governance gets built in reaction to an incident instead of ahead of one. The companies that get ahead of that timeline are going to have a real advantage over the ones still finding out what their AI is doing after the fact.”
This is a problem and it is up to Anthropic to answer this problem. Sadly governance is in question. And so is the reactionary nature of this “feature”.
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