White Papers

Governance for Agentic Threats - A Strategic Roadmap

Covasant — Tue, 09 Dec 2025 07:25:02 GMT

Beyond the Hype:
Governance, Not Panic, as the Response to Agentic Threats

A recent attack proved AI agents can accelerate cyber risk. Here is your roadmap for control and resilient defense.

A state-linked group recently demonstrated how an AI agent could be manipulated to autonomously execute over 80% of a cyberattack. This incident was a turning point.

Now, enterprise leaders are caught between two narratives: one that AI builders are telling them, that everything is fine; and the other one that cybersecurity vendors are stressing on, that everything is on fire. This confusion often leads to analysis paralysis. This PoV explains why the real threat isn't AI, but the lack of structure around it.

Download this PoV to learn:

Six concrete steps your security and engineering teams must take now, from limiting agent permissions to strengthening identity governance.
How AI has compressed the cost and speed of an attack, making proper governance a financial and security necessity.
How the shift in attack speed forces you to change your threat model and what the cost of attack means for your budget.
How AI agents can be manipulated and why engineering discipline must replace assumptions about default safety.
How to update governance frameworks, risk registers, and identity controls to reflect agent-driven operations.
How to move away from tracking old threats and instead focus on rapid scanning and monitoring for agent-driven bursts of activity.

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Agentic AI for Fraud Detection and AML Compliance

Covasant — Wed, 03 Dec 2025 09:12:25 GMT

The Key Role of Agentic AI in Fraud Detection & Compliance

Move beyond manual checks. See how autonomous agents detect threats and maintain compliance in real time.

For most enterprises, fraud detection and regulatory compliance are distinct, resource-heavy operations. Security teams react to threats after they appear, while compliance teams scramble to prepare for audits. This disconnected approach leaves gaps that bad actors exploit and regulators penalize.

This white paper outlines how organizations can leverage Agentic AI to unify and automate these critical defenses. We break down a practical, regulator-ready framework for deploying AI agents that flag issues and resolve them proactively. We draw on real-world applications to show you how "always-on" resilience works in practice, moving you from reactive checks to proactive prevention.

Download the White Paper to Learn:

How to move from lag-based response to real-time action, where AI detects and stops attacks the moment they occur.
How automating alignment with major regulatory standards ensures you are audit-ready every day, not just once a year.
The shift from static tools to "pre-built agents" that can execute complex workflows and integrate with your enterprise data layers seamlessly.
How to reduce the setup time for security operations and eliminate costs by replacing task-based manual roles with outcome-based automation.
How to ensure every AI decision is logged, explainable, and free from bias, keeping you compliant with new laws like the Economic Crime and Corporate Transparency Act.

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Data Observability for AI Systems: Free White Paper | Covasant

Covasant — Thu, 21 Aug 2025 12:40:13 GMT

Data Observability:
The Backbone of Reliable AI Systems

Building a strong foundation for data observability helps you identify issues early, maintain data integrity, and create AI systems you can truly trust.

Why Your Enterprise Needs Reliable AI and Analytics

Organizations today face significant challenges managing data quality at every stage of the ML lifecycle. Without data observability, your pipelines are vulnerable to issues like model drift, data quality degradation, pipeline failures, and schema changes that can break production systems.

This white paper provides a practical framework for building scalable, trustworthy AI pipelines with data quality at the core. Download the white paper to learn:

How to implement the 5 pillars of data observability: Freshness, Volume, Distribution, Schema, and Lineage, with practical examples
How to monitor machine learning pipelines for consistent data quality in production
How to detect and prevent model drift, feature instability, and pipeline failures before they impact your business
Best practices for data quality monitoring at scale, with real-world applications in banking, healthcare, telecom, and manufacturing

White Papers

Governance for Agentic Threats - A Strategic Roadmap

Beyond the Hype:Governance, Not Panic, as the Response to Agentic Threats

Download this PoV to learn:

Get the PoV

Agentic AI for Fraud Detection and AML Compliance

The Key Role of Agentic AI in Fraud Detection & Compliance

Download the White Paper to Learn:

Get the Whitepaper

Data Observability for AI Systems: Free White Paper | Covasant

Data Observability:The Backbone of Reliable AI Systems

Why Your Enterprise Needs Reliable AI and Analytics

Get the Whitepaper

Beyond the Hype:
Governance, Not Panic, as the Response to Agentic Threats

Data Observability:
The Backbone of Reliable AI Systems