LightfieldAI-native CRM that builds itself and does work for you
Thynkk — Stop Lurking. Start Replying.
Get Reddit traffic without the scroll
10 followers
Get Reddit traffic without the scroll
10 followers
Thynkk reads your site, finds Reddit conversations worth joining, and drafts what you'd say — so you show up where buyers are already talking.
I built this because I kept doing the same thing: knowing Reddit sends real traffic, opening 20 tabs, scrolling for an hour, and still not being sure which thread was worth a reply — or what to say without sounding like a shill.
Thynkk is simple: paste your website → we find live Reddit conversations where your product actually fits → you get ranked threads + reply drafts you can copy and post.
Not a "post and pray" scheduler. Not spam automation. Just the research and writing prep compressed into ~60 seconds.
Try it free — one scan on your site, no card. If it’s useful, the Launch Pack is $19 one-time for 3 full scans (no subscription — I hate paying monthly for tools I use twice at launch).
I'll be here all day — ask me anything, roast the UX, or tell me your niche and I'll tell you if Reddit’s even the right channel for it.
Thanks for checking us out 🙏
How does it pick which Reddit threads to surface versus skip, and is there any way to bias it toward specific subs or keywords you care about?
@salihrbsu It’s a two-step pipeline: find candidates, then rank for reply-worthiness.
1. Discovery (search)
When you paste your URL, Thynkk crawls your site and infers your product name, niche, audience, and keywords. It then runs Google searches scoped to Reddit (and some Quora) using problem-style queries like “best {niche}”, “looking for {niche}”, “recommend {keyword}”, etc. — niche and problem terms first, your brand name last (since most indie sites aren’t mentioned on Reddit yet).
It prefers recent threads (last ~12 months). If results are thin, it broadens the search. At this stage it only keeps real discussion URLs (e.g. Reddit /comments/ or /r/ links), dedupes them, and drops non-community pages.
2. Ranking (AI filter)
Those candidates go to Claude with your product context. It ranks threads by:
• Niche/problem fit — not whether your brand is named
• Intent — questions, recommendation requests, “what tool do you use”, complaints seeking solutions
• Recency — strongly prefers last 12 months; deprioritizes very old threads unless there aren’t enough recent ones
• Reply safety — deprioritizes memes, drama, megathreads already full of brand lists, dead threads
• Promo risk — each draft is labeled low/medium/high for how salesy it would sound
You typically get 5–10 surfaced threads from a larger pool of search hits. Free scans show a preview (fewer threads, truncated reply drafts); full scans unlock everything.
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Can you bias it toward specific subs or keywords?
Not directly today. The dashboard only takes a website URL — there’s no field for target subreddits or custom keywords.
Indirectly, yes: keywords come from your homepage (title, meta, page copy). A clearer site description → better inferred keywords → better search queries → more relevant threads. The “Communities to watch” section is AI-suggested based on what it found, not something you configure upfront.
On the roadmap / workaround: subreddit and keyword targeting would be a natural next feature (e.g. “focus on r/SaaS, r/indiehackers” or “prioritize astrology, horoscope”). For now, the best lever is making your site copy explicit about the problem you solve and who it’s for.
Curious how it decides which threads are actually worth jumping into versus just topically relevant. Does it factor in signals like post engagement or commenter intent, or is it mostly keyword matching?
@veyselclyw Good question — it's a two-step thing, not just "keyword matched Reddit."
1) Discovery
We generate search queries from the site (niche, problem language, "looking for / recommend / alternative / frustrated with…") and pull candidate threads (title, snippet, date). So the first pass is topical + intent-shaped queries, not dumping an entire subreddit.
2) Ranking what's actually worth joining
Those candidates go through a model pass that scores fit for this product. It prioritizes:
- clear ask / recommendation / "what tool" / complaint seeking a solution
- problem + niche fit (even if the brand is never named)
- threads that are still answerable without being spammy
- newer threads when date is available
It deprioritizes memes, drama, mega "list every tool" threads, and stuff that's only loosely related.
Each result gets something like intent type, a relevance score, a one-line match reason, and a promo-risk flag on the draft reply — so "topically related" and "good place to jump in" aren't treated as the same.
What it doesn't do today: pull live Reddit engagement (upvotes/comment counts) or read the full comment tree. Ranking is from title/snippet/date + product context, not raw karma.
So short version: search finds candidates; intent + product fit decides what's worth your time.
The Reddit angle is genuinely clever, I wasn't expecting it to pull threads from smaller subs my customers actually hang out in. Drafts were solid but I still edited the tone before posting.
@semra276308 thank you
Pulled up my blog on Thynkk and it actually surfaced a niche subreddit thread I had missed for weeks. The reply draft felt a little stiff, but the angle it suggested was genuinely useful.
@ayferkeskide6x thank you