Designing Scryon’s AI call experience from first principles
Scryon
YEAR
2026
PROJECT OVERVIEW
Scryon came to us with an ambitious AI capability spanning recording, transcription, analysis, and action management. We turned that broad requirement into a clear, trustworthy mobile experience.
Owl led product strategy, information architecture, UX/UI, prototyping, and the design system—creating a coherent Android product and a reusable foundation for future releases.
Branding — to give Scryon a visual identity
Before shaping the product flows, we gave Scryon a recognisable identity. Competitive analysis showed a category crowded with literal phone symbols and generic AI cues, so the system needed to feel immediate without becoming interchangeable.
The wordmark turns the ‘o’ into a compact call-and-signal symbol. That idea carries into an app icon that combines calling, audio, notes, and notification—making the product’s promise visible before a user opens it.

Design systems — a smart agentic token harness
Semantic tokens connect brand, surface, text, stroke, feedback, and interaction roles across light and dark themes. Reusable patterns for call rows, processing states, actions, navigation, and errors let the product respond consistently as AI states change.
Shared Colours / Semantic Colours
Type Ramp
24 / 29 · Bold · +0.24Turn every call into clarity.
20 / 24 · Medium · +0.20Summary, outcome, next steps.
16 / 22 · Medium · +0.16A transcript is useful. A transcript that knows what happens next is better.
14 / 20 · Regular · +0.14Vartika Singh · 5:30 PM · Jun 19
12 / 14 · Regular · +0.12Assigned to Praveen Kumar
Fetch data — analysing the capabilities
We designed one entry point for recent calls, existing recordings, and imported audio. Contextual permission prompts request call data or phone storage only when needed, keeping setup light while making the source and status of every file clear.


Transcript generation — making asynchronous progress easy to trust
The flow covers uploading, transcribing, ready, failed, and retry states without blocking the call library. Once complete, summary and outcome lead the hierarchy while the player and verbatim transcript remain close enough for verification.




User action — carrying conversation context into the next step
Extracted actions stay linked to the call, participant, owner, and supporting detail. Users can review or edit them in context, manage them in a focused list, and move directly into follow-up through actions such as call or email.



Design impact
One clear product model
Recording, transcription, analysis, and actions now follow one predictable flow.
Trust in every state
Progress, failure, retry, and privacy controls make AI behaviour visible and recoverable.
Ready to scale
Reusable tokens and components reduce rework as the product grows.
We transformed a capability-heavy requirement into a product people can understand, trust, and extend.








