Should I Build It Should I Build It
02 Jun 2025
Artificial Intelligence API Developer Tools

An API or SaaS that takes voice input and returns structured commands ...

...or API calls based on a user’s backend schema or command set. Ideal for devs building voice-based apps, home automations, or wearable devices.

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Freemium

People love using similar products but resist paying. You’ll need to either find who will pay or create additional value that’s worth paying for.

Should You Build It?

Build but think about differentiation and monetization.

Your are here

You're entering a market with a decent amount of existing solutions (n_matches = 15), so differentiation will be key. The general idea of turning voice into structured data or API calls resonates, especially for developers working on voice-based apps, home automation, or wearable devices. However, it seems like people want to use these types of products (medium engagement, avg n_comments = 10), but don't want to pay for them, putting you squarely in the 'Freemium' category. The challenge here is to figure out how to extract value, either through premium features or by targeting a different paying customer base. The criticism for similar products mainly revolves around pricing, latency, voice customization, privacy issues, and safety concerns. It seems like the key is going to be a great free tier, with compelling reasons to upgrade. Differentiating on features (e.g. better voice models, better language support) can help you stand out in an increasingly crowded market. Given the issues with competitors, safety, fraud and misuse are also potential concerns to be addressed early on.

Recommendations

  1. First, deeply understand who gets the most value from the free version of your API. Analyze usage patterns to identify power users or specific use cases that heavily rely on your service. Knowing this will help you craft your premium offering.
  2. Next, create premium features that significantly enhance the experience for those high-value users. Consider features like lower latency, higher rate limits, custom voice models, enhanced security, or detailed analytics. Frame these features as essential for serious developers or larger-scale applications.
  3. Explore the possibility of charging teams rather than individuals. Small teams building voice-enabled applications might be willing to pay for a collaborative platform with shared resources and centralized management. This can also simplify licensing and billing.
  4. Offer personalized help or consulting services to enterprise clients. Some businesses may need assistance with integrating your API into their existing infrastructure or customizing it for specific use cases. Providing hands-on support can be a valuable premium offering.
  5. Test different pricing approaches with small groups of users before a full launch. Experiment with tiered pricing, usage-based pricing, or feature-based pricing to find the optimal balance between revenue and user adoption. Collect feedback on perceived value and price sensitivity.
  6. Address latency concerns head-on. Many users of similar products complained about latency. Optimize your API for speed and provide clear latency benchmarks. Transparency here can build trust and attract developers who need real-time performance.
  7. Prioritize security and prevent misuse. Given the concerns about safety and potential misuse, implement robust security measures and content moderation policies. Clearly communicate these measures to users to build confidence in your platform. Include clear guidelines on not using the API for fraud.
  8. Actively solicit feedback on voice customization. While you may not be able to satisfy every request, demonstrating a willingness to improve voice models and language support can set you apart from competitors and show users you're listening.
  9. Consider an open-source strategy for parts of your stack, especially given the popularity of open source voice assistants. This can attract community contributions, build trust, and provide a competitive edge.

Questions

  1. Considering the 'Freemium' nature of this market, what are the non-obvious ways you can create value that compels users to upgrade beyond the free tier? Are there specific industries or applications where the paid features become indispensable?
  2. Given the reported issues with latency and voice customization in similar products, what specific technical choices will you make to ensure low latency and high-quality, customizable voice models from day one? How will you build this into your architecture?
  3. Considering the sensitivity around voice data and potential for misuse, what proactive steps will you take to ensure user privacy and prevent fraudulent activities using your API? How will you communicate these safeguards to your users to build trust?

Your are here

You're entering a market with a decent amount of existing solutions (n_matches = 15), so differentiation will be key. The general idea of turning voice into structured data or API calls resonates, especially for developers working on voice-based apps, home automation, or wearable devices. However, it seems like people want to use these types of products (medium engagement, avg n_comments = 10), but don't want to pay for them, putting you squarely in the 'Freemium' category. The challenge here is to figure out how to extract value, either through premium features or by targeting a different paying customer base. The criticism for similar products mainly revolves around pricing, latency, voice customization, privacy issues, and safety concerns. It seems like the key is going to be a great free tier, with compelling reasons to upgrade. Differentiating on features (e.g. better voice models, better language support) can help you stand out in an increasingly crowded market. Given the issues with competitors, safety, fraud and misuse are also potential concerns to be addressed early on.

Recommendations

  1. First, deeply understand who gets the most value from the free version of your API. Analyze usage patterns to identify power users or specific use cases that heavily rely on your service. Knowing this will help you craft your premium offering.
  2. Next, create premium features that significantly enhance the experience for those high-value users. Consider features like lower latency, higher rate limits, custom voice models, enhanced security, or detailed analytics. Frame these features as essential for serious developers or larger-scale applications.
  3. Explore the possibility of charging teams rather than individuals. Small teams building voice-enabled applications might be willing to pay for a collaborative platform with shared resources and centralized management. This can also simplify licensing and billing.
  4. Offer personalized help or consulting services to enterprise clients. Some businesses may need assistance with integrating your API into their existing infrastructure or customizing it for specific use cases. Providing hands-on support can be a valuable premium offering.
  5. Test different pricing approaches with small groups of users before a full launch. Experiment with tiered pricing, usage-based pricing, or feature-based pricing to find the optimal balance between revenue and user adoption. Collect feedback on perceived value and price sensitivity.
  6. Address latency concerns head-on. Many users of similar products complained about latency. Optimize your API for speed and provide clear latency benchmarks. Transparency here can build trust and attract developers who need real-time performance.
  7. Prioritize security and prevent misuse. Given the concerns about safety and potential misuse, implement robust security measures and content moderation policies. Clearly communicate these measures to users to build confidence in your platform. Include clear guidelines on not using the API for fraud.
  8. Actively solicit feedback on voice customization. While you may not be able to satisfy every request, demonstrating a willingness to improve voice models and language support can set you apart from competitors and show users you're listening.
  9. Consider an open-source strategy for parts of your stack, especially given the popularity of open source voice assistants. This can attract community contributions, build trust, and provide a competitive edge.

Questions

  1. Considering the 'Freemium' nature of this market, what are the non-obvious ways you can create value that compels users to upgrade beyond the free tier? Are there specific industries or applications where the paid features become indispensable?
  2. Given the reported issues with latency and voice customization in similar products, what specific technical choices will you make to ensure low latency and high-quality, customizable voice models from day one? How will you build this into your architecture?
  3. Considering the sensitivity around voice data and potential for misuse, what proactive steps will you take to ensure user privacy and prevent fraudulent activities using your API? How will you communicate these safeguards to your users to build trust?

  • Confidence: High
    • Number of similar products: 15
  • Engagement: Medium
    • Average number of comments: 10
  • Net use signal: 8.6%
    • Positive use signal: 12.4%
    • Negative use signal: 3.8%
  • Net buy signal: -0.6%
    • Positive buy signal: 0.8%
    • Negative buy signal: 1.4%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

OSS voice based conversational API with <1sec latency and other nuances

27 Mar 2024 Artificial Intelligence API

Hi Hackernews, we're Maitreya, Prateek and Marmik. Over the past few months we've been working on building a platform to build, scale and monitor voice based LLM applications.Demo (https://www.youtube.com/watch?v=OSrOmyR7oQs)1⃣ Open Source orchestration: We're open-sourcing our orchestration to quickly setup and create LLM based voice driven conversational applications https://github.com/bolna-ai/bolna/2⃣ Hosted API Platform: Exposing our managed solution via APIs to build voice driven applications https://docs.bolna.dev/api-reference/introduction3⃣ Normal LLM telemetry tools won't work in giving visibility for audio bytes in and out of the system across multiple models. So, we've build our own observability layer fully integrated with the dashboard as well.4⃣ 3 different modes for creating agents - Lite (Intent classification based) (useful for basic calls and really pocket friendly). Normal (<2sec latency but only one llm call means it's cheaper than nitro), Nitro (<1sec latency and but multiple llm calls means really expensive)5⃣ Follow up tasks like webhook integration, summarisation, and extraction.6⃣ Modular and extensible architecture, which means connecting two different llms yet parallel paths(for example code and english to automate leetcode screening interviews) is really easy, albeit you'll initially need some hacking until we're able to release that to both hosted and open source versions)Over the next weeks we'd be doing a lot of small releases here starting with a hindi SLM for lead qualification and sales within next 10 days.We'd love to welcome you guys to our community, give us feedback and together build "langchain for voice first AI applications".

Avatar
8
8
Relevance

SpeakStruct – Turn voice into consistent structured data

12 Jun 2024 Artificial Intelligence

Hey folks,Built SpeakStruct to allow users to setup templates to turn voice input into consistent, structured output. Use cases from feedback I've had are customer support, coaching/check-ins, note taking, etc.Although there is a pricing section, signing up is free (no CC required). If you don't want to sign up, a demo is available here (sale-sy demo, but shows the product). https://app.arcade.software/share/nWm35szNPwD3PpH4eUSpOpen to all feedback.

Users questioned the target audience for loud music over voiceover, noted that the product aligns with future needs, and inquired if Whisper is used at the backend.

The loud music over the voiceover makes the product resemble a scam.

Avatar
11
3
-33.3%
3
11
Relevance

Speech-to-speech playground for OpenAI's new Realtime API

02 Oct 2024 Artificial Intelligence API Developer Tools

Hi there - Ben from LiveKit here!If you’re curious about OpenAI’s brand-new Realtime API and speech-to-speech model, check out this hosted playground and play with the model yourself. If you’d like to learn more about how this came together, read on.If you’re like me, you’ve probably been wondering what novel things a model like this can do in an API setting with unfettered access to the system prompt and other parameters. I’ve been fortunate to have had early access through my work at LiveKit, where we’ve built open-source developer tooling that makes deploying this model in a production app as simple as possible.I thought it would also be fun to build a “playground” environment, partially to dogfood our own tooling but largely because I just wanted to play with the model. This playground is freely available to anyone to try, and comes loaded up with a bunch of fun demos of the model’s unique capabilities that I’ve put together.What blew my mind is how much mileage you can get out of the system prompt alone in this API. Here are some use-cases that are at least halfway to a complete MVP:- "Customer Support": An complete phone support agent for the playground- "Spanish Tutor": A bilingual language-learning demo- "Meditation Coach": It can actually pause and resume speech all on its own as it guides you through a meditation routineAlso some fun (and a bit irreverent…) demos of its style and non-verbal capabilities:- "Smoker’s Rasp": It can cough and speak like it’s been smoking three packs a day for 30 years (my favorite, lol)- "Unconfident Assistant": Umms, buts, and more - surprisingly lifelike- "Opera Singer": The best singing demo I’ve been able to compose (but still not quite what they showed off back in May…)The playground doesn’t store anything anywhere besides your browser but you can share anything fun you put together with a link that encodes your config into URL params.For now - anyone can use this playground to access the model and give it a spin (session limit 5min). In the coming days when more people have access to the underlying API, I’ll update it to require you bring your own OpenAI API Key.Lastly - if you’re even more curious how this was built or want to tweak or adapt it for yourself, the whole project and every dependency is open-source (link in footer!).

Users are inquiring about the product's capabilities, such as playing Doom and non-verbal functions. Some users face access issues due to 'Rate Limit Exceeded' errors, while others mention the need to purchase tokens. Positive feedback includes praise for the product when it works. Questions about legacy voice mode suggest interest in text-to-speech features.

Users have criticized the product for requiring the purchase of tokens, experiencing rate limit issues, and encountering errors when the rate limit is exceeded. Additionally, there are complaints about non-verbal capabilities not functioning and the product only offering a legacy voice mode.

Avatar
10
7
7
10
Relevance

VoiceXD - Design and build custom AI assistants

14 Jun 2023 Artificial Intelligence Virtual Assistants Messaging

VoiceXD is a collaborative no-code platform for creating AI Assistants customized to your logic, rules, data, and use cases which can be published to our growing list of supported messaging channels like Whatsapp, SMS, etc.

Users expressed excitement and congratulations on the Product Hunt launch, praising the product's beautiful design and accessibility for assistant-user interactions. There is appreciation for the team's work in enabling cross-functional collaboration and excitement for the community. Many are looking forward to the future development of the well-built platform, particularly Voice XD.

Avatar
87
4
75.0%
4
87
75.0%
Relevance

Enabling end-to-end LLM-based voice driven conversational applications

13 Dec 2023 Artificial Intelligence GitHub

Hey everyone on HN! We recently spent the past couple of weeks building out an end-to-end platform which can plug-in multiple models (both open/closed-source) to create voice driven conversational applications.We've tried to make the process simple & concise through documentation. Feel free to try it out and provide feedback.We will be launching a dashboard in the coming week for monitoring and analytics alongwith more open source models.Let us know what you all think. (if you want to contribute, we have tons of features planned - do let us know)

Avatar
5
5
Relevance

An open source framework for voice assistants

13 May 2024 Open Source

I've been obsessed for the past ~year with the possibilities of talking to LLMs. I built a bunch of one-off prototypes, shared code on X, started a Meetup group in SF, and co-hosted a big hackathon. It turns out that there are a few low-level problems that everybody building conversational/real-time AI needs to solve on the way to building/shipping something that works well: low-latency media transport, echo cancellation, voice activity detection, phrase endpointing, pipelining data between models/services, handling voice interruptions, swapping out different models/services.On the theory that something like a LlamaIndex or LangChain for real-time/conversational AI would be useful, a few of us started working on a Python library for voice (and multimodal) AI assistants/agents.So ... Pipecat: a framework for building things like personal coaches, meeting assistants, story-telling toys for kids, customer support bots, virtual friends, and snarky social bots.Most of the core contributors to Pipecat so far work together at our day jobs. This has been a kind of "20% time" thing at our company. But we're serious about welcoming all contributions. We want Pipecat to support any and all models, services, transport layers, and infrastructure tooling. If you're interested in this stuff, please check it out and let us know what you think. Submit PRs. Become a maintainer. Join the Discord. Post cool stuff. Post funny stuff when your voice agent goes completely off the rails (as mine sometimes do).

Users are excited about the open source aspects and advancements in voice technology, particularly with GPT-4o and its real-time capabilities. There's a demand for improved speech-to-speech models and audio-to-audio functionality, with some users noting stagnation in voice assistant development and suggesting qualitative improvements. Questions about specific functionalities like speech-to-speech and live translation indicate a keen interest in practical applications. Comments on hardware and the desire for open source voice assistants reflect a push for more customizable solutions. Overall, the project is seen as technically impressive, with potential for future applications.

Users criticize the product for lacking a direct speech-to-speech model, high latency, and poor performance compared to competitors like Siri and Google Assistant, which are also noted to have worsened. The product's reliance on multiple agents, inability to handle complex or two-part requests, and issues with microphones and respecting settings are highlighted. Users suggest improvements in audio-to-audio models, better documentation, and addressing stagnation. Open source options and monetization strategies are questioned, and specific issues with Whisper and multimodal models are mentioned.

Avatar
346
35
0.0%
-2.9%
35
346
11.4%
Relevance

Project S.A.T.U.R.D.A.Y. – open-source, self hosted, J.A.R.V.I.S.

02 Jul 2023 Artificial Intelligence GitHub Audio

Welcome to Project S.A.T.U.R.D.A.Y. This is a project that allows anyone to easily build their own self-hosted J.A.R.V.I.S-like voice assistant. In my mind vocal computing is the future of human-computer interaction and by open sourcing this code I hope to expedite us on that path.I have had a blast working on this so far and I'm excited to continue to build with it. It uses whisper.cpp [1], Coqui TTS [2] and OpenAI [3] to do speech-to-text, text-to-text and text-to-speech inference all 100% locally (except for text-to-text). In the future I plan to swap out OpenAI for llama.cpp [4]. It is built on top of WebRTC as the media transmission layer which will allow this technology to be deployed anywhere as it does not rely on any native or 3rd party APIs.The purpose of this project is to be a toolbox for vocal computing. It provides high-level abstractions for dealing with speech-to-text, text-to-text and text-to-speech tasks. The tools remain decoupled from underlying AI models allowing for quick and easy upgrades when new technology is realeased. The main demo for this project is a J.A.R.V.I.S-like assistant however this is meant to be used for a wide variety of use cases.In the coming months I plan to continue to build (hopefully with some of you) on top of this project in order to refine the abstraction level and better understand the kinds of tools required. I hope to build a community of like-minded individuals who want to see J.A.R.V.I.S finally come to life! If you are interested in vocal computing come join the Discord server and build with us! Hope to see you there :)Video demo: https://youtu.be/xqEQSw2Wq54[1] whisper.cpp: https://github.com/ggerganov/whisper.cpp[2] Coqui TTS: https://github.com/coqui-ai/TTS[3] OpenAI: https://openai.com/[4] llama.cpp: https://github.com/ggerganov/llama.cpp

Users suggest improvements like adding a J.A.R.V.I.S. explanation, integrating with Alexa-like services, and including hotword detection. There's interest in the product's handling of memory and conversation, and requests for demos and latency benchmarks. Skepticism exists about vocal computing's future, with some believing telepathic interaction is next. Concerns are raised about privacy with 24-hour mic/camera access. Technical queries about speech recognition and response generation are discussed, with a note on GPUs outperforming CPUs. Minor feedback includes acronym punctuation.

Users expressed skepticism about the product's long-term viability, citing a belief that telepathic interfaces, not vocal computing, represent the future. Concerns were raised about privacy due to 24-hour microphone and camera access. The lack of a video demo and latency details hindered proper evaluation, with some noting high latency in the existing demo and suggesting improvements in natural language understanding/processing. Criticisms also mentioned the impracticality of CPU-only solutions for real-time tasks and delays in response generation. One comment suggested that a video during speech input was unnecessary.

Avatar
121
22
0.0%
-9.1%
22
121
13.6%
Relevance

Superflows- Open source toolkit to build AI assistant for SaaS

06 Aug 2023 Artificial Intelligence SaaS Developer Tools

Henry, Matt and James here - we're building an open source devtool that makes it easy to integrate an LLM-powered assistant into software products. It calls your API to take actions in the software and answer questions, like having a ChatGPT plugin within your product. It’s also open source, so you don’t have to send user data to another 3rd party.*We started working together 2 years ago and have pivoted a few times. One problem we came across running a startup was we had to learn to use a lot of business software.We also heard from people running software companies that one of their biggest problems was helping users get the most out of their software. We’re building Superflows to address these problems.Superflows works by calling API endpoints (and in time, functions in your code) which you choose to expose. This lets the chatbot achieve tasks within your software in response to natural language queries.You can upload your OpenAPI spec to our dashboard to get up and running, or there are presets to test. You can enable/disable endpoints and evaluate performance in the playground. We also have a react UI library to make it easy to integrate into your software.You can self-host for free. We're charging for the cloud version. This has faster & easier setup, user permissions, analytics & support.*We currently only support OpenAI LLMs, but are working on making it easy to host llama 2 so the whole stack is open source.

Avatar
2
2
Relevance

VoiceAI - Capture every conversation

09 Oct 2023 Artificial Intelligence SaaS Developer Tools

The most accurate transcription, translation and analytics platform for English, Arabic, Indian and mixed languages. Transcribe any file or real-time speech in a user-friendly platform, or integrate VoiceAI to your applications with just a few lines of code.

The Product Hunt launch garnered excitement and positive feedback, with users eager to try the platform and congratulating the team. The product is praised for its exceptional STT API, cross-functional features, easy integration, and linguistic diversity. Some users expressed specific needs, like DJI mic integration, while others hoped for improvements over previous products. Questions arose about the build's foundation (custom vs. Whisper). One user highlighted the timely launch, having unsuccessfully sought a similar product recently.

The user expresses dissatisfaction with prior products, suggesting a potential issue with previous offerings from the same source. This might indicate concerns about the reliability, quality, or effectiveness based on past experiences.

Avatar
123
13
30.8%
7.7%
13
123
30.8%
7.7%
Relevance

Play AI - The voice interface of AI

29 Apr 2024 Artificial Intelligence Audio API

PlayAI is a new real-time conversational voice AI platform for creating human-like voice agents. It makes conversations contextual, handles turn-taking, interruption, voice energy and emotion modulation for natural, fluid, and human conversations in real-time.

PlayAI is receiving overwhelmingly positive feedback for its realistic and human-like conversational AI, intuitive voice interface, and responsiveness. Users praise the natural conversations, speed, and improved vocal models. The Restaurant Staff template is specifically highlighted. Some users are experiencing mic recognition issues and find the speed slightly too fast. Questions are raised about API pricing, language support (Spanish), and comparisons to Vapi. Users are excited to try the tool, check it out, and integrate it into their workflows. Congratulations on the launch are common, and there's positive feedback for individuals like Hammad.

Users expressed concerns about voice customization, specifically requesting a voice template resembling Carmen's. Integration with diverse languages and dialects was desired. Technical issues were noted, including microphone recognition problems and a slightly fast processing speed. Questions were raised about security measures against voice phishing. Spanish voice search functionality was also requested.

Avatar
416
35
22.9%
35
416
22.9%
Relevance

Cols.ai - AI phone calling platform

16 Jul 2024 Artificial Intelligence Customer Communication Developer Tools

Human-like AI voice assistants with sub-1000ms latency can handle complex tasks in real-time, efficiently solving customer problems during calls. Experience seamless, instant support and elevate your customer service to new heights.

Cols.ai's Product Hunt launch received positive feedback, with users praising its multilingual support, versatility, cost-effectiveness, and lifelike AI voice technology. Many appreciate its potential for personalized conversations, improved sales, and smoother customer interactions by breaking language barriers. The automated workflow feature and impressive analytics are also valued. Users are excited about AI enhancing personalization and improving sales with real-time data. Some users seek assurances regarding call stability, sound quality, and proof of strength. One user reported not receiving a call back.

The Product Hunt launch received criticism regarding a lack of responsiveness, with one user reporting they didn't receive a call back. Another user expressed apprehension about future competition and uncertainty surrounding the product's current standing in the market.

Avatar
156
20
25.0%
5.0%
20
156
25.0%
5.0%
Relevance

Vocol.AI - All-in-one voice collaboration platform

31 Jul 2023 Artificial Intelligence Languages Productivity

Powered by advanced speech and Natural Language Processing technologies, Vocol is a one-stop voice collaboration platform designed to boost work efficiency by turning voice and data into actionable insights.

The Product Hunt launch received overwhelmingly positive feedback. Users congratulated the team and wished them success. The product is considered promising and cool, with one user reporting a great and real experience with the app. Vocol is viewed as a convenient and efficient AI tool, particularly useful for remote teams, as it converts speech to text. It's also highlighted as indispensable for podcast production workflows. Overall, the comments indicate a strong positive reception to the launch.

Avatar
169
11
27.3%
11
169
27.3%
Top