What is PromptReports.AI?

PromptReports.AI is an AI-powered platform that creates professional executive research reports in minutes. It provides market analysis, financial reports, and strategic intelligence customized for your business needs.

How does AI report generation work?

Our platform uses advanced AI models to analyze your input data and generate comprehensive research reports. Simply provide your topic or data, select a report template, and our AI creates a professional document with insights, analysis, and recommendations.

What types of reports can I create?

You can create market analysis reports, competitive intelligence reports, trend scanning reports, financial analysis, strategic assessments, and custom research reports tailored to your specific industry or topic.

Yes, we prioritize data security. All data is encrypted in transit and at rest. We do not share your data with third parties, and you maintain full ownership of all reports generated on our platform.

Knowledge Base (RAG)

Retrieval-Augmented Generation enables intelligent document search and context-aware AI responses grounded in your data.

What is RAG?#

Retrieval-Augmented Generation (RAG) is a technique that enhances AI responses by retrieving relevant information from your documents before generating content. Instead of relying solely on the AI model's training data, RAG grounds responses in your specific data, resulting in more accurate, relevant, and factual outputs.

Grounded Responses

AI answers are based on your actual documents, not just general knowledge.

Source Citations

See exactly where information came from with automatic citations.

Semantic Search

Find relevant information based on meaning, not just keywords.

Automatic Indexing

All uploaded content is automatically indexed for fast retrieval.

Enterprise-Grade RAG

PromptReports uses advanced embedding models and vector search to ensure fast, accurate retrieval even with large document collections. Your data is securely stored and only accessible to you.

RAG Features#

RAG capabilities are integrated throughout PromptReports in several key areas:

Feature	Location	Description
Chat with Reports	Any generated report	Ask questions about your report content with automatic context retrieval
Context Files	Prompt creation	Upload documents to provide context for AI-generated content
Source Citations	Throughout platform	AI automatically cites sources when referencing uploaded content
Semantic Search	Knowledge Base page	Find relevant information across all your documents

Chat with Reports#

The "Ask the Report" chat feature lets you have a conversation with any generated report. The AI retrieves relevant sections from your report to answer your questions accurately.

Open a Report

Navigate to any generated report from your profile or the My Reports section.

Click "Ask the Report"

Find the chat icon or "Ask the Report" button in the report viewer.

Ask Questions

Type any question about the report content. The AI will search and answer based on the actual report.

Review Citations

The AI response includes citations showing which sections of the report were used.

Effective Questions

Ask specific questions for best results. Instead of "What's in this report?", try "What were the key findings about market growth?" or "Summarize the competitor analysis."

Context Files#

When creating prompts, you can attach context files to ground AI responses in your data. Supported file types include PDF, TXT, DOCX, and more.

File Upload

Upload PDF, TXT, DOCX files directly as context for your prompts.

URL Import

Import content from web URLs to use as context.

Text Input

Paste text directly as context without uploading files.

Reusable Contexts

Save contexts to use across multiple prompts.

How It Works#

Under the hood, PromptReports uses a sophisticated pipeline to enable RAG:

Document Ingestion

When you upload a document, it is parsed and split into smaller chunks for efficient retrieval.

Embedding Generation

Each chunk is converted into a high-dimensional vector using an embedding model.

Vector Storage

Embeddings are stored in a vector database for fast similarity search.

Query Processing

When you ask a question, it is also converted to an embedding.

Retrieval

The most similar document chunks are retrieved based on vector similarity.

Generation

Retrieved context is provided to the AI along with your question to generate an accurate response.

Pro Tips#

Best Practices for RAG

Use high-quality source documents - RAG can only be as good as your data
Keep documents focused on specific topics for better retrieval accuracy
Use the Contexts page to manage and organize your context files
Combine multiple smaller documents rather than one massive file
Review citations to verify the AI is using the correct sources
Update context files regularly to keep information current

The Knowledge Base page provides a central hub for understanding RAG capabilities and navigating to the features where RAG is used. For hands-on context management, visit the Contexts page.

PreviousDaily Benchmarks

NextMemory Systems