Scientific Research & Technical Teams

✅ Niche & Pain

Researchers spend hours reading papers, preparing summaries, and re-running common analyses.

🤖 Agents

• Literature Review Agent

• Experimental Summary + Insight Generator

• Code-to-Plot Explainer Agent

• Data Cleaning + Outlier Detection Assistant
  
  

🧠 ML / Models

• Semantic search over papers

• Summarization tuned on academic datasets

• Tabular + time-series anomaly detection

• Prompt-tuned coding assistant
  
  

🔁 Workflow

1. Researcher provides topic → lit review agent returns curated summaries.

2. Upload dataset → agent flags issues + creates EDA report.

3. Ask “what does this chart mean?” → receives LLM explanation with domain insight.
   
   

💸 Business Impact

→ Saves 10+ hours/week per researcher
→ Makes junior researchers more productive
→ Increases reproducibility + knowledge sharing