Launching today
Lev8
Find, research, and reach the right people
613 followers
Find, research, and reach the right people
613 followers
Chat with Lev8, the fastest way to find and reach your target people and companies, powered by live web search via parallel AI agents across every corner of the internet. Enrich CSVs with waterfall lookups, monitor intent signals, and send personalized multi-channel messages, all running automatically.
Lev8
👋 Hey Product Hunters,
I'm Tony Zhang, co-founder of Lev8 , the fastest agent to find and reach your target people and companies across every corner of the internet and reach across multiple channels.
Here are a few searches our early users have thrown at Lev8:
“Find me VPs of Sales at fast-growing voice agent startups in the Bay Area that raised funding recently.”
“Find everyone who starred our GitHub repo, then reach out to them across multiple channels.”
“Find coffee shops in San Francisco with a 4.5+ rating and no website.”
AI has made it easier to build products. Getting the right people to notice them is still hard.
We felt this ourselves. Our team spent hours jumping between search tools, databases, spreadsheets, and enrichment services just to answer a simple question:
Who should we talk to, and why?
So we built Lev8.
What Lev8 does
Lev8 turns the live web into people and business intelligence.
Describe who you’re looking for in plain language, and Lev8:
Searches across public sources
Verifies identities
Adds relevant context
Surfaces the signals that explain who matters right now
What happens behind the scenes
Our crawler reaches sources that static databases miss. Parallel agents explore the web, while our identity system makes sure the facts belong to the right person or company.
The goal isn’t to create another oversized lead list.
It’s to help you discover the companies and people others miss—and provide reliable intelligence that both people and AI agents can use to make better decisions.
Lev8
🎁 For the Product Hunt community
Product Hunt members get 500 free credits today.
👉 Try Lev8.com with a search you couldn’t solve before, and tell me how it goes. I’d especially love to hear what you searched for and where the results could be better.
I’ll be reading every comment.
Congrats on the launch, Tony! How do you verify that the person and company data are still current?
Lev8
@blink_66 Thanks for the shoutout!
We keep data fresh by completely rethinking how data is sourced—instead of locking people into a static, stale database, Lev8 operates as a live system that mines the open web in real time.
Our swarm of background agents monitors live web sources 24/7, tracking dynamic updates like job changes, hiring activity, funding, and tech stack shifts as they happen. On top of that, we run every contact through a three-layer qualification process to strip out the noise, verify their identity across platforms, and ensure they’re actually reachable before you ever hit send.
@nora_yu The research step is where every tool I've tried falls apart. Enrichment is fine, but the "why now" signal is usually stale by the time it hits my inbox and the first line reads like it was written by a robot who skimmed a LinkedIn headline. What's your freshness window on the signals, and does the operator get to see the raw evidence behind a suggested angle before sending?
Lev8
By default, we balance signal freshness with research speed and cost. If your campaign depends on very recent information, you can tell the Lev8 agent the freshness window you need. Before sending, you can review the suggested angle and its supporting source links.
@nora_yu Congrats on the launch! 🙌🏽
Flowtica Scribe
@Lev8 is one of the most technically grounded agent systems I’ve seen for people and company intelligence, and it works remarkably well.
The first time I tried it, I felt it had already gone beyond any general-purpose search tool I had used for finding and matching the right people and companies.
Search is an extremely long-tail problem. Lev8 handles it with a multi-agent system that can move quickly across a huge amount of scattered information and identify the exact people or companies you are looking for.
Quite often, it opens up a part of the market you did not even know existed.
It also does not stop at discovery. Lev8 connects the results to the social and outreach channels you already use, so the same workflow can continue all the way to the first conversation.
If connecting with people and companies is part of your work, give Lev8 a try. It may be the most accurate and efficient tool available for this job right now!
@zaczuo Sounds very useful and the demo looks awesome. But what data sources does it actually use and how does it handle people/companies with similar (or the same) names? Can we see the underlying data to verify it?
Lev8
@zaczuo @jn263
Lev8 built a search engine to discover and analyze publicly available web information in depth, while also integrating data from a range of established data platforms.
To handle similar names, lev8 cross-checks details like company information and work history rather than relying on the name alone. If only a name is provided, some ambiguity may remain.
The result include relevant source URLs so you can verify the results and ask the agent to investigate further if needed.
@zaczuo @richgalulu Thanks for the in-depth explanation. Sounds very robust.
the "who should we talk to, and why?" framing is exactly the difficult part. as a founder, finding names is usually not the bottleneck anymore, finding people who are relevant right now and having enough real context to write something that does not feel like mass outreach is
the live web search and intent signals sound especially useful for launch prep, partnerships, and early sales. Curious how Lev8 shows confidence and sources behind each result, and how you prevent the personalized outreach from becoming confidently written spam based on weak or outdated signals :)
Lev8
@andrasczeizel Finding names is easy, but having real context to reach out right now is the actual bottleneck. To prevent "confidently written spam," Lev8 ditches static databases to mine live web signals (like GitHub, forums, and tech stack shifts) in real time, with every insight linked directly back to its live source so you can verify it yourself. While AI hallucinations are a real challenge, we run cross-model validation across multiple LLMs—accepting a data point only when all models agree.
On top of that, we run Signal Scoring to filter out weak or stale inputs, ensuring outreach is only triggered when there is true urgency and ICP fit. Instead of rigid templates, the messaging is context-native and grounded in verifiable events, acting more like a research teammate than a cold-spam machine. Would love to get your thoughts if you're gearing up for a launch soon!
@nora_yu that sounds much closer to the kind of outreach I'd actually trust. linking every insight to a live source, then only triggering outreach when the signal is strong and the ICP fit is real, addresses my biggest concern here. the cross-model validation is interesting too. I imagine it may sacrifice some recall for precision, but for outbound that honestly feels like the right tradeoff.
and yes, we're preparing for a launch soon :) I'd be happy to try Lev8 on a real outreach use case and send you a feedback on where the context feels genuinely useful versus where it still feels generic. followed you on X!
Tony, the coffee shop example is what caught my attention, since it implies discovery beyond the usual B2B databases. I sell AI software to healthcare and my buyers barely exist on LinkedIn: therapists in small practices, home health administrators, office managers. Every prospecting tool I have tried collapses there because it leans on the same two databases. Can Lev8 work from public registries, for example finding providers by license type or specialty and then locating their practice contact info? That search alone would be worth real money to me. Will test it with the 500 credits.
Lev8
@clemente_lopez1 That is exactly why we built Lev8—the traditional B2B databases completely fall apart the second you step outside the tech/corporate bubble. Since we don't rely on static database scraping, our agent swarm can mine the live web across niche sources, public registries, specialized directories, and local web presence. It’s designed to find practitioners like independent therapists or home health admins by license, specialty, or location, and then stitch together their actual practice contact info.
@clemente_lopez1 The registry answer for your segment is probably NPPES rather than anything a prospecting tool licenses. It is the CMS provider registry, public, free, and downloadable in full, and it carries taxonomy codes so you can filter to exactly the therapist and home health categories you sell into, with practice address and phone attached. State license boards cover what the taxonomy misses.
Where it stops is the part you actually need. NPPES gives you the practice, not the person. Your buyer is often the office manager or the administrator, and they do not hold an NPI, so they never appear in it. You end up with a clean list of organizations and still no named human.
So the useful test of any tool here is not whether it can find the clinic. It is whether it can get from a clinic to the person who signs. When you spend the 500 credits, is that the search you are going to point it at?
the outreach-side deliverability question above is a good one, but I'm curious about the other direction: the crawler side. pulling live data from LinkedIn and similar platforms at agent speed is exactly the kind of activity those platforms actively try to detect and rate-limit or ban accounts for. is Lev8 hitting these sources through some kind of licensed/API access, or is it closer to scraping, and if the latter, does the risk of a flagged account sit with Lev8's infrastructure or with the user's own connected accounts?
Lev8
@galdayan Lev8 uses authorized LinkedIn data APIs rather than scraping through users’ own accounts. That means users don’t need to connect or risk their personal LinkedIn accounts, and the data access is handled through Lev8’s compliant infrastructure.
@nora_yu good to hear, that's the answer that actually matters here. licensed API access instead of scraping means the compliance risk isn't quietly sitting on the user's own account without them realizing it. one more thing I'd be curious about down the line: does that licensed access cover the full breadth of what Lev8 searches (company + people data across the web), or just the LinkedIn piece specifically, with other sources handled differently?
Lev8
@galdayan
Lev8 uses a combination of official APIs and publicly accessible information across the web. The agent handles the search and analysis without accessing or involving any of the user’s accounts.
User authorization is only required when they choose to carry out outreach through their connected accounts.
Congrats on the launch @tony_zhang! The live web crawler approach is a huge step up from static databases that lag by 6+ months.
Because you're scraping real-time signals (like GitHub activity or forum posts), how does the identity system disambiguate someone who maintains multiple roles—e.g., a VP of Sales who is also an advisor or founder at a stealth startup? Does Lev8 tie the intent signal specifically to their primary domain/company context before generating the outreach hook?
Lev8
@franz_briones Yes. You can have Lev8 enrich the data you need, identify relevant email hooks, or search and scrape for specific signals you want to reference. Lev8 can then use those insights to generate highly personalized, engaging emails or outreach messages.
Congrats on the launch! I searched for a pretty unusual customer profile and Lev8 understood the request better than I expected. There were a couple of results I’d remove, but the overall direction was solid.
Lev8
@sandy_liusy Appreciate the congrats and the feedback! Really glad to hear Lev8 nailed the direction on a tough, non-standard search, that deep comprehension is exactly what we built our agent swarm for, going way beyond simple keyword matching to actually understand the context you're looking for. I appreciate you pointing out the couple of off-target results as well. We’re constantly fine-tuning our scoring and qualification layers to filter out that extra noise, so this helps us make the agent matching even sharper.