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Medical Transcription Intelligence Cyron AI

SolarBuddy Automation

Every address gets geocoded, logged, and stored with coordinates or automatically flagged with a failure reason.

An automated intake-to-PDF pipeline that processes property data within seconds, calculates solar potential, and registers API costs into a dashboard with zero manual handling.

No Lead Intake Drops Silently

Most solar assessments stall not because homeowners are uninterested but because the data validation takes too long. System metrics reveal that data integrity drops significantly when API lookups go unhandled. SolarBuddy required an architecture that removed this operational dependency entirely. The automated backend handles the data intake, calculates solar potential, and records every operational cost trace—giving administrators a clean view containing only the records that are already verified.

The Impact

Streamlined Intake Delivery

Automates a multi-step ingestion pipeline that delivers a personalized downloadable solar report dir

Centralized Cost Visibility

Aggregates granular per-API cost logs across OpenAI token usage, Make.com operations, and free-tier

Automated Data Screening

Audits data ingestion health automatically by parsing incoming payloads and isolating incomplete rec

How We Thought

Focused on transforming raw property submissions into calculated estimates instantly, ensuring no processing delays or hidden execution costs stall system tracking.

1. Webhook Ingestion

The Entry Point

The workflow triggers instantly on multi-step lead intake form submissions, capturing contact information, energy metrics, and roof image uploads.

2. Forward Geocoding & Solar Analysis

The API Execution

Data coordinates pass to third-party geocoding and solar endpoints to retrieve regional irradiance, tariff structures, and production estimates.

3. Result Routing & Deduplication

The Logic Gate

The automation checks database histories for identical property addresses before execution to prevent duplicate API spend.

4. Dual Destinations

The Output Split

Clean transactions generate an assessment report and write to the Leads table; failed requests route directly into an error view.

5. Error Classification

The Safety Net

A scheduling scenario scans recently added leads for missing fields and creates specific issue tags for administrator review.

Architecture Snapshot

An event-driven pipeline where inbound webhooks trigger immediate response workflows. The architecture couples data ingestion, API execution, validation logic, and parallel CRM logging into a single automated stream that eliminates processing lag

The Stack

Make.com, Vercel, OpenAI, and Airtable work together to create a fully automated solar analysis infrastructure. Vercel hosts the intake form and admin dashboard, Make.com orchestrates the automation and routing logic, OpenAI handles report processing, and Airtable serves as the central database for all leads, costs, and error logs.

Make.com

Vercel

Open AI

Airtable

Systems Delivered

Multi-Step Lead Intake Webform

Per-API Cost Tracking Module

Make.com Automated Calculation Backend

APITemplate.io PDF Generation Engine

Authenticated Dashboard User Interface

What Changed

Inbound data moves from submission to structured PDF reports in seconds.
Administrative teams waste zero time cross-referencing manual solar grids or layout formats.
Pipeline spend leaks dropped because every software operation logs an audit cost trace.
Dedicated integrity views guarantee swift visibility for records needing manual adjustment.
The entire lead processing and report delivery ecosystem runs continuously 24 hours a day.

Curious how we approach complex builds like this?

See How We Work

CIZO helped us turn a complex solar assessment process into a simple, automated workflow. The system saves our team time and gives us better visibility across the entire process.

- JonathanAutomation | USA

Most ideas never reach this stage. Execution is where ideas earn their value.