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Craig ML Dsouza
Craig ML Dsouza

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Building an AI Research Agent That Uses Real Data (Wiki + Finance)

I Built an AI Agent That Uses Real Data Instead of Just Guessing

Most AI tools today just generate text.

They rely on model memory, often guess information, and produce inconsistent outputs.

I wanted to explore a different approach — what if an AI system could fetch real data, process it step-by-step, and return structured insights instead of raw text?

So I built OpenAgent.


What is OpenAgent?

OpenAgent is a multi-step AI research agent designed to move beyond basic text generation.

Instead of relying only on the model, it:

  • pulls data from Wikipedia for context
  • fetches market data from Yahoo Finance
  • processes everything through a structured pipeline
  • outputs clean, structured insights

Why this matters

Most AI systems:

  • generate unstructured text
  • mix signal with noise
  • are difficult to integrate into real applications

OpenAgent focuses on:

  • real data instead of guesses
  • structured outputs instead of paragraphs
  • step-by-step processing instead of single-pass generation

How it works

Each query goes through a multi-phase pipeline:

Planning → Execution → Signal Extraction → Synthesis
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Planning
Determines which tools to use (Wikipedia, Finance)

Execution
Fetches real data from external sources

Signal Extraction
Filters high-value information from raw data

Synthesis
Generates structured output with key insights


Example

Prompt:

Analyze Microsoft (MSFT)
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Output:

{
  "summary": "...",
  "keyInsights": ["..."],
  "risks": ["..."],
  "opportunities": ["..."],
  "sentiment": "POSITIVE",
  "confidenceScore": 82
}
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Instead of a long paragraph, you get usable, structured data.


Demo

The system fetches real data, processes it, and generates structured results in real time.

What you can do with it

  • Analyze stocks and companies
  • Perform quick research with real data
  • Build structured AI workflows
  • Use outputs directly in applications

Key takeaway

LLMs are powerful, but raw text output is often not enough.

By combining:

  • external data sources
  • structured pipelines
  • controlled outputs

you can build systems that are more reliable and usable in practice.


Try it out

GitHub:
https://github.com/CraigMLdsouza/OpenAgent

Full version:
https://craigstorm.gumroad.com/l/openagent-research


Final note

This is a developer-focused project aimed at exploring more reliable AI systems.

If you're building with AI, moving beyond text generation into data-driven agents is a direction worth exploring.

Top comments (1)

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shriya_saxena_431474aab70 profile image
Shriya Saxena

This is sick honestly. AI that actually fetches real data and turns it into structured insights is way more useful than just text generation. Good Job Craig!! Keep it up