Problem

We faced a bottleneck in converting inbound client inquiries into qualified leads. Submissions via a Tally form arrived as unstructured data, requiring manual validation and data entry into Airtable. This process was prone to errors and delayed follow-ups, reducing our responsiveness and tarnishing the client experience.

Additionally, the lack of an automated scoring system meant we could not reliably prioritize opportunities. Without consistent classification, the team spent unnecessary time triaging each request, missing chances to engage warm leads promptly. We needed a scalable workflow that could ingest, validate, and classify data with minimal manual intervention, while preserving data privacy.

Solution

We designed an AI-enabled no-code workflow integrating Tally, Make, and Airtable. The Tally form collects client name, phone, email, customer request, and proposed budget. Make automates data retrieval, validates entries, converts budgets to numeric values, and applies conditional filters to classify leads as Cold, Warm, or Unclassified.

Our AI component analyzes client requests to generate a concise structured summary, enriching the lead profile before it lands in Airtable. Make then creates a new Airtable record with the summary and classification, enabling the business team to review and follow up—driving faster, more informed outreach while maintaining privacy standards.

Impact

Lead classification accuracy improvement: X%
Time-to-first-follow-up reduction: Y%
Data entry error rate decrease: Z%

Quote of how incredible of an impact this had.

My Role

No-code Automation Specialist
- Implemented end-to-end Tally-Make-Airtable workflow
- AI & Data Engineer
- Developed AI-driven request summarization and classification logic

AI No-Code Lead Qualification Workflow