In Outmind, you can perform your searches in two ways:
direct document search
search via the AI Assistant
These two approaches are complementary, but they work differently.
⚖️ Quick comparison
| Direct search | AI search |
How it works | Deterministic (exact indexed matching: based on terms, filters, and criteria) | Probabilistic (understands meaning and context) |
Results | Exhaustive | Selection of the most relevant |
Accuracy | Very precise if the right keywords are used | Good even without exact wording |
Understanding | Literal | Contextual |
Use case | Finding a specific document | Understanding, analyzing, synthesizing |
Main limitation | Requires the right terms and search criteria | Not always exhaustive |
📄 When to use direct search?
Use it when:
you are looking for a specific document
you know terms, filters, or criteria (source, date, type, etc.)
you want to browse or filter a set of documents
you want to make sure you don’t miss anything
👉 Example: filter by source, document type, or time period to retrieve all matching items.
🤖 When to use AI search?
Use it when:
you don’t know exactly how the document is named
you are looking for broader information
you need a list of documents
you need a summary or analysis
🧠 Search: a key step in a broader process
Search is already an essential value driver: quickly finding the right document saves a significant amount of time.
But in many cases, the work doesn’t stop there.
Once documents are found, they still need to be reviewed, understood, and turned into actionable insights.
A typical workflow looks like this:
Search: Identify documents using keywords, filters, or context
Curation: Browse results (titles, snippets, dates…) to spot what seems relevant
Review: Open and read documents to validate their relevance
Extraction: Identify key elements (important information, names, data…)
Generation: Produce a usable output (summary, synthesis, list, answer…)
👉 This process reflects what you would naturally do as a user in Outmind: search, browse, open, analyze, and then use the information.
👉 It applies both to a human working manually through the search interface and to the AI Assistant, as long as you clearly describe the steps to follow.
👉 The Assistant can chain these steps, but it can also request intermediate validations depending on how you structure your request.
👉 The key difference: it allows you to save time and process more information, while still keeping control over the process.
To go further on how to structure your requests, you can read: Creating a good prompt for your assistant: methods and examples.
💡 How to improve AI search?
AI search is not exhaustive, but you can get closer to it:
be precise in your request
run several more targeted searches
break your search into multiple iterations
ask the AI to list the documents it used
combine it with direct search
🧠 Key takeaways
Direct search = exhaustive, criteria-driven
AI search = smart, context-based
Both are complementary and should be combined