
YieldStack
CBRE Group
Jones Lang LaSalle
Online platform for commercial real estate loans

NVivo
ATLAS.ti
MAXQDA
CATMA
Dedoose
Paideias
QualCoder
AI-assisted qualitative analysis for PhD and postgraduate researchers. The AI surfaces candidate evidence; you confirm every coding decision — producing an audit trail and examiner-ready AI-disclosure statement. Seven methodologies supported.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | stacksource.com | qualintel.io |
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| Company | — | Startup from New Zealand · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of StackSource yet.
QualIntel OS is an AI-assisted qualitative research platform for PhD and postgraduate researchers — built for the question every examiner now asks: how did you use AI in your analysis? Other AI tools code your data and ask you to check it. QualIntel works the other way: the AI surfaces candidate...
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New StackSource Lender Interface
QualIntel OS
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As answered by people managing StackSource and QualIntel OS.
QualIntel OS's answer:
QualIntel OS is built around one non-negotiable rule: nothing gets coded without human confirmation. The AI retrieves candidate evidence from your transcripts, but the researcher accepts or rejects every suggestion — and each decision is timestamped into a methodology audit trail as you work. At submission time, that becomes a one-click package: evidence pack, codebook, audit trail, and an auto-generated AI disclosure statement an examiner can actually inspect. Most AI analysis tools do the thinking for you. QualIntel OS deliberately refuses to — it does the busywork and keeps the interpretation provably yours.
QualIntel OS's answer:
It depends what you need. If you want maximum speed — automated theme generation across large document sets — AI-native tools do that well. If your analysis has to survive a supervisor, an examiner, an ethics board, or a funder, QualIntel OS is built for exactly that moment: researcher-confirmed evidence, an accept/reject decision log, methodology-aware workflows (reflexive TA, grounded theory, IPA, Gioia, and more), and a disclosure statement generated from what actually happened rather than what you remember. Legacy tools like NVivo organise your data but leave all the work and none of the defence; generic chatbots do the work but destroy the defence.
QualIntel OS's answer:
Postgraduate researchers — master's and PhD candidates whose thesis has to survive examination — plus their supervisors, independent research consultants, and programme evaluators who need to defend findings to funding boards. Anyone doing qualitative analysis where "the AI found the themes" is a disqualifying answer.
QualIntel OS's answer:
The founder built it for his own problem: doing postgraduate research at a university whose AI policy demands declared, accountable AI use, while facing hundreds of pages of transcripts. Generic AI tools would do the analysis but hollow out the rigour; legacy software preserved rigour but did none of the lifting. QualIntel OS is the missing middle — AI that carries the structure and retrieval while the researcher keeps every interpretive decision, with the proof generated automatically as a by-product of working.
QualIntel OS's answer:
Next.js on Vercel for the web app, a Python/FastAPI API with PostgreSQL, Qdrant for semantic search, Anthropic's Claude for evidence retrieval and Voyage AI for embeddings (both under no-training terms), Clerk for authentication, and Stripe for billing. Hosting is on SOC 2 Type II certified infrastructure (Railway, US West).
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