Just read it—really interesting point. We currently focus more on product events, sign-ups, and paid conversions than raw pageviews, but we haven’t separated AI crawlers from real users at the server level yet. Your human, crawler, and rogue-bot split makes a lot of sense. How are you planning to identify sophisticated headless browsers without blocking legitimate users?
Voice‑controlled automation across messaging apps sounds powerful. I’ll give the free credits a try — I’m curious how SMBs might use this for routine workflows compared to Zapier.
Thank you, our most important features are that it's secure, self-improving, and allows you to automate your tasks entirely through voice commands. Compared to applications like Zapier and n8n, it can create automations 10-50 times faster and connect to messaging applications with a single click. You can control it from places like WhatsApp without even opening the application itself. We're providing free credits for you to try it. We would be very happy if you could try it and leave a review.
The trust question feels connected to the first-use question.
“Secure, self-improving automations” describes a lot of capability, but trust probably means something different depending on what someone is actually letting Awish do.
That makes the first workflow feel like a consequential decision, not just an onboarding choice.
Exactly. Trust starts with what Awish can access and how that information is handled. User data, workflow details, and company information are stored securely, while app connections are established through permission-based authentication. We also make the required access and planned actions clear before a workflow runs.
That makes sense. The permission boundary is an important part of how users decide what level of automation they’re comfortable delegating.
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We are building Awish because existing automation tools are too slow and complex. Awish exists to create secure automations 10–50x faster using natural language with control through WhatsApp, Slack, or Telegram.
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How do you currently handle your analytics and would you mind reading my indiehacker pots on how AI crawlers and bots are ruining analytics data?
https://www.indiehackers.com/post/i-just-discovered-my-analytics-numbers-are-mostly-fake-here-is-why-8197e3ff9d
Just read it—really interesting point. We currently focus more on product events, sign-ups, and paid conversions than raw pageviews, but we haven’t separated AI crawlers from real users at the server level yet. Your human, crawler, and rogue-bot split makes a lot of sense. How are you planning to identify sophisticated headless browsers without blocking legitimate users?
Secure automation feels like a strong angle. Congrats on building something that works across Slack and Telegram!
Voice‑controlled automation across messaging apps sounds powerful. I’ll give the free credits a try — I’m curious how SMBs might use this for routine workflows compared to Zapier.
Thank you, our most important features are that it's secure, self-improving, and allows you to automate your tasks entirely through voice commands. Compared to applications like Zapier and n8n, it can create automations 10-50 times faster and connect to messaging applications with a single click. You can control it from places like WhatsApp without even opening the application itself. We're providing free credits for you to try it. We would be very happy if you could try it and leave a review.
The trust question feels connected to the first-use question.
“Secure, self-improving automations” describes a lot of capability, but trust probably means something different depending on what someone is actually letting Awish do.
That makes the first workflow feel like a consequential decision, not just an onboarding choice.
Exactly. Trust starts with what Awish can access and how that information is handled. User data, workflow details, and company information are stored securely, while app connections are established through permission-based authentication. We also make the required access and planned actions clear before a workflow runs.
That makes sense. The permission boundary is an important part of how users decide what level of automation they’re comfortable delegating.