LLMs can summarize. Ascribe understands.
Purpose-built by researchers to deliver insights you can trust — fast, accurate, and secure. Ascribe delivers research-grade insights — built for accuracy, control, and compliance.
Fill out this form to discover why market researchers prefer Ascribe for open-end analysis
AI is reshaping research — but one size doesn’t fit all.
As AI becomes central to insights workflows, many teams are experimenting with large language models like ChatGPT or Claude for coding and summarizing open-ends. These general LLMs offer speed and convenience — but lack the research methodology, transparency, and data control that professional researchers depend on.
That’s why leading insights teams choose Ascribe, the AI alternative to LLMs designed specifically for market research.
Purpose-built AI for market research vs. general-purpose LLMs
Ascribe (AI for Market Research)
Generic LLMs
Purpose
Ascribe
Designed by and for research professionals
Generic LLMs
Built for general consumer or enterprise use
Accuracy
Ascribe
Research-grade, validated against industry coding standards
Generic LLMs
Inconsistent, unverified accuracy
Control
Ascribe
Codebook management, reusability, and respondent-level drill-downs
Generic LLMs
Limited transparency or reproducibility
Workflow Integration
Ascribe
End-to-end: survey design → AI coding → visualization → reporting
Generic LLMs
Manual handoffs, disconnected workflow
Security & Compliance
Ascribe
Enterprise-grade, region-based hosting for data privacy
Generic LLMs
Data storage and reuse vary by vendor
Support
Ascribe
Expert research guidance from real humans
Generic LLMs
Generic AI support, no market research expertise
Scalability
Ascribe
Handles millions of open-ends without sacrificing precision
Generic LLMs
May degrade or become cost-prohibitive at scale
Evolution
Ascribe
Continuously refined with researcher feedback
Generic LLMs
Broad, consumer-driven feature roadmap
Market Research Deliverables
Ascribe
Ability to export coded results, save excel structured data, dichotomous data
Generic LLMs
Fails at large datasets, not consistently formatted
Instant clarity
AI-driven summaries, natural-language queries, and visualizations tailored for research presentations.
Seamless workflow
Connect survey design, coding, analysis, and reporting — all within Ascribe.
Reliable results
Human-in-the-loop validation ensures accuracy and trustworthiness.
Scalable performance
From small ad-hoc studies to millions of responses, Ascribe scales with your data.
AI speed meets research-grade rigor
LLMs offer quick answers — but lack context, control, and accountability.
Ask Ascribe bridges that gap, combining the power of AI with the discipline of research methodology.
Deliver insights that are not just fast, but accurate, defensible, and client ready.
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Responsible AI, designed for insight generation
Human in the Loop
Every model is reviewed and refined by research experts for quality and nuance.
Philosophy of Abundance
Using AI to enhance researcher capabilities, not replace them.
Safe & Responsible AI
Enterprise-level security and regional compliance to protect sensitive respondent data.
