BeastData
Our Work

Results for real
San Diego businesses

Every project starts with a clear problem and ends with measurable results. Here's a sample of what we've built.

Law FirmSan Diego, CA

Intake time cut by 60% for a San Diego personal injury firm

n8nCRMWordPressCalendly
60%
Less time spent on intake
<2 min
Response time (was 24+ hrs)
3x
More consults scheduled per week

Overview

A solo attorney was spending 3–4 hours per week manually processing new client inquiries — copying form data into their CRM, sending intake questionnaires, scheduling consults. We automated the entire flow.

The Problem

New client inquiries were coming in through a basic contact form. Staff manually copied data into a spreadsheet, emailed a PDF intake form, and scheduled a consult by phone. Leads that came in after hours often waited 24+ hours for a response — and went cold.

Our Solution

We rebuilt their intake flow using n8n automation. When a lead submits the contact form, they instantly receive a branded confirmation email, an automated intake questionnaire, and a Calendly link to self-schedule a consult. All data routes automatically into their CRM. Staff get a Slack notification with the lead summary.

HVAC CompanySan Diego, CA

3x more after-hours leads captured for a local HVAC company

AI Chatbotn8nSMS AutomationLead Capture
3x
After-hours leads captured
$0
Additional ad spend required
11pm
Latest lead captured on day 1

Overview

A family-owned HVAC business was missing a significant portion of their leads — people calling or submitting forms after 5pm with no follow-up until the next morning. We fixed that with an AI chatbot and automated follow-up.

The Problem

Their website had a basic contact form but no chat. After-hours inquiries sat until the next morning. By then, many customers had already called a competitor. The owner estimated they were losing 30–40% of potential leads this way.

Our Solution

We deployed an AI chatbot trained on their services, service area, and pricing ranges. It handles after-hours inquiries, qualifies leads (emergency vs. scheduled), and captures contact info. Urgent requests trigger an immediate SMS to the owner. Scheduled requests enter an automated follow-up sequence.

Med SpaSan Diego, CA

40% fewer no-shows and 2x more Google reviews for a San Diego med spa

n8nSMSEmail AutomationGoogle Business
40%
Reduction in no-shows
2x
Google review velocity
4.1 → 4.7
Google rating in 90 days

Overview

A growing med spa was struggling with no-shows eating into revenue and a thin online review profile holding back their local search rankings. We automated both.

The Problem

Staff were calling patients manually to confirm appointments — time-consuming and inconsistent. No-show rates were around 25%. Their Google rating was 4.1 with fewer than 30 reviews, limiting their visibility for competitive local search terms.

Our Solution

We built an automated sequence: appointment confirmation email (immediate), reminder SMS (48 hrs before), reminder email with easy reschedule link (24 hrs before). Post-appointment, patients receive a review request SMS at the optimal time (2 hrs after). We also set up a Google Business Profile review widget on their website.

Research InstitutionSan Diego, CA

Custom data management platform for a San Diego research lab

ReactPythonAWSPostgreSQL
100%
Data centralized in one system
80%
Reduction in report prep time
3 days → 1 hr
New team member onboarding

Overview

A biomedical research lab needed a secure, custom web application to manage complex experimental datasets and streamline collaboration across their team. Off-the-shelf tools weren't cutting it.

The Problem

Researchers were managing critical data across spreadsheets, shared drives, and email threads. Version control was nonexistent. Onboarding new team members took days. Reporting to external collaborators was a manual, error-prone process.

Our Solution

We designed and built a custom web application with a React frontend and Python backend deployed on AWS. The platform includes a role-based access system, dataset versioning, automated report generation, and a collaboration layer. All data is encrypted at rest and in transit.

Life Sciences CompanySan Diego, CA

Salesforce automation that saved 10+ hours per week for a biotech sales team

SalesforcePythonAPI IntegrationAutomation
10+ hrs
Saved per week across team
Real-time
Pipeline visibility (was daily lag)
0
Manual Salesforce updates required

Overview

A San Diego biotech company's sales team was manually updating Salesforce records, running reports, and processing data from multiple external systems. We automated the entire workflow.

The Problem

Sales reps were spending 2+ hours daily on data entry and reporting. Deal stages were being updated inconsistently. Management had no real-time visibility into pipeline health because reports required manual exports and formatting.

Our Solution

We built a Python-based automation layer using the Salesforce API. Incoming data from external systems automatically creates and updates CRM records. Custom Salesforce Flows handle stage transitions. A nightly report is generated and delivered to leadership with no manual intervention.

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