How a Global Research Agency Saved $100K+ Building a White-Label Qualitative Research Platform

Learn how a global research agency launched a branded qualitative research platform for audio and video with Speak AI. The team captures and analyzes 127+ hours of consumer feedback, saves about 983 hours of analyst time, avoids $100K+ in engineering work, and delivers multilingual, client ready reports at speed.
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What you can do
Capture, transcribe, and analyze audio, video, or text
Summaries, action items, themes, quotes, and key moments
White-label embeds, repositories, and exports for real workflows
Trusted, fast, global
Users
250,000+
Languages
100+
Exports
DOCX, SRT, VTT, CSV

127+ hours of video and interview feedback analyzed • about 980 hours saved • $115K+ estimated savings to date

Overview

A global research agency used Speak AI to power a white label video and audio insights platform for rapid product and packaging feedback.

The team captures video reviews and in-depth interviews, structures responses automatically, and shares client-ready findings in a branded portal with AI chat, filters, and visualizations.

The result is a faster, scalable workflow that preserves qualitative depth while reducing analyst effort and internal development costs.

The Challenge

Launching a modern video and audio research product required three difficult ingredients at once.

First, reliable capture at scale across geographies and languages.

Second, accurate transcription and analysis with consistent coding for sensory and packaging themes.

Third, a secure, white labeled delivery experience that clients could explore without training.

Building this from scratch would be slow and expensive. Managing multi-language feedback, permissions, exports, and API integrations added more risk to timelines.

Solution and Workflow

Speak AI provided the capture to insights backbone while letting the agency control brand, UX, and client experience.

  • Embeddable audio and video recorder plus surveys to collect structured responses directly inside the agency’s platform.
  • Automatic transcription and analysis with custom fields for sensory attributes like taste, texture, smell, aftertaste, and on-pack claims.
  • Folder and account-level AI chat to synthesize hundreds of video and audio files at once and cite source segments.
  • Client-facing libraries that are fully white labeled with branded players, keyword and sentiment views, and controlled access.
  • Developer-friendly APIs and CSV uploads that simplified ingestion and kept the internal roadmap focused on experience rather than infrastructure.
  • Multilingual analysis across English, French, Dutch, Swedish, and more, with translation and unified reporting in one place.

The agency organizes each client by folder, automates analysis with saved prompts, and shares curated libraries that update in real time as new media arrives.

Continue reading the full guide (click to expand)

Results

Metric Before Speak AI With Speak AI Impact
Recorded hours processed Manual capture and analysis across tools 127.7 recorded hours analyzed to date Standardized pipeline from upload to insights
Analyst time per recorded hour About 8.0 hours for transcription and thematic coding About 0.3 hours for oversight and edits About 96% faster analysis
Total time saved Backlog and context switching across tools About 983 hours saved to date Analysts focus on interpretation and recommendations
Estimated labour savings Research heavy manual workflow About $17.5K saved on analysis labour Compounds as more recordings are added
Estimated development savings Building capture, analysis, exports, and libraries in-house $100K+ engineering time avoided Faster go-to-market with lower platform risk

Methodology note: Totals reflect 127.7 recorded hours analyzed to date, including embeddable uploads and limited meeting assistant usage. Research heavy baseline assumes 8.0 manual hours per recorded hour for transcription and analysis versus 0.3 hours of AI-assisted oversight. Savings per recorded hour are modelled at $137. Figures are rounded to protect confidentiality. Development savings reflect internal estimates for equivalent capture, analysis, translation, export, permissions, and white label delivery features.

Security and Governance

Data is encrypted in transit and at rest. Customer data is not used for model training.

Role-based access with folder permissions and audit-friendly sharing.

White labeled libraries with optional password protection and usage statistics.

Usage Snapshot

Thousands of media files processed across studies with multilingual responses. Analysts use custom fields, saved prompts, and advanced filters to compare segments and deliver clear, defensible recommendations.

Industry Context and Keywords

market research, video research, consumer insights, iHUT, sensory testing, packaging test, concept test, multilingual analysis, white label portal, API integration, AI chat, sentiment analysis, keyword visualization, insights repository

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Take the Next Step

Want to launch a white label video insights experience without the heavy build? Book a 15 minute walkthrough, create a free Speak AI account, or estimate your ROI with our interactive calculator.

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