SuperReport: AI-Powered Verified Research Reports
Technology

SuperReport: AI-Powered Verified Research Reports

Problem Statement

Needed faster, accurate research reports with citations to improve analyst productivity and client delivery timelines.

Client Info

Mid-size consulting firm specializing in market research

Outcomes

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60% faster research report generation

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Reliable citation verification built into workflow

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Improved analyst satisfaction and reduced manual review load

How did BeautifulCode do it?

Challenges Encountered During Implementation

Data Quality & Verification: Ensured retrieved content was trustworthy by building automated citation checks.

Complex Orchestration: Managed multi-step AI pipelines with Celery chains for reliability and observability.

User Experience: Balanced automation with analyst control via interactive “Verify This” chips and diff views.

Solution

Built SuperReport: an AI-native platform leveraging RAG pipelines to generate citation-rich report drafts, enable verification workflows, and accelerate analysts’ turnaround time with high accuracy.

Overview of Delivery Methodology

Step 1 – Discovery: Understood analyst workflows and bottlenecks in research reporting.

Step 2 – Architecture: Designed modular system using LlamaIndex, Celery, and Qdrant.

Step 3 – Implementation: Built ingestion, retrieval, and report generation pipelines with streaming SSE.

Step 4 – UX Design: Delivered interactive editor with verification loops and inline diff review.

Step 5 – Iteration: Piloted with analysts, collected feedback, and refined workflows

Technologies Used

Python
Python for Core AI and data automation components
AWS
AWS for Cloud deployment and infrastructure
LangChain
LangChain for GenAI orchestration and automation

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