I made the bold prediction that 2025 would become the year of the enterprise browser following Black Hat USA earlier this year. In that Forbes contribution, I did not call a winner. Rather, I highlighted a handful of companies that I judged to be leading the pack and warranting consideration. In this follow up piece, I will dive deeper into one of those solution providers, Mammoth Cyber, and share my insights after spending time with co-founder and chief executive Michael Shieh.

Modern AI’s Blind Spot

Modern AI, both generative and emerging agentic frameworks, are transforming enterprise workflows by automating tasks, delivering insights, enhancing productivity, and accelerating decision-making. However, the pressing challenge is that most AI models remain blind to what is happening inside of a business. If you ask an AI agent for help with a customer issue, it will likely provide formulaic responses. It lacks insight into important business context, such as contract terms, support ticket history, CRM records, user roles, and other business metrics.

Mammoth Cyber’s AI browser attempts to close that gap by feeding real-time enterprise context, allowing AI to reason and learn with awareness of the actual business state. The potential is the ability to move beyond providing theoretical advice to facilitating actionable execution through dynamic policy control, AI workflow management, situation report generation, data leakage mitigation, and more. Most importantly, what Mammoth Cyber is unlocking is the ability to guardrail AI usage and prevent harmful user behavior.

The Need for Guardrails

Modern AI is quickly revolutionizing the way knowledge workers transact business. However, without the proper guardrails in place, organizations open themselves to catastrophic risks from a compliance standpoint. These tools require access to critical and sensitive information including CRM systems, customer personal identifiable information, intellectual property, and financial records. Consequently, ensuring safe and secure access is paramount – especially within highly regulated industries such as healthcare and financial services and the need to comply with the European Union’s GDPR mandate. 

Mammoth Cyber’s architecture addresses these needs, enforcing context-aware, real-time controls. Every AI action is validated against policy constructs, weighs data sensitivity, and validates usage dynamically against business rules and context. In essence, nothing is allowed to run free in the wild of IT infrastructure. Mammoth Cyber positions itself as a controlled intermediary, supporting safe and secure powerful AI-driven workflows while locking down what is required. That is a challenging task, one that developers often struggle to achieve.

Mammoth Cyber’s Architectural Approach

Mammoth Cyber’s architectural approach makes the browser itself the AI enforcement point. It deeply leans into real-time context, ingesting data such as open support tickets, business transactions, and employee interactions. It leverages this critical context to adapt security posture dynamically, and uses data loss prevention techniques to prevent data leakage and mask PII while enforcing zero trust access.

Mammoth Cyber claims that its architecture is model-agnostic, providing organizations with the flexibility to choose public or private LLMs. That is an important consideration given the expected plethora of bespoke models that will be fine-tuned to specific industry applications supported by private data. The company also supports pooling of tokens to optimize AI operational cost and delivers a simplified deployment experience with centralized policy control, including the ability to monitor shadow AI usage and block troublesome prompt injection out of the box.

Unlocking Organizational Efficiency

With Mammoth Cyber’s AI control layer in place, enterprises can empower themselves to do things that were previously deemed too risky. A salesperson can prepare a highly tailored customer proposal that leverages information from multiple internal systems without risk. A support agent can resolve a trouble ticket guided by AI, pulling insights from contracts, logs, and past interaction data. An internal workflow such as a new employee or customer onboarding can be automated by AI while ensuring compliance at every step. Finance or compliance teams can generate reports automatically with built in masking and audit trails within the browser.

The potential is limitless, but these tasks require a balance of security, usability, and control. Flexibility is key. There is often friction associated with the adoption of new security tools because they require a rip-and-replace or bolt-on approach that diminishes security outcomes. Mammoth Cyber’s approach is decidedly more pragmatic. Its licensing is customizable, and it supports a myriad of identity and single sign on controls from Google, Microsoft Entra, Okta, Ping, and others while interoperating with existing firewalls and endpoint security solutions.

Final Thoughts

I like what Mammoth Cyber is doing to reimagine the enterprise browser in the modern AI era. The company is a relatively unknown entrant, and it will need to prove its value through adoption. However, I believe that its grounds up design that combines dynamic policy control, business context and zero trust access is powerful. That makes it one to watch in an emerging category.