AUTHOR

Neurasensei AI Team

Posts by Neurasensei AI Team.

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On-site search that sells: from query to conversation

Searching products and knowledge is only the beginning. See how to connect it with an assistant, recommendations and actions in the frontend.

Voice transcription in business: what to do with recordings so your data stays in-house

Transcribing meetings and sales calls can bring order to your work, but it requires consent, retention rules and access control.

Two coral paths: documents and model tuning

RAG or fine-tuning? What actually improves model responses

RAG adds knowledge, fine-tuning changes behaviour. Confusing the two leads to expensive deployments that don't solve the problem.

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RAG without magic: how to build a knowledge base that doesn't hallucinate

Chunking, embeddings, hybrid search and reranking. A practical guide to RAG that answers from sources.

Two coral cores — one open, one closed inside a glass cube

Open-source or closed models? What to actually choose for your company

Open source gives you control; closed models give you convenience and quality. The decision depends on your data, budget and who will maintain the infrastructure.

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Local models or frontier models? How to match AI to the task

Not every task needs the largest model. How to split tasks, calculate costs and protect data when choosing between local and frontier models.

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Decision model vs. language model: who makes the decision in your AI?

An LLM understands language, but it should not decide on an action by itself. Here is where text generation ends and the decision layer begins.

A coral path choosing the simple route instead of a maze

When Is AI Not Worth Implementing? Six Signals to Check

Not every problem needs a model. Sometimes a form, a rule, or a tidier process is enough. Here are six signals that AI is the wrong first step.

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How to measure AI quality in your company: metrics that actually matter

Don't measure the number of messages. Measure whether customers find answers faster, whether the issue gets resolved, and how much support costs.

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Human in the loop: where a person must stay in the AI process

Human in the loop is not a checklist. It is a decision design: what AI prepares, what a person approves, and when the process must stop.

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AI Security in Your Company: 7 Rules That Protect Data and Reputation

Prompt injection, data leaks, and excessive agent autonomy. How to deploy AI in a company without giving up control.

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AI in customer service: what to automate and what to leave to humans

Automation does not have to mean a chatbot that handles everything. We show which cases can be handed to AI and which are better passed to a human.

Coral agent sphere surrounded by permission barriers

AI Agent Without Opening Pandora’s Box: Permissions, Boundaries and a Kill Switch

An agent with access to everything is fast only until the first incident. How to design autonomy you can actually control.