built to be versatile and human
built to be versatile and human
built to be versatile and human
voice agents, ivr, customer support, dubbing. hear silk across every use case."
the models
the models
the models
mulberry
velvet & calm
• Starts speaking in 162 ms, faster than a blink.
• Creates the voice you describe instantly.
muga
warm & conversational
• 24 kHz studio-quality audio
• 6 built-in emotions (Happy, Sad, Angry, Excited, Whisper, Neutral)
mulberry
warm & conversational
• Starts speaking in 162 ms, faster than a blink.
• Creates the voice you describe instantly.
muga
velvet & calm
• 24 kHz studio-quality audio
• 6 built-in emotions (Happy, Sad, Angry, Excited, Whisper, Neutral)
mulberry
velvet & calm
• Starts speaking in 162 ms, faster than a blink.
• Creates the voice you describe instantly.
muga
warm & conversational
• 24 kHz studio-quality audio
• 6 built-in emotions (Happy, Sad, Angry, Excited, Whisper, Neutral)
built for natural, real-time voice applications
built for natural, real-time voice applications
built for natural, real-time voice applications
mulberry responds in 162ms, the fastest ttfb on the market, at ₹0.40/min (~$0.005/min).
mulberry responds in 162ms, the fastest ttfb on the market, at ₹0.40/min (~$0.005/min).
fast enough to respond
fast enough to respond
speech starts coming back as little as 162ms. the conversation does not have to wait.
describe the voice. skip the catalogue.
describe the voice. skip the catalogue.
write the age, accent, pitch, pace, timbre and character you need.
hindi. english. hinglish. same person.
hindi. english. hinglish. same person.
change the language halfway through without changing the voice behind it.
pay for what gets spoken.
pay for what gets spoken.
top up credits once. burn them down request by request.
implement silk in your project instantly
get a key. send a request. receive 24 khz audio.
from rumikai import Rumik client = Rumik() # muga: expressive, steer with an inline tone tag audio = client.speech.create(text="[happy] Namaste! Kaise hain aap?", model="muga") audio.save("hello.wav") # mulberry: faster, steer with a description + preset speaker audio = client.speech.create( text="Hi there, how can I help you today?", model="mulberry", description="a warm 30s female voice, conversational pacing", speaker="speaker_2", ) audio.save("greeting.wav")
from rumikai import Rumik client = Rumik() # muga: expressive, steer with an inline tone tag audio = client.speech.create (text="[happy] Namaste! Kaise hain aap?", model="muga") audio.save("hello.wav") # mulberry: faster, steer with a description + preset speaker audio = client.speech.create( text="Hi there, how can I help you today?", model="mulberry", description="a warm 30s female voice, conversational pacing", speaker="speaker_2", ) audio.save("greeting.wav")
from rumikai import Rumik client = Rumik() # muga: expressive, steer with an inline tone tag audio = client.speech.create(text="[happy] Namaste! Kaise hain aap?", model="muga") audio.save("hello.wav") # mulberry: faster, steer with a description + preset speaker audio = client.speech.create( text="Hi there, how can I help you today?", model="mulberry", description="a warm 30s female voice, conversational pacing", speaker="speaker_2", ) audio.save("greeting.wav")
silk keeps the voice intact even through language changes
silk keeps the voice intact even through language changes
silk keeps the voice intact even through language changes
meet the teams already speaking through silk
meet the teams already speaking through silk
meet the teams already speaking through silk
curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.
curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.
100 + hours in 2 days
100 + hours in 2 days
curvet put mulberry and muga directly inside its ai workflow canvas. within two days, teams generated voices across education, design, crm and enterprise workflows.
100 + hours in 2 days
curvet ai
snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.
snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.
snap tv
snaptv uses silk to give a voice to bite-sized lessons made for how india learns, quickly, on mobile, in simple hindi and easy english.
jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.
jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.
jee concepts are difficult enough. monk learning uses silk to turn dense explanations into clear, natural voice for aspirants preparing every day.
monk learning
faqs
faqs
faqs
