Build an AI-Powered Lead Qualification App

Import your lead sample to Vext and let your customized-AI rate the inbound lead quality for you.

Start For Free

Quickly Assess Inbound Leads with Tailored AI

Enhance your lead generation workflow by integrating your unique lead data into Vext to seamless empowers you to build a precise lead scoring AI, tailored specifically to your organization's needs. This innovative approach ensures a more efficient and targeted lead management process.

See It in Action

Fill the form and see the result here.

How It Works

Import Sample Lead Data

Optimize your AI's lead scoring by using the "few-shot" method: provide examples of good and bad leads to the language learning model. The more varied your data, the more accurately the AI assesses and prioritizes leads.

Set Up LLM Reply Format

Choose a model based on the complexity of the task. Provide detailed instructions, including response style, format, tone, and specific information sources to use, ensuring tailored and effective outcomes.

Integrate With Your Flow

Incorporate your custom AI into your lead form with a no-code solution using Zapier for straightforward implementation, or with the Vext API for a more in-depth integration. This allows you to streamline your lead management process, enhancing efficiency and accuracy in capturing and analyzing lead data.


You can integrate with any lead form that is compatible with Zapier or supports API integration, such as HubSpot Form, Salesforce, Calendly, and etc. For this specific use case, we are utilizing HubSpot Form.

In this particular use case, the "few-shot" method should suffice. However, it is important to provide a wide range of examples to ensure that the LLM has a comprehensive benchmark for effectively evaluating your inbound leads.

At Vext, data security is our top priority. We've made sure: (1) the data you've imported is encrypted and only accessible to you and your AI only, (2) the LLMs that we offer are only from trusted vendors that doesn't use your data for training purposes and able to enforce encryption. (e.g. Azure OpenAI models vs OpenAI).