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The Core Squad
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COSTAQDA

Cutting literature review and qualitative coding time for academic researchers with an AI-assisted analysis suite

Core AIAcademic Research / EdTech SaaS
Industry
Academic Research / EdTech SaaS
Year
2023
Timeline
6 months
Squad size
6 specialists
At a glance

"An AI-assisted suite that takes researchers from raw documents to a publication-ready literature review or coded transcript analysis."

Impact & results
30PDFs processed per review batch
Timeline
6 months

6 months — sprint-based delivery across the core analysis suite and the document-parsing engine.

The squad
Product ManagerTech LeadAI EngineerBackend EngineerFrontend EngineerQA Engineer
The challenge

Researchers spend more time processing documents than analyzing them.

Manually appraising study quality, coding transcripts, and assembling a literature review from dozens of source documents is slow, repetitive work that eats into the time researchers should spend on actual analysis and interpretation.

  • Manual CASP-style quality appraisal across many source documents
  • Transcript coding (meaning units, open/axial coding, theming) done by hand
  • Assembling a publication-ready literature review from scratch
Platform intelligence
"We built a platform that parses uploaded research documents and transcripts with the OpenAI API, automates quality appraisal and coding, and produces a structured evidence synthesis or literature review ready for export."
What's included

Everything under this engagement.

01

Qualitative Evidence Synthesis

  • Upload research PDFs for automated CASP quality appraisal
  • AI-assisted inductive coding and meta-ethnographic synthesis
02

Review Writer

  • Upload up to 30 PDFs at once
  • Automated evidence synthesis matrix
  • Publication-ready literature review exported to Word/PDF
03

Transcript Analyzer

  • Upload interview/focus group transcripts
  • Automated meaning units, open/axial coding, and theme generation
04

Costa GPT — AI Document Parsing

  • OpenAI API-powered parsing of uploaded research documents
  • Feeds structured content into the coding and synthesis pipeline
Gallery

Explore the interface and core components.

COSTAQDA — Dashboard
COSTAQDA — Dashboard
Build & infrastructure

The technology driving this solution.

AIOpenAI APINoNode.jsPgPostgreSQL

Our approach

We built a document-parsing engine on the OpenAI API that ingests research PDFs and transcripts, then layered automated CASP-style quality appraisal, inductive coding, and meta-ethnographic synthesis on top — exporting straight to a publication-ready format.

The result

Researchers can now run a batch of up to 30 source PDFs through automated evidence synthesis, or a full transcript through automated coding and theming, instead of doing it by hand.

Delivered by

Core AIAI agents, chatbots, LLM apps

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