sub-1ms-per-frame on cpu is the easy number to benchmark — on real-time agent pipelines the harder thing is frame jitter compounding across the STT→LLM→TTS hop, where any lookahead the suppressor needs eats the latency budget you saved. gain-mask + deep filtering also has the target-speaker vs blind-separation question lurking when two voices overlap mid-utterance.
About Hush on Product Hunt
“Open-source noise suppression for voice AI agents”
Hush launched on Product Hunt on June 23rd, 2026 and earned 186 upvotes and 26 comments, placing #6 on the daily leaderboard. Hush removes competing voices, background noise, and audio interference from real-time calls so your voice AI agents always hear what matters.
On the analytics side, Hush competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Hush performed against the three products that launched closest to it on the same day.
Who hunted Hush?
Hush was hunted by Hasan Ali. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Hush including community comment highlights and product details, visit the product overview.
Hasan Ali
sub-1ms-per-frame on cpu is the easy number to benchmark — on real-time agent pipelines the harder thing is frame jitter compounding across the STT→LLM→TTS hop, where any lookahead the suppressor needs eats the latency budget you saved. gain-mask + deep filtering also has the target-speaker vs blind-separation question lurking when two voices overlap mid-utterance.