WHITEPAPERS

Frameworks, and architectures for building reliable enterprise AI.

Our whitepapers cover all aspects of running an AI factory at scale. Agentic process automation, AI governance, Zone III systems, How to build an Evidence Factory, and AI-assisted SDLCs, and measurable value creation at enterprise scale.

Built from real operational experience. Written for organizations moving beyond AI hype.


Ad-hoc, project based deployment models suffer from high failure rates up to 70%, extended time to value and unsuitable governance overhead. The agentification fac1tory model replaces this with a systematic, repeatble production pipeline – achieving a 65% success rate, 40-60% faster time to value.


In this paper, we share the lessons from 177 agentic AI deployments. In it you will find that there are four types of processes. Agentic AI can only support two of these. When you try the others, there’s 70% chance you’re project is not going to be successful.


Why enterprises are sleepwalking into the most
consequential AI architecture failure of the decade


In this whitepaper we introduce the Value Office as the runtime-integrated economic control layer for agentic process automation.


Enterprises are deploying autonomous AI agents into critical business processes and at the same time, they’re still governing them with
dashboards, post-factum audits, and static controls. This whitepaper defines the Evidence Factory, the missing runtime intelligence layer that makes enterprise-scale agentic AI survivable, auditable, and economically defensible.


This whitepaper synthesizes findings from NCC-1701’s research into enterprise AI governance, aligning with global regulatory standards including the EU AI Act, GDPR, and the NIST AI Risk Management Framework (RMF). It provides a technical blueprint for deploying autonomous agents in high-stakes, audit-heavy domains.