Answers for decision‑ready research

AI-powered qualitative analysis combines traditional qualitative research methodologies with artificial intelligence to analyze unstructured data such as interviews, open-ended survey responses, and customer feedback. This approach allows for faster, more consistent analysis of large datasets while maintaining the nuanced understanding that makes qualitative research valuable.

Our AI platform is designed to analyze virtually any form of text-based qualitative data, including interview transcripts, open-ended survey responses, customer reviews, social media comments, support tickets, and focus group discussions. We can also process and analyze multimedia content by first converting audio and video to text through our transcription services. For specialized data types like medical records or technical documentation, we can customize our models to understand domain-specific terminology and contexts. Our system is language-agnostic and can work with content in multiple languages, though English currently offers the most advanced analysis capabilities.

Traditional qualitative analysis relies heavily on manual coding and interpretation, which can be time-consuming and subject to individual researcher bias. Our AI approach augments human expertise with machine learning to identify patterns and themes more efficiently across larger datasets. This hybrid approach maintains the contextual understanding and nuance of human analysis while adding computational power to process more data in less time, identify non-obvious connections, and maintain consistency across large projects. Unlike fully automated solutions, we keep humans in the loop for validation and interpretation of findings.

AI-powered qualitative analysis combines traditional qualitative research methodologies with artificial intelligence to analyze unstructured data such as interviews, open-ended survey responses, and customer feedback. This approach allows for faster, more consistent analysis of large datasets while maintaining the nuanced understanding that makes qualitative research valuable.

We take data security and privacy very seriously. All data is encrypted both in transit and at rest, and we maintain strict access controls. Our systems are compliant with industry standards including SOC 2, GDPR, and HIPAA (for healthcare projects). We can also work within your organization's security infrastructure, including on-premises deployment if required. Additionally, we can anonymize sensitive data before processing and sign custom data protection agreements.

Yes, our platform is designed to handle sensitive and confidential data with the highest security standards. We offer multiple deployment options, including fully isolated environments for highly sensitive projects. Before processing, we can implement custom anonymization protocols to remove or mask personally identifiable information (PII) and other sensitive data points. We're happy to work under your organization's NDAs and data protection agreements. For regulated industries like healthcare or finance, we have specialized compliance protocols to ensure all data handling meets relevant regulatory requirements. We can also provide detailed data handling documentation for your compliance and audit purposes.

We take data security and privacy very seriously. All data is encrypted both in transit and at rest, and we maintain strict access controls. Our systems are compliant with industry standards and working toward SOC 2, GDPR, and HIPAA (for healthcare projects). We can also work within your organization's security infrastructure, including on-premises deployment if required. Additionally, we can anonymize sensitive data before processing and sign custom data protection agreements.

Our pricing model is flexible and based on several factors - the volume and complexity of data being analyzed, the depth of analysis required, the frequency of research (one-time vs. ongoing), and the level of customization needed. We offer project-based pricing for discrete research initiatives and subscription models for ongoing research programs. Project-based pricing typically ranges from $2,000 for smaller, focused studies to $10,000+ for comprehensive, multi-source research programs. Subscription plans start at $5,000 per month for continuous analysis with regular reporting. All pricing includes access to our platform, customization for your specific needs, and expert support from our research team. We're happy to provide a detailed quote based on your specific requirements after an initial consultation.

Our deliverables are customized to your needs but typically include a combination of the following. For thematic analysis workflows: comprehensive research reports with executive summaries and detailed findings, interactive dashboards for exploring themes and patterns in your data, data visualizations including thematic maps and sentiment analysis charts, actionable recommendations based on insights, raw data exports with AI-applied coding for your own analysis, and presentation decks for stakeholder communication. For decision analysis workflows: influence diagrams and decision matrices showing how stakeholders make decisions in different contexts. For the causal belief workflow: causal maps showing how different factors contribute to a common outcome. For all ongoing research programs, we provide regular insight reports and trend analyses showing changes over time. All deliverables are designed to be accessible to both research teams and business stakeholders, with appropriate levels of detail for different audiences. We can also integrate our findings with your existing business intelligence tools or reporting systems.

We employ a multi-layered approach to ensure quality and validity. First, our AI workflow is continuously updated and validated against human-coded datasets to maintain high accuracy. Second, we implement a human-in-the-loop validation process where experienced researchers review and validate AI-generated themes and patterns. Third, we use triangulation methods, comparing findings across different analytical approaches to strengthen validity. For critical projects, we can implement parallel human coding on a sample of the data to benchmark AI performance. We also provide transparency in our methodology, clearly documenting how insights were generated and the confidence levels associated with different findings. This hybrid approach combines the consistency and scale of AI with the contextual understanding and interpretive skills of human researchers.

We offer both standardized packages and fully customized research solutions. Our standardized packages provide cost-effective options for common research needs like customer feedback analysis, product research, or employee experience studies. These include predefined methodologies and deliverables but can be tailored to your specific context. For more complex or unique research needs, we develop fully customized solutions that align precisely with your objectives, data sources, and organizational context. This might include specialized analysis frameworks, custom AI model training for your industry terminology, or integration with your existing research tools and processes. All solutions, whether standardized or custom, include consultation with our research methodologists to ensure the approach meets your specific needs.

For standard projects with existing data that do not require new collection or integration, you can actually expect preliminary insights within 1-2 days of project kickoff and comprehensive findings within 1-2 weeks. For ongoing research programs, we establish continuous analysis pipelines with regular reporting cycles. We also offer expedited analysis for time-sensitive projects, though this may impact the depth of analysis possible. For clients who require custom workflows to meet their needs, the project timelines can vary based on scope, complexity, and data volume, but most follow this general framework - Initial consultation and project scoping (1-2 weeks), data collection or integration (1-4 weeks depending on whether data already exists), AI model customization and analysis (1 week), validation and refinement (1 week), and final reporting and insights delivery (1 week).