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AI that actually works inside the enterprise.
Articles on revenue discovery, margin intelligence, and what it actually takes to make AI work in regulated and data-fragmented organisations. Written by Jeremy Vince, Co-Founder and CEO of NexDiscovery.
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Newsletter — AI Enterprises Actually Trust
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Most Enterprise AI Is Still Reactive
Dashboards wait for someone to review what happened. Copilots wait for someone to ask the right question. That is useful visibility. It is not intelligence. The real problem is that enterprise systems do not think across signals, and nobody has time to connect them manually.
Enterprise AI Has a New Problem
The bill is arriving before the ROI. One unnamed company spent $500M on AI in a single month. Token costs scale with usage. ROI does not always follow. The enterprises that will win are the ones that find AI that proves value before the meter runs, not after.
The Portco CEO's Data Problem
A PE value creation plan needs sharper answers than any dashboard provides. The revenue and margin signals are already in the data, in CRM, billing, finance, and support systems that have never been searched together. Here is what it looks like when they are.
Deep reads
The questions buyers ask before they say yes.
How to find hidden revenue in a PE-backed company in 30 days
The signals exist in your data. They are scattered across CRM, billing, finance, and customer systems that have never been searched simultaneously. Here is the exact process for surfacing them: what to connect, what to look for, and what a finding looks like when you get one.
Why enterprise AI pilots get blocked by legal teams and what to do instead
Most enterprise AI requires data to leave the environment, which triggers vendor due diligence reviews that can take 12 to 18 months. One architectural change eliminates the objection entirely. Here is what compliance-by-design actually looks like, and what it unlocks.
HIPAA-compliant AI for healthcare operational intelligence
PHI must stay inside your environment. Most AI vendors cannot deliver that, or they require a BAA negotiation that takes 6 to 12 months. Here is what healthcare organisations need to look for, and why the architecture question matters more than any feature list.
How to improve EBITDA in a portfolio company using data in 30 days
The EBITDA improvement levers are already inside the portco's data. Revenue that could be retained, costs that could be reduced, friction that could be removed. Most PE value creation plans address these with consulting and headcount. There is a faster path.
What OCC and FDIC compliance teams actually require from AI vendors
The third-party vendor review process at regulated financial institutions is the most common reason AI initiatives stall. Understanding exactly what triggers the review, and what eliminates the trigger, is the difference between a 30-day sprint and an 18-month procurement process.
The difference between a dashboard and a discovery engine
Dashboards show you what you already knew to measure. Discovery engines find what you did not know to look for. The distinction sounds simple. The operational difference is significant, and it explains why most BI investments produce reports that describe problems after they happen rather than signals before they do.
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