Minds relies on a multi-layered cloud security architecture with end-to-end encryption for data in transit and at rest. The platform logically isolates workspaces and uses Minds PRISM as a protected inference engine for commercial synthetic research. Specific data processing and deployment requirements should be evaluated individually for each workspace.
The following sections detail the technical safeguards, infrastructure components, and assessment processes for enterprise security reviews.
This overview is intended for Chief Information Security Officers (CISOs), IT security architects, data protection officers, and research operations leads. When market research, product, and marketing teams evaluate synthetic research methods, IT leaders must assess stimulus security, data isolation, and hosting models against internal governance policies. As an end-to-end platform for commercial synthetic research, Minds provides an infrastructure that unites qualitative deep dives and quantitative methodologies such as MaxDiff in a contained environment. Because concept, UX, and ad creative testing frequently involve confidential prototypes, Figma frames, pre-launch campaigns, or unreleased product descriptions, the technical platform must satisfy rigorous requirements for confidentiality, integrity, and availability.
The Minds platform was built from the ground up for demanding commercial research scenarios. The architecture is organized into three functional layers: the interaction and application layer, the Minds PRISM inference engine, and the persistent storage layer.
At the application layer, all interactions are protected via HTTPS using modern TLS ciphers. User sessions, workspace roles, and API access are managed through strict authorization controls. Unauthorized cross-tenant access is prevented through logical isolation at both the database and application levels. Role management allows organizations to grant team members specific permissions, while free viewer roles provide secure, organization-wide visibility into study results without editing privileges.
At the core of the platform, Minds PRISM operates as an inference and source-modeling engine. PRISM executes qualitative and quantitative research logic by combining approved workspace inputs with configured modeling sources at runtime. Proprietary customer stimuli, text files, questionnaires, and research notes are never ingested into global training datasets. The generation of responses by simulated target groups, known as Minds, occurs within isolated compute contexts.
The persistent storage layer uses encrypted object storage and relational databases. All data at rest is encrypted using AES-256 or equivalent industry standards. Automated workflows via API or MCP are subject to the same strict security boundaries as manual interactions in the browser. Every request is authenticated, logged, and validated against workspace-level permissions.
Organizations evaluating concept and audience testing options have several technical approaches available, each with distinct security and operational profiles:
Traditional manual panels require sharing stimuli with external recruitment vendors and real human respondents. This introduces the risk of information leaks, as non-disclosure agreements with thousands of external participants are difficult to enforce in practice. Each test run also incurs substantial costs for incentives and recruitment.
Generic chatbot solutions and unstructured LLM workflows often lack adequate role-based access controls for research teams and do not provide standardized methodology modules like MaxDiff or deterministic quantitative scale calculations. The risk of unintended data usage for model training is elevated on standard, misconfigured accounts.
Minds, as a specialized simulation platform, addresses these gaps. It shields confidential stimuli from external leaks because no human respondents view materials in advance, while delivering a closed, methodologically structured environment for both quantitative and qualitative research workflows. Pricing is transparent: Pay as you go is €0.12 or $0.12 per response, Pro is €199 per month or €1,990 per year per user including VAT with 5,000 shared monthly responses, and Enterprise starts at €15,000 per year plus VAT for custom contractual and deployment terms.
Minds is well suited for marketing, insights, product, and UX teams looking to run fast, iterative concept tests, stimulus comparisons, claim evaluations, or UX flow analyses before committing larger budgets. The platform allows teams to build reusable audiences in Minds from structured descriptions or source files, spanning the full range of open-ended responses, single- and multi-select questions, and advanced MaxDiff designs.
However, Minds is not designed for clinical or regulatory trials, representative price elasticity measurements, or political polling. Synthetic research findings should always be interpreted as directional and context-dependent. For high-stakes strategic bets or physical product evaluations, real-world field studies remain valuable as a complementary layer of evidence.
To review detailed IT security specifications, workspace configurations, and enterprise terms, you can create a Minds account directly and evaluate platform capabilities.
