reOS
reOS is an operating system for end-to-end customer research that consolidates planning, recruitment, conducting, analysis, and action into one platform. It addresses the common failure of research insights to be acted upon by providing traceable, source-linked evidence and closing the loop from insight to implementation. The tool supports live and AI-moderated interviews, prototype testing, and omnichannel ingestion of feedback from support tickets, emails, forms, and transcripts. Its DIVE analysis pipeline (Decode, Improve, Validate, Enrich) ensures human-led AI analysis, preventing hallucinations by validating every claim against its source. reOS also enables research compounding through Super Insights that surface patterns across multiple projects, and offers built-in coaching to improve team research skills. The platform aims to replace the fragmented stack of recruiting, scheduling, transcription, analysis, and repository tools with a single system that connects to existing CRM and support apps.
- Category
- AI Research Tool
- Pricing
- Unknown
Problem solved
Customer research insights are often lost in slide decks after a single presentation, leading to inaction, duplicated studies, and customer feedback loops that remain open. reOS solves this by making every insight traceable to its source, ensuring actionable follow-through, and closing the loop with customers.
Use cases
- Plan and execute customer interview studies with AI-generated research plans
- Recruit participants from CRM contacts and manage scheduling, consent, and incentives
- Conduct live or AI-moderated interviews with silent observers and automatic transcription
- Analyze omnichannel feedback (tickets, emails, calls, surveys) to identify trends and root causes
- Track and ship fixes based on insights, then notify the customers who provided feedback
- Generate validated reports with source citations to share with stakeholders
Audience
- Product Managers
- Researchers
- Designers
- Enterprise
- Startups
Pros
- Covers the entire research lifecycle from planning to closed-loop action
- Traceable insights with direct links to source evidence (timestamped, verbatim)
- Human-led AI analysis via DIVE pipeline reduces hallucination risks
- Consolidates multiple research tools into a single platform, reducing context switching
- Super Insights automatically surface cross-project patterns, making research compound
Cons
- Pricing may be prohibitive for very small teams or individual researchers
- Requires onboarding and integration effort to replace existing tool stack
- Heavy reliance on AI features may still introduce errors if not carefully overseen
- Limited to user research; not a general-purpose project management tool
- No self-hosted or offline deployment option for data-sensitive environments
Official website: https://www.reos.ai/
Canonical LambdaBase page: https://www.lambdabase.com/tools/reos