In generative AI, grounding is the ability to connect AI models to verifiable sources of information. If you provide models with access to specific data sources, then grounding tethers their output to these data and reduces the chances of inventing content. This is especially critical in high-stakes areas such as finance, where accuracy and reliability are essential.

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Benefits of Grounding

✅ Reduces model hallucinations, which are instances where the model generates content that isn’t factual.
✅ Anchors model responses to your data sources.
✅ Provides traceability and auditability by providing grounding support, which are links to sources.
If you want to connect your AI model with world knowledge, up-to-date information, or even your own content, then use Grounding with Bigdata.com. Grounding with Bigdata.com enhances your model’s accuracy and recency by letting you choose sources like web content, local, national, or regional news, official government sites, specialty content providers, and more. Along with factual answers, the Bigdata API provides inline supporting links (grounding sources), top search results, along with the response content.

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How does it work?

Bigdata.com is a managed service that uses Retrieval Augmented Generation (RAG) to provide grounding behind the scenes through an API.
AcronymNameDescription
RRetrievalSearch for relevant data
AAugmentedAdd it to the prompt context
GGenerationFor use in Generative AI
This RAG approach ensures Bigdata.com’s responses remain accurate, relevant, and informed by the latest, verified data sources.

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Use Cases

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Grounding for Accurate, Real-time Responses

Using Bigdata.com, your AI models can consistently deliver accurate answers. For instance, in finance or market analysis, Bigdata.com retrieves recent financial news, earnings reports, and economic indicators, ensuring generated responses reflect the latest market conditions. Example:
Prompt: “Provide a brief analysis of TSLA recent earnings and how analysts are reacting.” Result: Bigdata.com retrieves the most recent earnings report for Tesla and current analyst commentary, grounding the model’s response in precise and timely information.
To search using this prompt, use the Similarity Query filter from the Search Service.or ask a question using the Chat API Service

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Web Content Retrieval and Analysis

With Bigdata.com, you can extract highly relevant data from across the web for analytical tasks like sentiment analysis, trend forecasting, or market intelligence. Example:
Prompt: “Analyze recent negative sentiment toward renewable energy policies across the EU.” Result: Bigdata.com searches recent negative-only news articles, policy announcements, and blog discussions, presenting summarized insights for detailed sentiment and trend analysis.
Web Content Retrieval will be available soon in the Search Service.and it is available in the Chat Service by default.

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Multimodal Reasoning Using Your Own Files

Bigdata.com empowers your AI model to interpret and reason from multimodal data in your own uploaded files, that contain text, tables, images, charts, or diagrams. Example:
Prompt: “From the uploaded quarterly financial report (PDF with tables and charts), summarize performance trends and identify anomalies or unexpected results.” Result: Bigdata.com extracts numerical data from the PDF’s tables and interprets trends from charts or diagrams, producing a concise analysis and highlighting anomalies for review.
To upload your propietary content, use the Upload Service.This is a how-to guide that demo how to upload your propietary content and search for insights in it.
🚀 Leveraging Bigdata.com enables sophisticated research workflows that demand careful planning, reasoning, and grounded thinking across diverse and complex scenarios. Have fun!