How Signum works

Voice based narrative input

Athletes reflect in their own words, on a rhythm that fits the team.

Signum collects short voice notes and written reflections from athletes. Prompts are designed to invite genuine reflection: how they’re feeling, what’s working, what’s not, rather than survey boxes. Voice captures tone and emphasis that text alone can miss, which helps the system understand context without requiring long essays.

• Reflections, not surveys. Open ended prompts let athletes say what matters to them instead of choosing from predefined options.
• Anonymous by design. Responses are not attributed to individuals in any output coaches or staff see. The goal is to surface team level patterns and reduce fear of speaking up.
• Cadence that fits the season. Regular check ins can be weekly or biweekly; deeper reflection moments can be scheduled around key phases (e.g., pre season, post competition). Teams configure what works for them.

AI powered narrative sensing

Tone, language, and emotional patterns are analyzed over time, not as one off snapshots.

The system uses multimodal AI to interpret what athletes share: not only the words they use but the way they’re said. Sentiment, stress indicators, and recurring themes are tracked across responses and over time, so trends become visible (e.g., a gradual shift in how workload or communication is described) rather than relying on a single moment in time.

• Tone and language. Voice and text are analyzed for emotional tone, certainty, and consistency with prior responses, informed by established research in language and affect.
• Themes over time. Recurring topics (trust, communication, workload, belonging) are identified and trended so staff can see whether things are improving or need attention.
• No individual profiling. Analysis is aimed at team level and subgroup patterns. The system is not built to label or diagnose individual athletes.

Privacy preserving analysis

No surveillance. No individual diagnosis. Aggregated, actionable insight only.

Signum is built so that coaches and administrators see team level indicators and trends, not who said what. Data is processed in a way that supports pattern recognition across the group while preventing reidentification. The aim is to improve culture and wellbeing without creating new risks for athletes who speak up.

• No surveillance. The product is not designed for real time monitoring or tracking of individuals. It is a reflection and insight tool, not a compliance or oversight mechanism.
• No individual diagnosis. Outputs do not attach mental health or performance labels to specific athletes. They surface themes and trends so that staff can respond with appropriate support and policy, including referrals to qualified professionals when needed.
• Evidence aligned safeguards. Design choices are informed by sports psychology and safeguarding research, with ongoing input from experts in athlete welfare and equity.

Actionable outputs

Team level indicators, trends, and clear next steps for coaches.

What staff see is designed to be useful in practice: high level culture and wellbeing indicators, how they’re changing over time, and concrete action items. The goal is to close the loop: athletes share, the system synthesizes, and coaches can respond in ways that athletes can recognize, so trust in the process grows.

• Team level indicators. Dashboards show aggregate culture and wellbeing metrics (e.g., trend direction, theme strength) so staff can see the big picture without drilling into individual identities.
• Trends over time. Comparisons across weeks or phases help distinguish one off spikes from sustained shifts, so responses can be proportionate and evidence based.
• Coach action items. Synthesized recommendations (e.g., “Consider 1:1 check ins on role clarity,” “Revisit load for athletes reporting burnout”) give staff a starting point for follow up without exposing who said what.

Continuous vs episodic monitoring

Built for prevention and trend spotting, not only crisis response.

Signum supports both ongoing rhythm and targeted deep dives. Regular check ins create a baseline and make it easier to notice when something changes. Episodic moments (e.g., after a major competition or before a break) can be used to capture richer reflection when it’s most relevant. Together, this helps programs act earlier and reduce reliance on reactive, crisis driven interventions.