AI-powered qualitative research platform and searchable interview repository
Marvin provides an AI-assisted qualitative research platform where teams can centralize, search, and analyze customer interview data. The stack reveals a performance-oriented architecture (PostgreSQL, Redis, Prometheus, Grafana, Datadog) built to handle high-volume research data and millisecond query latency — pain points explicitly cited in their engineering backlog. Active hiring skews toward senior engineers (4 of 6 open roles) while simultaneously scaling sales development, suggesting they're balancing infrastructure maturity with revenue growth.
Marvin is a qualitative research platform used by product, design, and research teams to automate the collection and analysis of customer interviews. The product integrates with existing research workflows (user interviews, call recording, transcription, transcript coding) and provides a centralized, searchable repository of findings. Founded in 2020 and based in Oakland, the company operates with a 51–200-person team. Current engineering effort centers on AI-driven chat interfaces, interview automation, and test reliability — areas where they've identified gaps in existing test coverage and infrastructure scaling.
Backend: Go, Django, Celery, PostgreSQL, Redis. Infrastructure: AWS, Terraform, CloudFormation. Monitoring: Prometheus, Grafana, Datadog. Frontend: React, Next.js, JavaScript. CRM/Sales: HubSpot, Salesforce, LinkedIn Sales Navigator, seamless.ai.
Active projects include an AI-driven chat interface, AI interviewer experience, outreach campaign management, strategic pipeline research, and end-to-end testing infrastructure — the last addressing a cited gap in testing culture and reliability.
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Marvin's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.