AI Infrastructure, Agents, and Inference Insights
Explore practical guides from PAVii.AI on AI inference, LLM architecture, agentic experience, AI harnesses, MCP integrations, context engines, and production-ready AI systems for modern businesses.
PAVii.AI Security
Oct 15, 2026
How Do You Make an AI Agent Keep Rules When Context Fills?
AI agents keep rules after the context window fills when hard rules live outside the model. Smart contracts check every tool call the agent makes.
PAVii.AI Security
Oct 15, 2026
Can an AI Company Learn From Your Data Without Seeing It?
Yes, partly. Privacy gates, aggregation and zero-knowledge proofs let an AI company learn from usage without seeing the personal data of a user.
PAVii.AI Security
Oct 15, 2026
How Is Blockchain Used to Secure AI Agents?
Blockchain for AI security: tamper-evident receipts, smart-contract rules, on-chain access control for shared memory, agent identity and zero-knowledge proofs.
PAVii.AI Security
Oct 15, 2026
Do AI Agents Need a Blockchain, or Is a Log Enough?
A signed hash-chained log is enough when one team runs and checks its own AI agents. You need a blockchain anchor when other parties must verify the log.
PAVii.AI Security
Oct 15, 2026
How Do You Stop Attacks on AI Agents? A Playbook
How to prevent AI agent attacks: least privilege, untrusted text as data, gates before tool calls, privacy filters, pinned hashes, budgets and a kill switch.
PAVii.AI Security
Oct 15, 2026
How Do You Make LLM Inference Faster and Cheaper?
Inference engineering for LLMs: model routing, small fine-tuned models, quantization, batching, caching, NPU and edge chips, and FPGA inference with trade-offs.
PAVii.AI Security
Oct 15, 2026
How Do You Prove to an Auditor What Your AI Agent Did?
Prove what an AI agent did with signed, hash-chained receipts. A gateway outside the agent writes them and anchors them on a blockchain for the auditor.
PAVii.AI Security
Oct 15, 2026
How Do You Stop an AI Agent Reading Above Your Access?
Stop AI agent privilege escalation: make the agent use the access of the user, and check access on every read from the shared company brain.
PAVii.AI Security
Oct 15, 2026
What Is x402 and How Do AI Agents Pay for Things?
x402 uses HTTP 402 Payment Required so an AI agent can pay for an API call in stablecoins and retry. Learn how agentic payments work and how to keep them safe.
PAVii.AI Research
Aug 21, 2026
Prompt Injection Explained: How Attackers Hijack AI Agents and How to Stop Them
Prompt injection is the top security risk for AI agents with tool access. Learn how injection attacks work, real-world examples, and layered defenses that actually help.
PAVii.AI Research
Aug 14, 2026
Running Multiple AI Agents in Parallel: A Practical Guide for Desktop Workflows
Parallel AI agents can research, code, and execute tasks simultaneously on your desktop. Learn when parallelism helps, when it hurts, and how to orchestrate it.
PAVii.AI Research
Aug 5, 2026
MCP Explained: The Protocol Connecting AI Agents to Your Tools and Data
Model Context Protocol (MCP) lets AI agents connect to databases, SaaS tools, and files through a standard interface. Learn how MCP works and how to use it safely.
PAVii.AI Research
Jul 22, 2026
Model-Agnostic AI: Why Locking Into One LLM Provider Is a Business Risk
Model-agnostic AI lets you swap LLM providers without rebuilding your product. Learn the risks of provider lock-in and how to design systems that stay flexible.
PAVii.AI Research
Jul 8, 2026
Local-First AI Assistants: Why Running AI on Your Own Machine Is Winning
Learn what local-first AI means, how it compares to cloud-only AI assistants, and why businesses are choosing desktop AI that keeps data on their own machines.
PAVii.AI Security
Jun 4, 2026
Agentic Security: How to Protect AI Agents, Tools, and Business Workflows
Agentic security helps companies protect AI agents, MCP tools, business data, permissions, and automated workflows as AI systems begin taking real action.
PAVii.AI Research
Jun 3, 2026
AI Inference Explained: How Smart Model Routing Improves Speed, Cost, and Accuracy
Learn what AI inference is, why model routing matters, and how PAVii.AI helps companies run faster, more accurate AI systems with lower compute waste.
PAVii.AI Product
Jun 3, 2026
What Is Agentic Experience and How Can It Help Your Company?
Agentic experience helps AI understand your application, call tools, complete workflows, and give customers better results through MCP and AI-ready interfaces.
PAVii.AI Engineering
Jun 2, 2026
What Is an AI Harness? A Practical Guide for Testing, Evaluating, and Shipping AI Systems
An AI harness connects models, prompts, tests, tools, and evaluations so teams can build reliable AI agents and applications before they reach production.
PAVii.AI Research
Jun 1, 2026
Architecture of LLM Systems: Context, Retrieval, Agents, and Inference Layers
Understand the architecture of LLM applications, including context engines, retrieval, tool use, agents, inference routing, and deployment patterns for business AI.
AI agent attacks in 2026: hidden instructions, tool and MCP abuse, data leaks, poisoned memory, supply-chain servers, cost loops and agent-to-agent tricks.
PAVii.AI Security
AI Safety and Platform Team
AI Research Notes
Read deeper notes on AI infrastructure, enterprise agents, context-aware systems, and the technical patterns that help companies build dependable AI products.
Why Context Engines Matter for Enterprise AI
Learn how context engines help AI systems retrieve the right knowledge, reduce hallucinations, and give employees and customers more accurate answers.
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MCP and AI-Ready Interfaces for Business Applications
See why MCP-style interfaces help AI agents understand your product, call tools safely, and reduce errors in business workflows.
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NPU Optimization and Edge Inference: Cutting AI Cost at the Hardware Layer
NPU optimized models and edge inference reduce AI compute cost, latency, and data exposure. Learn when hardware-aware deployment beats bigger models.
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