Enterprise AI, explained for builders and buyers. Page 10 of 29
Practical writing on governed agent orchestration, on-premise AI, compliance, and the infrastructure decisions that separate pilot projects from production platforms.
CapEx or OpEx? How Finance Teams Account for On-Premises AI Spend
The same AI programme can land on the balance sheet or in the income statement depending on how it is bought and built. A line-by-line guide to how hardware, licences, internal agent development, fine-tuning and data work are typically classified under IFRS and US GAAP, and where AI creates new judgement calls.
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Hybrid Search for Private RAG: Why Vector Search Misses Policy Numbers and Part Codes
Vector search is good at meaning and bad at exact strings, and enterprise questions are full of exact strings: policy numbers, part codes, clause references. How hybrid keyword-plus-vector retrieval works in a private RAG pipeline, and how to run it inside your own infrastructure.
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AI Agents for Credit Memo Preparation and Risk Summarization
The commercial credit memo is a synthesis job built from a dozen systems, and it consumes the analyst time that should go into judgement. How to build an agent that assembles the evidence and drafts the narrative without ever forming the credit opinion itself.
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How to Trigger VDF AI Agents from Enterprise Events
Most enterprise work arrives as an event, not a question: a ticket opens, an invoice posts, a document lands. A practical guide to wiring webhooks, queues and schedules into governed agent runs — with the delivery, identity and backpressure problems handled before they reach production.
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Long-Context Models vs Private RAG: What On-Premises Buyers Should Evaluate
A million-token context window looks like it retires your retrieval pipeline. On-premises, it mostly moves the cost into GPU memory and quietly removes your permission filter. How to decide which work belongs to retrieval and which belongs to context.
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AI Agents for Subrogation: Finding Recovery Before the File Closes
Subrogation is lost at intake, not in negotiation. How agents can flag recovery potential, preserve evidence, and build the file — with the pursue decision left to people.
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When an Employee Leaves: Offboarding People from an Enterprise AI Platform
Revoking SSO does not undo what an AI platform learned. A joiner-mover-leaver checklist for agents, private RAG permissions, memory, shared prompts, and audit trails.
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Red-Teaming an Enterprise AI Agent Before It Reaches Production
An adversarial test is not a benchmark. How to scope, run, and sign off a red-team exercise against an agent's tools, permissions, and retrieval — and what evidence it should leave behind.
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Stopping AI Agents Safely: Cancellation and Deadlines on Private Infrastructure
Design cancellation across agent branches, local model servers, queues, and tools so stopped workflows release GPU capacity and report their actual state.
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