Building a business with AI can quickly become a mess of chats, tools, ideas, and conflicting advice. siift turns that noise into a living map of your business, connecting strategy, evidence, decisions, and results in one place. From validation and build strategy to GTM and growth, our AI uses your evolving business context and proven processes to challenge assumptions, identify risks, and help you focus on what matters next.
Hey Product Hunt! Iโm Samim, founder of siift ๐
๐ Why we built siift Two years ago I ran my last startup on a general-purpose AI. It felt like a superpower: research, plans, content, decisions, all accelerated. As the business grew, our thinking got buried across chats, and no one really understood the details anymore.
AI did everything we asked, without any second thought or filtering. It helped us make rushed decisions, not informed ones. The work it produced wasn't documented, reliable or built to scale, so we followed its advice until we were lost in the noise. Lacking a clear direction, we had to shut down the company.
AI didn't kill the business. It let us go further than we should have, which cost us a year and tens of thousands of dollars.
So we built the tool we wished we'd had, to prevent others from falling into the same rabbit hole.
๐ก What siift does siift helps you decide. It's for anyone building a business or working on a project who has to make risky decisions and figure out what deserves their time.
Instead of another chat window, you get to: See the big picture. Ideas, actions and results on one visual canvas your team can share. Trust data-driven guidance. Follow evidence and metrics instead of black-box, yes-man AI advice. Build on everything. Your context, strategy and decisions all compound scalabley. Know what's next. See where you are, what you've learned, and what is actually a priority.
siift balances the convenience of AI automation with human judgement and control.
ย
๐ Product Hunt Launch Offer
This week only, sign up to get 30% off lifetime with our launch deal.
Weโd genuinely love your feedback. What works? What doesnโt?
And what else should a Human-first AI for serious business builders offer?
Report
@samimsย Love the focus on human judgment, AI is great for speed but having a central source of truth for strategy is so necessary. congrats for launch๐
Report
How does siift decide when an assumption is risky or needs to challenged?
@christian_onochieย Great question. Siift actually starts from a fairly conservative position: an assumption is considered risky until there's enough evidence to support it.
We use a scoring system that looks at how important the assumption is to the business, how strong the supporting evidence is, and whether there are conflicting signals. The evidence itself is also evaluated independently by a separate AI service, rather than just relying on the AI that generated the assumption in the first place.
So the goal isn't to declare an assumption right or wrong - it's to surface the ones where being wrong would matter most, but the evidence is still weak, so founders know what to validate first.
Report
Where 'proven processes' are concerned, what frameworks do they follow - the well-tested methodologies, or something self-developed? Btw, Congratulations @samims@sivapoba & team @siift ๐โ๏ธ
Report
How does the artificial intelligence verify evidence from real customer interviews rather than just relying on generic startup frameworks?
Report
seeing a tool turn that noise into clear execution steps is refreshing because i have been through the nightmare of conflicting advisor chats.
siift
Hey Product Hunt! Iโm Samim, founder of siift ๐
๐ Why we built siift
Two years ago I ran my last startup on a general-purpose AI. It felt like a superpower: research, plans, content, decisions, all accelerated. As the business grew, our thinking got buried across chats, and no one really understood the details anymore.
AI did everything we asked, without any second thought or filtering. It helped us make rushed decisions, not informed ones. The work it produced wasn't documented, reliable or built to scale, so we followed its advice until we were lost in the noise. Lacking a clear direction, we had to shut down the company.
AI didn't kill the business. It let us go further than we should have, which cost us a year and tens of thousands of dollars.
So we built the tool we wished we'd had, to prevent others from falling into the same rabbit hole.
๐ก What siift does
siift helps you decide. It's for anyone building a business or working on a project who has to make risky decisions and figure out what deserves their time.
Instead of another chat window, you get to:
See the big picture. Ideas, actions and results on one visual canvas your team can share.
Trust data-driven guidance. Follow evidence and metrics instead of black-box, yes-man AI advice.
Build on everything. Your context, strategy and decisions all compound scalabley.
Know what's next. See where you are, what you've learned, and what is actually a priority.
siift balances the convenience of AI automation with human judgement and control.
ย
๐ Product Hunt Launch Offer
This week only, sign up to get 30% off lifetime with our launch deal.
๐ Try siift today
Weโd genuinely love your feedback. What works? What doesnโt?
And what else should a Human-first AI for serious business builders offer?
@samimsย Love the focus on human judgment, AI is great for speed but having a central source of truth for strategy is so necessary. congrats for launch๐
How does siift decide when an assumption is risky or needs to challenged?
siift
@christian_onochieย Great question. Siift actually starts from a fairly conservative position: an assumption is considered risky until there's enough evidence to support it.
We use a scoring system that looks at how important the assumption is to the business, how strong the supporting evidence is, and whether there are conflicting signals. The evidence itself is also evaluated independently by a separate AI service, rather than just relying on the AI that generated the assumption in the first place.
So the goal isn't to declare an assumption right or wrong - it's to surface the ones where being wrong would matter most, but the evidence is still weak, so founders know what to validate first.
Where 'proven processes' are concerned, what frameworks do they follow - the well-tested methodologies, or something self-developed?
Btw, Congratulations @samims @sivapoba & team @siift ๐โ๏ธ
How does the artificial intelligence verify evidence from real customer interviews rather than just relying on generic startup frameworks?
seeing a tool turn that noise into clear execution steps is refreshing because i have been through the nightmare of conflicting advisor chats.