Deepgram

Deepgram

Voice AI platform for developers.

4.8
β€’65 reviewsβ€’

1.7K followers

Enterprise Voice AI platform designed for developers building voice-first products using speech-to-text, text-to-speech, or speech-to-speech APIs. Over 200,000 developers build with Deepgram's voice-native foundational models, accessed via APIs or self-managed software. Start building with $200 in free credits!

This is the 10th launch from Deepgram. View more
Deepgram Saga

Deepgram Saga

The Voice OS for Developers
Control your dev workflow with your voice. End the mentally expensive context switching that takes up almost half your day by skipping the alt-tabbing, clicking, and typing. Just speak to deploy, document, or debug. Powered by MCP, Saga keeps you in flow.
Deepgram Saga gallery image
Deepgram Saga gallery image
Deepgram Saga gallery image
Deepgram Saga gallery image
Deepgram Saga gallery image
Deepgram Saga gallery image
Deepgram Saga gallery image
Launch Team / Built With

What do you think? …

Sharon Yeh
Maker
πŸ“Œ
Hey Product Hunt Community! πŸ‘‹ Sharon here, PM at Deepgram. We’ve been building Saga for the past few months to solve a pain that’s personal for most of us in PM and Engineering: too many tools, too many tabs, too much friction. Most AI copilots still need help translating your intent into precise prompts. Other voice assistants are not well integrated into the typical dev stack. So we thought: what if you could speak your commands into workflows? That’s Saga. It listens, understands, and actually executes. We built it for developers who are already using Cursor, Windsurf, Jira, Slack, Linear (and more), and we’d love your feedback as we expand across modalities, operating systems and breadth of tasks. πŸ™Œ We’d love to hear from you on: One thing you wish you could do just by speaking? What MCP action is your favorite? Thanks for checking out Saga! We’ll be around all day in the comments and our Discord channel: https://discord.com/invite/deepgram. β€”Sharon (and the Deepgram team)
Chan Bartz

In your video you say that the AI can take in vague instructions and turn into precise instructions. Models like o1 and o3 do that sort-of fine, but the question holds: can it be done in a truly useful way? Would appreciate so much some use cases and other examples to see how it works in your cool app

Sharon Yeh

@chan_bartz Great question! Yes, models like o1 and o3 can kind of handle vague input, but they’re inconsistent without the right prompt structure. What Saga does is convert your fuzzy, natural speech into a clean, structured instruction that actually works when passed into tools like Cursor, Replit, or Windsurf. It acts like a pre-processor that speaks β€œLLM,” so you don’t have to.

Example 1:

You say: β€œMake a helper to format a date string”

Saga rewrites it into:

Create a helper function to format a date string. The function should:

1. Accept a date string as input.

2. Convert the date string into a more readable format (e.g., "YYYY-MM-DD" to "Month Day, Year").

3. Handle invalid date inputs gracefully by returning an error message or null.

Then pipes that into Cursor and gets back usable code on the first try.

Example 2:

You say: β€œAdd error handling to this function”

Saga rewrites it into something like:

Add error handling to the specified function. Ensure that you include:

1. Try-catch blocks to manage exceptions.

2. Clear error messages for debugging purposes.

3. Return appropriate responses or throw errors based on the situation.

We’re seeing devs use it to avoid prompt tinkering and get more consistent results from AI coding tools.

Would love to see how it works for you when you try it out!

Tiffany Hakseth

Tried it out and this is awesome 🀩

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