---
id: "entity-twinloop"
type: "entity"
entityType: "organization"
canonicalName: "Twinloop"
aliases: ["Twinloop"]
source_timestamps: ["§ When You Need the “Why” Behind the Numbers", "§ The Road Ahead"]
tags: ["startup", "ai-driven-research"]
related: ["entity-gbk-collective", "claim-verbal-vs-typed-responses", "concept-synthetic-personas", "entity-columbia-business-school", "open-question-digital-twin-training"]
sources: ["commercial"]
sourceVaultSlug: "hbr-seg-commercial"
originDay: 5
articleStem: "hbr-new-30-ai-scale-customer-research"
sourceUrl: "https://hbr.org/2026/04/how-ai-helps-scale-qualitative-customer-research"
sourceTitle: "How AI Helps Scale Qualitative Customer Research"
---
# Twinloop

**Twinloop** is an early-stage company developing AI-driven research methods.

## Contributions in this source

- Partnered with [[entity-gbk-collective]] to test AI-moderated **voice** interviews against typed surveys, yielding the **7× longer responses** result → [[claim-verbal-vs-typed-responses]].
- Currently involved in a study with [[entity-columbia-business-school]] to determine optimal training-data modalities for [[concept-synthetic-personas]] → [[open-question-digital-twin-training]].

## Canonical reference

Twinloop website / product page. Early-stage firm focused on AI-moderated interviews and digital-twin research; limited public detail, consistent with the "early stage" portrayal.