Trisynx analyzes speech, slides, diagrams, equations, and code so recruiters, students, and teams receive timestamped notes they can trust.
Public beta supports individual, non-live YouTube videos up to 90 minutes.
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Example Output
Lecture Input
Original lecture video
Multimodal understanding
Speech • Slides • OCR • Visual reasoning
Generated Notes
Real export produced by Trisynx
How raw video becomes actionable knowledge.
Raw lectures, meetings, and tutorials enter the system.
Speech is aligned into searchable, timestamped text.
Slides, diagrams, and screen context are interpreted.
Audio and visual signals are reconciled into one model.
Clean notes, snippets, and decisions are generated.
Features
Trisynx listens, watches, and structures the lecture as one connected source instead of treating the video like a transcript alone.
Speech is captured with timestamps and speaker context, giving every later summary a reliable textual backbone.
“Gradient descent updates each weight by moving against the slope of the loss function.”
Diagrams, equations, and transitions are detected before the most useful frames are placed into the notes.
On-screen snippets are preserved as readable, copyable blocks instead of flattened screenshots.
01 def softmax(logits):
02 exp = np.exp(
03 logits - logits.max()
04 )
05 return exp / exp.sum()Transcript and visual evidence are fused into concise sections without dropping the reasoning chain.