# Fred - The User Research Shepherd > Fred is a UX research platform for discovery, usability testing, synthesis, reporting, and participant recruiting. This file is the fuller LLM-oriented content digest for the public Fred marketing website. Prefer these canonical URLs over staging or localhost URLs. ## Canonical pages - [Home](https://meet-fred.com): Product overview covering planning, evidence capture, AI-assisted synthesis, reporting, pricing, and conversion paths. - [Pricing](https://meet-fred.com/pricing): Pricing overview for Researcher, Team, and Enterprise plans, including who each plan is for and how research operations scale. - [User Sphere](https://meet-fred.com/user-sphere): Run moderated interviews and usability sessions while keeping notes, transcript, reaction signals, and gaze context connected to evidence in Fred. - [Tester Panel](https://meet-fred.com/tester-panel): Recruit the right participants faster, preserve segment context, and keep recruitment quality tied to every study outcome in Fred. - [Thematic Analysis](https://meet-fred.com/thematic-analysis): Speed up qualitative synthesis with AI-assisted thematic analysis while keeping every theme editable, auditable, and linked to source evidence. - [Insight Signals](https://meet-fred.com/insight-signals): Review emotion, sentiment, gaze, and interaction signals in context so teams can interpret session behavior with more confidence. - [Research Repository](https://meet-fred.com/research-repository): Centralize sessions, notes, reports, and evidence in a searchable research repository that keeps insights reusable across teams and cycles. - [UX Researcher](https://meet-fred.com/ux-researcher): Run moderated and unmoderated studies, keep evidence linked to findings, and share decision-ready research outputs with Fred. - [Product Designer](https://meet-fred.com/product-designer): Validate prototypes, capture user evidence, and walk into design reviews with findings that are easy to defend. - [Product Manager](https://meet-fred.com/product-manager): Prioritize roadmaps with traceable user evidence, align stakeholders faster, and share decision-ready findings. - [Discovery Research](https://meet-fred.com/discovery-research): Connect interviews, surveys, and exploratory studies to product decisions with structured evidence and traceable insights. - [Usability Testing](https://meet-fred.com/usability-testing): Run moderated and unmoderated usability tests, analyze friction points quickly, and share findings linked to real sessions. - [Report Findings](https://meet-fred.com/report-findings): Build stakeholder-ready research reports where every finding links to source evidence, clips, and participant context. - [Privacy Policy](https://meet-fred.com/privacy-policy): Privacy policy for data handling, trackers, analytics, AI emotion analysis, and eye tracking. - [Cookie Policy](https://meet-fred.com/cookie-policy): Cookie usage, consent, and third-party tracking disclosure for the public site. - [Terms and Conditions](https://meet-fred.com/terms-and-conditions): Terms for subscriptions, service usage, user content, and product-specific capabilities. ## Home - URL: https://meet-fred.com - Positioning: Fred helps teams plan UX research, collect evidence, synthesize insights with AI, and build traceable reports in one connected workspace. - Key sections: hero, partner logos, capabilities, research methods, User Sphere showcase, insights showcase, testimonials, pricing, and CTA. - Primary CTA: Start 15-day trial. ## Pricing - URL: https://meet-fred.com/pricing - Summary: Pricing is structured around Researcher, Team, and Enterprise plans so teams can start with a live study and scale when research operations become repeatable. - Plans: - Researcher: For independent researchers and consultants running focused studies in one workspace. Price: 299€ per month. - Team: For product teams that need collaboration, more study volume, and access to advanced research workflows. Price: 699€ per month. - Enterprise: For larger organizations that need rollout planning, governance, and room to scale across teams. Price: From 2400€ per month. ## Feature pages ### User Sphere - URL: https://meet-fred.com/user-sphere - SEO title: User Sphere for Moderated Research and Session Evidence - SEO description: Run moderated interviews and usability sessions while keeping notes, transcript, reaction signals, and gaze context connected to evidence in Fred. - Hero: Turn moderated sessions into decision-ready evidence. User Sphere keeps notes, transcript, sentiment, emotion, and gaze connected to the task and participant moment that created them, so teams can review what happened without rebuilding the story from scattered tools. - Highlights: - Moderated interviews and usability tests in one flow - Observer notes and transcript tied to the same timeline - Behavioral signals framed as reviewable evidence - Problem framing: Most moderated research stacks break the moment the session ends. Teams run the interview, gather reactions, maybe track sentiment or gaze, then still reconstruct the story from separate tools before anyone trusts the recommendation. - Value framing: They are not buying another meeting room. They are buying confidence. User Sphere matters when the live session turns into something the wider team can revisit, challenge, and carry into the next decision. - Capabilities: - Run moderated research without fragmenting the team. User Sphere gives you the room, observer workflow, and study structure without making the participant experience feel heavier. Bullets: Moderated interviews and usability tests in one flow | Observers capture notes on the session timeline | Cleaner audio protects transcript and quote quality - Capture what people say, feel, and focus on in the same place. The point is not to collect flashy signals. It is to keep those signals attached to the task, screen, and quote that produced them. Bullets: Emotion mapped to the moment that triggered it | Sentiment replay with source context preserved | Gaze and attention signals presented carefully - Carry evidence directly into the next decision. Signals do not stop at playback. Fred keeps them available for synthesis, stakeholder review, and reporting. Bullets: Findings stay linked to tasks, screens, and quotes | Evidence moves directly into Fred's reporting layer | Teams can defend recommendations with source context - Outcomes: Session evidence that survives into synthesis and stakeholder review. When session context stays connected, playback becomes a credible basis for prioritization and reporting instead of a separate archive. - Closing CTA: Turn live research into evidence your team can inspect and use. Use User Sphere to run moderated research, preserve source context, and carry the strongest evidence into Fred reports. ### Tester Panel - URL: https://meet-fred.com/tester-panel - SEO title: Tester Panel for Targeted UX Research Recruitment - SEO description: Recruit the right participants faster, preserve segment context, and keep recruitment quality tied to every study outcome in Fred. - Hero: Recruit the right participants before the decision window closes. Tester Panel gives teams a faster way to source relevant participants, keep recruitment quality high, and carry participant context into the rest of the research workflow. - Highlights: - Segment-based targeting for niche audiences - Faster participant fill without scattered ops work - Participant attributes stay linked to findings - Problem framing: Bad participant fit quietly weakens the whole study. Research teams lose speed and credibility when recruitment takes too long, attracts the wrong users, or drops participant context before synthesis starts. - Value framing: They are buying faster recruitment with stronger evidence quality. Tester Panel matters when sourcing the right audience becomes part of the product workflow, not a separate ops exercise. - Capabilities: - Define who the study actually needs before sourcing starts. Screening and segment logic stay close to the study objective, so recruitment reflects the decision you are trying to make. Bullets: Filter by demographics, behaviors, and custom criteria | Keep segment intent visible to the whole research team | Reduce generic participant matches that weaken findings - Move from target audience to active cohort without scattered recruiting ops. Recruitment workflows stay organized enough to keep timing tight without forcing the team into manual side systems. Bullets: Use Fred panel plus your own participants in one workflow | Keep launches moving during narrow decision windows | Reduce status chasing and spreadsheet-based coordination - Keep participant attributes available during analysis and reporting. The strongest recruitment workflow is the one that still matters after the sessions are done. Bullets: Retain participant segment context next to findings | Compare patterns by audience without rebuilding metadata | Defend recommendations with evidence from the right users - Outcomes: Tighter research cadence and evidence stakeholders trust more easily. When participant sourcing is faster and better aligned, studies launch sooner and the team has less explaining to do later. - Closing CTA: Bring participant sourcing into the same product where the evidence gets used. Use Tester Panel to keep recruitment quality high, timelines tight, and participant context visible all the way into the final decision. ### Thematic Analysis - URL: https://meet-fred.com/thematic-analysis - SEO title: AI-Assisted Thematic Analysis With Researcher Control - SEO description: Speed up qualitative synthesis with AI-assisted thematic analysis while keeping every theme editable, auditable, and linked to source evidence. - Hero: Synthesize qualitative evidence faster, without losing rigor. Thematic Analysis helps teams draft, refine, and validate themes while keeping every conclusion traceable to the quotes and sessions behind it. - Highlights: - AI-assisted drafts that researchers still govern - Theme-to-evidence traceability by default - Pattern continuity across studies and cycles - Problem framing: Qualitative themes fall apart when no one can audit how they were formed. Teams want faster synthesis, but they also need to understand why a theme exists, what evidence supports it, and whether it should survive review. - Value framing: They are buying synthesis speed that still feels trustworthy. Thematic Analysis matters when teams want AI assistance without giving up editability, traceability, or analyst judgment. - Capabilities: - Start with a useful draft instead of a blank analysis board. AI gives the team a structured first pass while preserving room for real interpretation and correction. Bullets: Create initial themes from transcripts, notes, and sessions | Treat AI output as draft material, not final truth | Reduce repetitive clustering work at the start of synthesis - Move from theme to source evidence without leaving the workflow. Researchers and stakeholders should be able to inspect why a theme exists at the exact moment it gets discussed. Bullets: Link themes back to quotes and session context | Keep participant and task information visible during review | Reduce audit friction when themes are challenged - Build institutional memory instead of recreating synthesis every cycle. The strongest qualitative workflows do not stop at one report. They keep patterns reusable over time. Bullets: Track recurring themes across studies and periods | Preserve analytical continuity beyond single projects | Support stronger strategic narratives from past evidence - Outcomes: Faster synthesis, better auditability, and stronger confidence in the final readout. When thematic analysis stays editable and source-linked, the team spends less time defending the method and more time discussing what to do next. - Closing CTA: Use AI-assisted thematic analysis that stays editable, inspectable, and defensible. Bring qualitative synthesis into a workflow that accelerates the first pass without weakening the final judgment. ### Insight Signals - URL: https://meet-fred.com/insight-signals - SEO title: Insight Signals for Emotion, Attention, and Session Behavior - SEO description: Review emotion, sentiment, gaze, and interaction signals in context so teams can interpret session behavior with more confidence. - Hero: See what people say, feel, and focus on in one evidence layer. Insight Signals adds emotion, sentiment, gaze, and interaction context to the session review workflow so the team can interpret behavior at the moment it happened. - Highlights: - Emotion and sentiment connected to the same participant moment - Attention and interaction patterns visible in context - Richer playback without a separate interpretation toolchain - Problem framing: Teams often leave the session with a transcript, but not with enough behavioral context. Recordings and notes explain part of what happened, but teams still miss the emotional shifts, attention cues, and interaction patterns that make behavior easier to interpret. - Value framing: They are buying a richer evidence layer, not just more metrics. Insight Signals matters when the team needs session review to answer harder questions about attention, hesitation, and emotional response. - Capabilities: - Keep reaction signals tied to the exact moment that triggered them. Behavioral interpretation is stronger when emotional and sentiment cues can be inspected next to the task, quote, and participant state. Bullets: Map reaction signals to the same point on the session timeline | Preserve source context for every observed shift | Reduce guesswork when explaining hesitation or confusion - Review where participants look, click, pause, and struggle in context. Attention and interaction patterns become useful when they help the team explain why a task succeeded, stalled, or failed. Bullets: Inspect gaze and interaction behavior near the triggering screen state | See where attention diverged from the intended flow | Spot hesitation patterns that static summaries miss - Move the most revealing signals into reporting without losing their source context. Richer playback only matters if the best moments survive into synthesis and stakeholder review. Bullets: Keep signals attached to clips, quotes, and tasks in reports | Make behavioral evidence easier to defend in product conversations | Turn playback into something the wider team can actually use - Outcomes: A sharper read on user behavior without leaving the core research workflow. When the reaction layer stays connected to the session, the team can interpret what happened with more depth and less reconstruction work. - Closing CTA: Use Insight Signals to make session playback more interpretable and more useful. Bring emotion, attention, and interaction cues into the same workflow where the team already reviews, synthesizes, and shares evidence. ### Research Repository - URL: https://meet-fred.com/research-repository - SEO title: Research Repository for Searchable, Reusable UX Evidence - SEO description: Centralize sessions, notes, reports, and evidence in a searchable research repository that keeps insights reusable across teams and cycles. - Hero: Keep research usable after the first report has already been shared. Research Repository helps teams preserve sessions, findings, and decision context in one searchable system so insights can compound instead of disappearing into folders and decks. - Highlights: - Projects, sessions, and findings in one searchable space - Evidence stays reusable across teams and cycles - Repository context supports better reporting and prioritization - Problem framing: Research loses value when teams cannot retrieve the evidence behind past decisions. Sessions, notes, reports, and clips often end up split across tools, which makes old research hard to search, compare, or reuse when the next product question arrives. - Value framing: They are buying a research memory that keeps paying off over time. Research Repository matters when the team wants evidence to stay searchable, reusable, and available during future planning and delivery cycles. - Capabilities: - Keep projects, sessions, findings, and reports in the same repository. The repository is strongest when the core artifacts of research are stored together instead of spread across disconnected systems. Bullets: Preserve context from study setup through final report | Keep evidence attached to projects and outcomes | Reduce the friction of locating the right artifact later - Make old research available during the next product decision. Searchability is valuable when the team can reuse what already exists instead of starting from zero again. Bullets: Locate prior studies, sessions, and findings faster | Compare patterns across time and project contexts | Support strategic continuity without manual digging - Reuse stored evidence in synthesis, stakeholder review, and reporting. A repository creates value when it feeds the next conversation, not when it acts like a storage archive. Bullets: Move prior evidence into new reports and decision reviews | Keep the source trail available for every reused insight | Strengthen team confidence that old knowledge is still usable - Outcomes: Less duplicated research and a stronger long-term evidence base. When prior studies stay easy to find and inspect, the team can build on what it already knows instead of repeatedly reconstructing old context. - Closing CTA: Turn past studies into a searchable evidence base the whole team can reuse. Use Research Repository to keep research operational long after the original sessions are over. ## Role pages ### UX Researcher - URL: https://meet-fred.com/ux-researcher - SEO title: UX Research Platform for UX Researchers - SEO description: Run moderated and unmoderated studies, keep evidence linked to findings, and share decision-ready research outputs with Fred. - Summary: Fred gives UX researchers one evidence chain from study setup to stakeholder decision, so findings remain traceable and defensible. - Value statement: Run every method, keep every signal, share findings stakeholders actually act on. - Key takeaways: - Keep interviews, tests, and survey evidence linked to each finding. - Share decision-ready reports without rebuilding the narrative for every team. - Speed up synthesis while keeping researcher control over final conclusions. - When to choose: - You need a single place for methods, evidence, and reporting. - Stakeholders ask for source validation in roadmap meetings. - Your team wants reusable research memory across releases. - Not ideal if: - You only need a one-off survey tool with no repository workflow. - Your process never requires stakeholder-ready evidence sharing. - Proof claims: - Every insight traces back to source evidence Context: Clips, responses, and participant context stay connected across the full research cycle. - Synthesis time is cut without cutting quality Context: AI-assisted drafts give researchers a head start — the researcher approves every final conclusion. - Reports are built for decision rooms, not archives Context: One link, all the evidence. Stakeholders can inspect sources without asking for a second deck. - Workflow: - Define the decision Document the product question, target segment, and outcome criteria before launching the study. - Collect structured evidence Run methods in Fred and keep all participant responses linked to the context they came from. - Synthesize with traceability Cluster evidence, review AI drafts, and verify every finding against its sources. - Share decision-ready outputs Publish reports with linked proof so stakeholders can validate and act immediately. - FAQs: - Q: Do I have to move my existing research out of Dovetail/Notion? A: No. Fred is designed to complement existing tools. You can import notes and data into Fred, or start new projects directly in Fred without abandoning your current workflow. - Q: Is AI-assisted analysis trustworthy for qualitative research? A: Fred's AI drafts themes and summaries as a starting point — you review, edit, and approve every conclusion before it's published. The researcher stays in full control of what goes into the final report. - Q: How does Fred handle session recordings and transcripts? A: Recordings and transcripts are stored and linked to the participant and task they came from. You can clip key moments and attach them directly to findings so the evidence chain is never broken. - Q: Can I share reports with stakeholders who don't have a Fred account? A: Yes. Fred reports can be shared via a public link so stakeholders can read findings and inspect evidence without needing a Fred account. ### Product Designer - URL: https://meet-fred.com/product-designer - SEO title: UX Research Tool for Product Designers - SEO description: Validate prototypes, capture user evidence, and walk into design reviews with findings that are easy to defend. - Summary: Fred helps product designers validate choices with user evidence that can be inspected, shared, and reused across iterations. - Value statement: Validate design decisions before they reach engineering — with evidence you can show in any review. - Key takeaways: - Run prototype validation and usability workflows without tool switching. - Attach findings to task context so design critiques stay objective. - Deliver reports that PM and engineering can validate directly. - When to choose: - Design reviews need stronger evidence, not just opinion summaries. - You iterate frequently and need reusable insight history. - Design and product teams need a shared source of truth. - Not ideal if: - You only need static mockup feedback collection. - Your team does not use research evidence in decision forums. - Proof claims: - Design recommendations stay tied to observed behavior. Context: Task-level findings and responses remain linked for review discussions. - Prototype testing and reporting are connected. Context: Outputs can be shared without recreating context in external decks. - Cross-functional teams can inspect the same evidence. Context: Design, product, and engineering align around one evidence model. - Workflow: - Scope the design question Define what decision this study should unlock and which audience matters most. - Launch prototype tests Run usability, first-click, and preference tests from the same project space. - Review linked findings Analyze friction points and evidence links directly from session outputs. - Share with stakeholders Publish a report that keeps each recommendation connected to its proof. - FAQs: - Q: Can I test Figma prototypes directly in Fred? A: Yes. You can share a Figma prototype link in Fred and run usability, first-click, or task-based tests directly against it without any additional tooling. - Q: What types of usability tests does Fred support? A: Fred supports first-click testing, task-based usability tests, open-ended prototype walkthroughs, and preference testing — all within one project workspace. - Q: How do I share test results with my PM or engineering team? A: Share a report link that includes findings, evidence clips, and participant context. Recipients don't need a Fred account to inspect the results. - Q: Can I compare two design variants side by side? A: Yes. You can run tests for multiple variants in the same project and compare findings side by side to make evidence-based design decisions. ### Product Manager - URL: https://meet-fred.com/product-manager - SEO title: User Research Platform for Product Managers - SEO description: Prioritize roadmaps with traceable user evidence, align stakeholders faster, and share decision-ready findings. - Summary: Fred helps product managers prioritize with traceable user evidence, reducing roadmap debates and accelerating stakeholder alignment. - Value statement: Frame roadmap decisions with user evidence your whole team can inspect — not another slide deck. - Key takeaways: - Frame studies around product decisions, not isolated outputs. - Inspect findings by segment with source-level transparency. - Share one report link for faster alignment across teams. - When to choose: - Roadmap discussions repeatedly stall on confidence or proof. - You need evidence-backed prioritization across squads. - Leadership asks for fast validation before committing build effort. - Not ideal if: - You only track usage analytics and never run research studies. - Roadmap decisions are fully fixed by compliance constraints. - Proof claims: - Roadmap priorities can be defended with user evidence. Context: Each recommendation can reference source sessions and participant context. - Stakeholder alignment time is reduced. Context: Teams review the same decision-ready report instead of fragmented summaries. - Release confidence improves before implementation. Context: Validation workflows connect assumptions to observed behavior early. - Workflow: - 1. Define the product decision Set the roadmap question, target users, and success threshold for the study. - 2. Run focused research Launch the right methods and capture responses with full participant context. - 3. Validate and prioritize Review linked findings to compare impact across user segments and feature options. - 4. Share and execute Distribute decision-ready reports to product, design, and engineering teams. - FAQs: - Q: How do I connect research findings to my roadmap? A: When setting up a study in Fred, you define the product decision it's meant to answer. Findings from the study stay linked to that decision context, making it straightforward to reference during roadmap prioritization. - Q: Can I run a quick study between sprints without a dedicated researcher? A: Yes. Fred provides guided templates that make it straightforward for PMs to set up and launch structured studies independently, without a research ops background. - Q: How do I share research with leadership who won't read a full report? A: Fred report links give stakeholders a focused view of key findings with source evidence a click away. There's no need to prepare a separate deck — one link covers everything. - Q: What's the fastest way to validate an assumption before sprint planning? A: Use Fred to run a short unmoderated test or survey against your target users. Most studies return actionable data within 24–48 hours, well ahead of planning windows. ## Use-case pages ### Discovery Research - URL: https://meet-fred.com/discovery-research - SEO title: Discovery Research Software for Product Teams - SEO description: Connect interviews, surveys, and exploratory studies to product decisions with structured evidence and traceable insights. - Summary: Fred supports discovery programs by keeping exploratory evidence connected, comparable, and decision-ready across multiple studies. - Value statement: Turn early-stage research into strategic direction with evidence that stays connected and reusable. - Key takeaways: - Capture context early so discovery findings stay strategic. - Compare patterns across studies instead of restarting every cycle. - Share hypotheses and implications with direct evidence backing. - When to choose: - You run recurring discovery work across product areas. - You need cross-study pattern visibility over time. - Strategy decisions require stronger evidence narratives. - Not ideal if: - You only need single-study documentation with no continuity. - Your team does not revisit prior research outcomes. - Proof claims: - Discovery context survives beyond the original study. Context: Projects keep objectives, evidence, and findings linked for reuse. - Patterns are easier to detect across research cycles. Context: Teams can compare findings without rebuilding historical context. - Strategic outputs are easier to defend. Context: Reports combine implications with direct supporting evidence. - Workflow: - Set discovery objectives Define hypotheses and target segments tied to your product strategy. - Collect multi-method evidence Run interviews, surveys, and tests while preserving context in one system. - Map patterns and implications Connect recurring themes across studies with traceable supporting data. - Share strategic guidance Publish decision-ready outputs that link insights to concrete product actions. - FAQs: - Q: Which methods can I use for discovery in Fred? A: You can combine interviews, surveys, usability tests, and other methods in one repository. - Q: Can I compare findings across studies? A: Yes. Fred keeps study outputs connected so teams can detect patterns and shifts over time. - Q: How does Fred help with stakeholder communication? A: Fred reports connect discovery findings to source evidence and implications, making strategic conversations clearer. - Q: Is discovery data searchable later? A: Yes. Teams can revisit and reuse prior evidence instead of rebuilding context manually. ### Usability Testing - URL: https://meet-fred.com/usability-testing - SEO title: Usability Testing Platform with Evidence Links - SEO description: Run moderated and unmoderated usability tests, analyze friction points quickly, and share findings linked to real sessions. - Summary: Fred helps teams run usability tests that produce fix-ready findings with direct links to sessions, tasks, and participant context. - Value statement: Launch tests quickly and keep every finding linked to real behavior, tasks, and participant context. - Key takeaways: - Capture moderated and unmoderated evidence in one workflow. - Prioritize usability issues with source-linked proof. - Share implementation-ready recommendations quickly. - When to choose: - You need repeatable usability validation before release. - Engineering asks for direct evidence behind issue severity. - You want faster transition from session to fix decision. - Not ideal if: - You only need simple click-count analytics with no qualitative depth. - You do not require task-level evidence traceability. - Proof claims: - Usability findings remain tied to observed behavior. Context: Task outcomes, recordings, and participant context are linked. - Issue prioritization becomes clearer for implementation teams. Context: Reports surface recurring friction with accessible source evidence. - Testing and delivery cycles are more efficient. Context: Teams move faster from validation to fix-ready decisions. - Workflow: - Configure scenarios and audience Define tasks and participant criteria based on the UX decision at hand. - Run sessions Collect behavior and responses in moderated or unmoderated formats. - Analyze friction patterns Review linked evidence to identify recurring usability barriers. - Share fix-ready recommendations Publish clear findings with source links so implementation teams can act quickly. - FAQs: - Q: Can I run moderated and unmoderated tests in the same project? A: Yes. Fred supports both approaches and keeps evidence connected across methods. - Q: How quickly can I get usability results? A: Most teams begin seeing actionable session data within hours of launch. - Q: Can stakeholders inspect session evidence directly? A: Yes. Reports can include links to recordings, task outcomes, and participant context. - Q: Does Fred support mobile and desktop testing? A: Yes. Fred supports usability studies across responsive experiences and device types. ### Report Findings - URL: https://meet-fred.com/report-findings - SEO title: Research Reporting Software with Traceable Evidence - SEO description: Build stakeholder-ready research reports where every finding links to source evidence, clips, and participant context. - Summary: Fred turns research outputs into stakeholder-ready reports where each finding stays connected to source evidence and decision context. - Value statement: Share research reports that are easy to trust because every claim is connected to evidence. - Key takeaways: - Build reports around decision implications, not raw notes. - Link claims to clips, responses, and participant context. - Share one artifact across teams without reformatting. - When to choose: - Stakeholders need inspectable evidence during planning meetings. - Your team spends too much time assembling report decks. - You want repeatable reporting standards across studies. - Not ideal if: - You only need raw exports and no stakeholder communication layer. - Your process does not require decision-ready synthesis outputs. - Proof claims: - Findings can be verified quickly by non-research stakeholders. Context: Reports expose evidence links directly within each key conclusion. - Reporting overhead is reduced. Context: Teams reuse structured templates instead of rebuilding narratives manually. - Decision meetings stay focused on action. Context: Implications and source evidence are presented in one artifact. - Workflow: - Select decision context Frame the report around the decision, audience, and key questions. - Curate linked findings Add prioritized findings with direct evidence references. - Add implications and actions Document what each finding means and what should happen next. - Share and align Send one report link that stakeholders can inspect and discuss confidently. - FAQs: - Q: Can I customize Fred report structures? A: Yes. You can tailor report sections while keeping findings connected to supporting evidence. - Q: Can reports be shared outside the research team? A: Yes. Reports are built for cross-functional stakeholders and can be shared as links or exports. - Q: How does Fred keep report findings credible? A: Each finding can reference source sessions, responses, and participant context for fast validation. - Q: Can teams collaborate on reporting? A: Yes. Fred supports collaborative workflows so multiple contributors can refine outputs together. ## Legal pages - Privacy Policy: https://meet-fred.com/privacy-policy - Covers personal data, analytics, trackers, AI emotion analysis, eye tracking, and third-party services. - Cookie Policy: https://meet-fred.com/cookie-policy - Covers cookie categories, consent handling, and third-party tracking or infrastructure services. - Terms and Conditions: https://meet-fred.com/terms-and-conditions - Covers use of the service, subscriptions, acceptable use, user content, and product-specific terms. ## Notes for LLM consumers - Prefer the canonical page URLs above when citing Fred. - Treat live page copy as the source of truth if it conflicts with older summaries. - Use pricing and legal pages for policy or commercial details instead of inferring from feature copy.