LeadPath scores, enriches, and routes every inbound lead in seconds. See exactly why a lead matters, assign it to the right owner, and respond before your competitors do. No spreadsheets. No guesswork. Connect your form and before it reaches your CRM, you will see the breakdown of each forms response. You determine what makes the scoring and why a lead should be responded to first before the standard enquiries. Gathers information from your customers website know who they are before contacting
I'm Steve, and I've been an online marketer for over 20 years. Last year, I started creating an easier way to score leads from my many subscription forms, and LeadPath came to me when I tried to understand the CRM I was using, just to much information. I needed a simpler way to look at the data that i had.
The problem LeadPath solves:
Every business gets leads. But most leads sit in a messy inbox, unprioritised and un-actioned. Some are hot. Some are just browsing. And by the time you figure out which is which, the hot ones have gone cold.
What LeadPath does:
It scores every inbound lead with a transparent 0–100 rating based on signals you control, deterministic scoring. Budget, timeline, source, keywords, contact quality—your rules, your scoring. Then it enriches each lead with company context, pulls in the data from their website so you know who they are before you even pick up that lead and routes it to whoever is managing your inbound leads, sales, support, anyone who is designated for SLA deadline.
Why it's different:
No black-box AI. No mystery. You see exactly why a lead scored what it did.
What I'd love from you:
• Feedback on the landing page
• Feature suggestions
• Questions about how it works
Try it free for 14 days
Happy to answer anything!
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piping form submissions to LLM with scoring prompt already gives fit score and reasoning, unless you enrich against external data or sync closed-won CRM outcomes to "tune" it it just prompt. what data this touches that basic API call dosent
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Maker
@konstantin_tikhaev This is not an AI generated lead scoring. Whatever is on the submission form comes through to LeadPath, then depending on what criteria has been set manually tells leadpath @How To Score'. These factors are deterministic on such things a sthe form submission requires. The external data you mention for Leadpath to enrich is from the data submitted on the form, so if a company asks for a website, Leadpath extracts the data from the customers website, social media, and other enriched data. Please check it out for the free trial available before telling me how my app works.
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Maker
@konstantin_tikhaev Fair question. LeadPath doesn't pipe submissions to an LLM with a scoring prompt. It uses deterministic, rule-based scoring—signals you control (budget, timeline, source, keywords, contact quality) mapped to a transparent 0–100 score.
The reason for that choice: you always see exactly why a lead scored what it did. No model drift. No hallucinated reasoning. No "trust the AI" moment.
The enrichment layer fetches company web data (page title, meta, social links, pricing signals, demo CTAs) before the first call. The routing layer then assigns hot leads to the right owner with SLA deadlines, Slack/email alerts, and CRM push (Pipedrive/Zoho).
So the value isn't "LLM scores your lead." It's the full workflow: score → enrich → route → alert → CRM—with every signal visible. That's the part a basic API call doesn't give you.
Appreciate the challenge—happy to go deeper if you want to test it.
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@stephen_roberts4 Thought is another LLM wrapper ) Scraping domain metdata and pricing signals directly gives clear edge over simple form parsing.
piping form submissions to LLM with scoring prompt already gives fit score and reasoning, unless you enrich against external data or sync closed-won CRM outcomes to "tune" it it just prompt. what data this touches that basic API call dosent
@konstantin_tikhaev This is not an AI generated lead scoring. Whatever is on the submission form comes through to LeadPath, then depending on what criteria has been set manually tells leadpath @How To Score'. These factors are deterministic on such things a sthe form submission requires. The external data you mention for Leadpath to enrich is from the data submitted on the form, so if a company asks for a website, Leadpath extracts the data from the customers website, social media, and other enriched data. Please check it out for the free trial available before telling me how my app works.
@konstantin_tikhaev Fair question. LeadPath doesn't pipe submissions to an LLM with a scoring prompt. It uses deterministic, rule-based scoring—signals you control (budget, timeline, source, keywords, contact quality) mapped to a transparent 0–100 score.
The reason for that choice: you always see exactly why a lead scored what it did. No model drift. No hallucinated reasoning. No "trust the AI" moment.
The enrichment layer fetches company web data (page title, meta, social links, pricing signals, demo CTAs) before the first call. The routing layer then assigns hot leads to the right owner with SLA deadlines, Slack/email alerts, and CRM push (Pipedrive/Zoho).
So the value isn't "LLM scores your lead." It's the full workflow: score → enrich → route → alert → CRM—with every signal visible. That's the part a basic API call doesn't give you.
Appreciate the challenge—happy to go deeper if you want to test it.
@stephen_roberts4 Thought is another LLM wrapper ) Scraping domain metdata and pricing signals directly gives clear edge over simple form parsing.