Most AI support tools ask you to rip out your helpdesk first. Ify works on top of Freshdesk, Zendesk, Salesforce, or HubSpot and gets to work across email, chat, WhatsApp, Slack, and more. The part that usually stalls an AI support rollout is "our docs aren't good enough." Ify solves that by building its own knowledge base: it scrapes your site and docs, generates SOPs from release notes and past ticket resolutions. Built for support teams who want something live now.
We built Ify because every AI support tool we looked at asked for the same trade: rip out your helpdesk, spend weeks migrating, then maybe get an AI agent that's actually useful.
Ify skips that. It works directly on top of Freshdesk, Zendesk, Salesforce, or HubSpot — so you keep what you have and just add the part that resolves tickets. If you don't have a helpdesk yet, it can run standalone too.
The thing we spent the most time on isn't the chat widget or the automations — it's the knowledge base. Almost every team we talked to had messy or incomplete docs, and that's usually what kills an AI support rollout before it starts. So Ify builds its own: it scrapes your site and docs, turns release notes and past resolved tickets into SOPs, and keeps learning from what your team resolves manually.
We're in private beta right now, working closely with early SMB and mid-market support teams to get this right before we open it up further. If you're curious how it'd fit with your current stack, or you've hit the "our docs aren't good enough for AI" wall yourself, I'd love to hear about it in the comments.
Would really appreciate any feedback, questions, or just tell us what you'd want an AI support agent to actually do.
Regards,
Karthik - Founder @ ify
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@karthik_veluswamy1 working directly on top of existing platforms like zendesk and freshdesk is a huge advantage for teams that don't want to migrate. qq what is the typical onboarding time for an SMB before ify has absorbed enough context to confidently resolve its first ticket?? congrats for launch🙌
@priya_kushwaha1 Under 20 minutes to connect your helpdesk (or email), pull in your knowledge base, and have your team ready to go. Give it a try 🙌
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@karthik_veluswamy1 Thanks, that sounds super easy to set up. I’ll definitely give it a try
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@karthik_veluswamy1 Been in the customer support space for 10+ years and this is definitely the right way to solve customer support with AI, from the product documentation upwards. Best wishes to the Ify team!
@saurabh_p Thank you, means a lot coming from someone who's been in customer support for a decade+. Glad the documentation, up approach resonates, that's the part we're most proud of. 🙏
@hamsapriya_veluswamy Definitely “Actions.” Customers kept telling us, “An ideal response is good but can it actually fix the issue?” So we connected ify to hundreds of apps, letting it handle tasks like refunds, subscription changes, and account updates. The surprise was seeing where support ends and operations begin. Customers started using ify to focus on managing the required tools and actions, not just resolve queries.
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@praveen_raj8 That reminds me of the old saying: actions speak louder than words. Seems like ify is taking that quite literally! 😄
@nivasravi Great question! Ify connects to thousands of business apps, so it goes beyond answering questions it can issue refunds, change subscriptions, update accounts, and take other actions directly in the tools your team already uses.
On top of that, there’s no per-user licensing, so your whole team can log in without additional seat costs. This broad action layer, combined with learning from your existing support knowledge, is Ify’s core strength.
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@karthik_veluswamy1@irsh1985@praveen_raj8 Congratulations, this is amazing that you are solving a problem that most customer support facing teams finds it difficult to solve.
Curious -
1) Does it replace the need to have a knowledge base like notion, confluence or would this be on top of these knowledge base.
2) What do you see as a single source of truth from a knowledge base perspective.
Ify doesn’t require you to replace Notion, Confluence, or your existing knowledge base. It works on top of them, combining that content with release notes and past ticket resolutions to build support ready SOPs.
Your existing tools can remain the source of truth for product documentation, while ify becomes the operational knowledge layer for support continuously turning scattered information into reliable, actionable answers.
Congrats Karthik and team Konnectify- I see where "Ify" comes from! Love the approach of working on top of the existing helpdesk instead of forcing teams to migrate. The bigger insight for me is the knowledge layer, especially turning past resolutions, release notes and messy documentation into something the AI can actually use. That feels like where a lot of support AI implementations succeed or fail. Will this also migrate data from past resolutions?
Wishing you a great launch. Excited to see where you take Ify! 🚀
Thank you! And yes — spot on. To your question - the knowledge base pulls from past resolutions too, not just docs and release notes, so it's not starting from scratch. That's the part we focused on most, since that's usually where support AI falls down. Appreciate the sharp question and thanks once again
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I've sold many similar products over the last decade and this is impressive. Worth checking out for sure.
Adding a quick note on the technical side of why we built ify this way:
When we set out to build this, one thing became clear very quickly:
AI is only as good as the context behind it — and support documentation is almost never perfect.
A lot of a team’s real tribal knowledge doesn’t live in pristine docs. It’s buried inside resolved tickets, Slack threads, release notes, and agent workarounds.
Instead of forcing support teams to clean up or rewrite their documentation before they can use AI, we built ify to continuously map, absorb, and turn that scattered historical context into usable SOPs.
The goal is for the AI to understand not just what the documentation says, but how the support team actually solves problems.
I’d love to hear from the technical and support folks here:
What’s the trickiest support query or workflow you’d still be hesitant to hand off to an AI agent today?
ify
Hey Product Hunt 👋,
We built Ify because every AI support tool we looked at asked for the same trade: rip out your helpdesk, spend weeks migrating, then maybe get an AI agent that's actually useful.
Ify skips that. It works directly on top of Freshdesk, Zendesk, Salesforce, or HubSpot — so you keep what you have and just add the part that resolves tickets. If you don't have a helpdesk yet, it can run standalone too.
The thing we spent the most time on isn't the chat widget or the automations — it's the knowledge base. Almost every team we talked to had messy or incomplete docs, and that's usually what kills an AI support rollout before it starts. So Ify builds its own: it scrapes your site and docs, turns release notes and past resolved tickets into SOPs, and keeps learning from what your team resolves manually.
We're in private beta right now, working closely with early SMB and mid-market support teams to get this right before we open it up further. If you're curious how it'd fit with your current stack, or you've hit the "our docs aren't good enough for AI" wall yourself, I'd love to hear about it in the comments.
Would really appreciate any feedback, questions, or just tell us what you'd want an AI support agent to actually do.
Regards,
Karthik - Founder @ ify
@karthik_veluswamy1 working directly on top of existing platforms like zendesk and freshdesk is a huge advantage for teams that don't want to migrate. qq what is the typical onboarding time for an SMB before ify has absorbed enough context to confidently resolve its first ticket?? congrats for launch🙌
ify
@priya_kushwaha1 Under 20 minutes to connect your helpdesk (or email), pull in your knowledge base, and have your team ready to go. Give it a try 🙌
@karthik_veluswamy1 Thanks, that sounds super easy to set up. I’ll definitely give it a try
@karthik_veluswamy1 Been in the customer support space for 10+ years and this is definitely the right way to solve customer support with AI, from the product documentation upwards. Best wishes to the Ify team!
ify
@saurabh_p Thank you, means a lot coming from someone who's been in customer support for a decade+. Glad the documentation, up approach resonates, that's the part we're most proud of. 🙏
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@karthik_veluswamy1 Not having to spend weeks fixing messy docs just to test an AI agent is a massive win
ify
@kshitij_mishra4 Thanks for your kind words. Please try ify and give us feedback.
What’s one feature you built because customers kept asking for it—and what surprised you about how they use it?
ify
@hamsapriya_veluswamy Definitely “Actions.” Customers kept telling us, “An ideal response is good but can it actually fix the issue?” So we connected ify to hundreds of apps, letting it handle tasks like refunds, subscription changes, and account updates. The surprise was seeing where support ends and operations begin. Customers started using ify to focus on managing the required tools and actions, not just resolve queries.
@praveen_raj8 That reminds me of the old saying: actions speak louder than words. Seems like ify is taking that quite literally! 😄
Congratulations @karthik_veluswamy1 @irsh1985 @sarnith_kumar @praveen_raj8.
Curious. How does this differ from something like a Fin or so?
ify
@nivasravi Great question! Ify connects to thousands of business apps, so it goes beyond answering questions it can issue refunds, change subscriptions, update accounts, and take other actions directly in the tools your team already uses.
On top of that, there’s no per-user licensing, so your whole team can log in without additional seat costs. This broad action layer, combined with learning from your existing support knowledge, is Ify’s core strength.
@karthik_veluswamy1 @irsh1985 @praveen_raj8 Congratulations, this is amazing that you are solving a problem that most customer support facing teams finds it difficult to solve.
Curious -
1) Does it replace the need to have a knowledge base like notion, confluence or would this be on top of these knowledge base.
2) What do you see as a single source of truth from a knowledge base perspective.
ify
@rahul_rajpal Thanks Rahul, great questions!
Ify doesn’t require you to replace Notion, Confluence, or your existing knowledge base. It works on top of them, combining that content with release notes and past ticket resolutions to build support ready SOPs.
Your existing tools can remain the source of truth for product documentation, while ify becomes the operational knowledge layer for support continuously turning scattered information into reliable, actionable answers.
Highperformr.ai
Congrats Karthik and team Konnectify- I see where "Ify" comes from! Love the approach of working on top of the existing helpdesk instead of forcing teams to migrate. The bigger insight for me is the knowledge layer, especially turning past resolutions, release notes and messy documentation into something the AI can actually use. That feels like where a lot of support AI implementations succeed or fail. Will this also migrate data from past resolutions?
Wishing you a great launch. Excited to see where you take Ify! 🚀
ify
@rramesh25 Thanks Ramesh
Thank you! And yes — spot on. To your question - the knowledge base pulls from past resolutions too, not just docs and release notes, so it's not starting from scratch. That's the part we focused on most, since that's usually where support AI falls down. Appreciate the sharp question and thanks once again
I've sold many similar products over the last decade and this is impressive. Worth checking out for sure.
ify
@george_hackett Really appreciate that — especially coming from someone with your track record. Thanks for checking it out!
ify
Hey everyone! 👋
Sarnith here, CTO & Co-founder at @ify.
Adding a quick note on the technical side of why we built ify this way:
When we set out to build this, one thing became clear very quickly:
AI is only as good as the context behind it — and support documentation is almost never perfect.
A lot of a team’s real tribal knowledge doesn’t live in pristine docs. It’s buried inside resolved tickets, Slack threads, release notes, and agent workarounds.
Instead of forcing support teams to clean up or rewrite their documentation before they can use AI, we built ify to continuously map, absorb, and turn that scattered historical context into usable SOPs.
The goal is for the AI to understand not just what the documentation says, but how the support team actually solves problems.
I’d love to hear from the technical and support folks here:
What’s the trickiest support query or workflow you’d still be hesitant to hand off to an AI agent today?