Case Study

How Our Claude Developers Built an AI Report Generation System for Hiswai

TL;DR: Claude developers for market intelligence built Hiswai an AI report generation system, engineered end-to-end with Claude Code, automating retrieval, planning, drafting, and quality assurance for enterprise research reports. Result: 80% faster report generation, 100% consistent report structure, and roughly half the analyst effort per report.

Hiswai is a knowledge management platform helping enterprise research teams track finance, policy, technology, and emerging industries.

Its research teams were stuck in a manual pipeline: analysts hunted down relevant documents, extracted the useful parts by hand, organised findings, and wrote every report from a blank page.

We partnered with Hiswai to automate that pipeline end to end, turning report generation into a governed AI system with full source traceability.

The Problem

Every report at Hiswai passed through the same manual bottleneck.

  • Analysts spent significant time identifying relevant documents, extracting information, and organising findings before writing a single word.
  • Report quality and structure varied from analyst to analyst.
  • Decision-making was delayed waiting on manual research cycles.
  • Production capacity was capped by how many analysts could research and write in parallel.
  • Existing document search tools offered keyword search, not contextual retrieval, structured report planning, or reliable long-form generation, and traceability between a claim in a report and its source was weak.

Hiswai needed a system that could research, plan, draft, and cite a full report automatically, at enterprise scale, without sacrificing traceability.

The Solution

Our Claude developers built an enterprise AI report generation system, engineered end-to-end with Claude Code, automating the complete report lifecycle from source retrieval to a finished, cited report.

Document Ingestion and Retrieval

FastAPI endpoints trigger automated report generation. Source documents are ingested from Amazon S3 with automatic deduplication, embedded via Amazon Bedrock, and indexed in Amazon OpenSearch Service for hybrid keyword-and-vector search.

AI Report Planning

The system generates the report's table of contents, creating chapters and sections dynamically based on the topic, validating the plan against a schema, and attaching source metadata to every section before a word of the report is drafted.

Intelligent Report Generation

Chapters generate concurrently, with automatic content expansion, anti-repetition logic, and fallback mechanisms so a single failed section doesn't stall the whole report. Every section is synthesised directly from its attached sources.

Quality Assurance

Hybrid search testing, table-of-contents validation, end-to-end testing, duplicate detection, and source-grounding verification run before a report ships.

The Architecture

Retrieval Layer

  • Amazon S3 for document ingestion with automatic deduplication
  • Vector embeddings via Amazon Bedrock
  • Amazon OpenSearch Service for hybrid keyword-vector search

Generation and Delivery

  • FastAPI APIs triggering automated generation
  • LLM-based report planning and drafting on Amazon Bedrock
  • AWS Lambda for serverless report generation
  • Amazon CloudWatch for monitoring and observability

The Impact

Hiswai's research teams get a finished, cited report where they used to get a blank page.

  • 80% faster report generation
  • 100% consistent report structure across every generated report
  • 2x reduction in analyst effort per report
  • Enterprise-scale report generation across multiple industries
  • Faster access to structured business insights for decision-makers

Key Takeaways for Research and Knowledge Teams

Pitfalls to Avoid

  • Automating report writing without structured retrieval underneath it
  • Skipping schema validation on AI-generated report plans
  • Treating source traceability as an afterthought instead of a build requirement

What to Prioritise

  • Separate retrieval, planning, and generation into distinct, governed stages
  • Validate structure before validating prose
  • Build deduplication and source-grounding checks in from day one

Build the Same System on Claude

If your research team is still assembling reports by hand, our Claude developers can scope a similar report generation system for you.

Speak with Our Claude Developers

The planet's best Claude developers can be working with you next week. Tell us your needs and we'll get in touch right away.