Fleet

Fleet

Your all-in-one IT Solution
3 reviews
617 followers

What is Fleet?

All-in-one solution for IT leasing and device management. We procure, secure, assist and recycle IT equipment. Our first product is the Fleet Cockpit. 🚚 Track devices ⎮ 👥 Organize teams ⎮ ⌛️ Save time ⎮ 💻 Provide support ⎮🛡️Secure

Do you use Fleet?

Fleet gallery image
Fleet gallery image

Recent Fleet Launches

Fleet AI Copilot

Forum Threads

The differences between prompt context, RAG, and fine-tuning and why we chose prompting

When integrating internal knowledge into AI applications, three main approaches stand out:

1. Prompt Context – Load all relevant information into the context window and leverage prompt caching.2. Retrieval-Augmented Generation (RAG) – Use text embeddings to fetch only the most relevant information for each query.3. Fine-Tuning – Train a foundation model to better align with specific needs.

Each approach has its own strengths and trade-offs:

Prompt Context is the simplest to implement, requires no additional infrastructure, and benefits from increasing context window sizes (now reaching hundreds of thousands of tokens). However, it can become expensive with large inputs and may suffer from context overflow.• RAG reduces token usage by retrieving only relevant snippets, making it efficient for large knowledge bases. However, it requires maintaining an embedding database and tuning retrieval mechanisms.• Fine-Tuning offers the best customization, improving response quality and efficiency. However, it demands significant resources, time, and ongoing model updates.

Why We Chose Prompt Context

For our current needs, prompt context was the most practical choice:

• It allows for a fast development cycle without additional infrastructure.• Large context windows (100k+ tokens) are sufficient for our small knowledge base.• Prompt caching helps reduce latency and cost.

What do you think is the better approach ? In our case as our knowledge base grows, we expect to adopt a hybrid approach, combining RAG for scalability and fine-tuning for more specialized responses.

View all

Review Fleet?

5/5 based on 3 reviews

Reviews

Marine Calvayrac
1 review
The right solution to simplify your IT management!
Noé Martineau
2 reviews
Better product i ever seen
Ajay Sahoo
115 reviews
Tagline of the product holds the real meaning.