Case Studies

The receipts.

No vague promises. Every project below shipped on time, hit its numbers, and paid for itself. Here's exactly how.

AI Automation

A SaaS company was losing 3 days per customer onboarding. We got it down to 4 hours.

Problem

Their ops team was manually creating accounts, migrating data from spreadsheets, sending welcome emails, and assigning training resources -- for every single new customer. Three full days, every time. It was killing their ability to scale.

What we built

An end-to-end automation pipeline using n8n workflow orchestration + Claude API for intelligent data mapping + HubSpot integration for CRM sync and personalized welcome sequences. The system handles account provisioning, data migration, onboarding emails, and training resource delivery -- zero human intervention needed.

n8n Claude API HubSpot PostgreSQL Webhooks
Results
93%

Time Reduction

$180K

Annual Savings

4.8x

ROI in 6 Months

RAPID Phase: Prototype & Prove → Deploy Timeline: 4 weeks

Industry: SaaS • Service: AI Automation

[Project Screenshot / Diagram]
[Project Screenshot / Diagram]
AI Agents

Their support team was drowning. Now an AI agent handles 80% of tickets before a human even sees them.

Problem

An e-commerce company with 50K+ monthly orders was burning through support staff. 80% of tickets were the same five questions: order status, returns, refund timelines, account resets, and shipping ETAs. Hiring more reps wasn't going to fix the math.

What we built

A custom AI support agent powered by Claude 3.5 Sonnet, deployed across live chat (Intercom), email, and SMS. The agent pulls real-time order data from Shopify, processes returns against policy rules, and handles account issues autonomously. Built-in escalation logic: if sentiment drops below threshold, if the request involves a refund over $200, or if the customer asks for a human -- it routes to the right team member with full context attached. No cold handoffs.

Claude 3.5 Sonnet Intercom Shopify API Twilio SMS n8n
Results
80%

Tickets Automated

52%

Cost Reduction

+15

NPS Increase

RAPID Phase: Assess → Prototype & Prove → Deploy Timeline: 6 weeks

Industry: E-Commerce • Service: AI Agents

SaaS Development

A FinTech founder had a 12-week window before a competitor closed the gap. We shipped the MVP in 8.

Problem

The founder had validated demand, had a waitlist of 800 people, and zero product. A well-funded competitor was 3 months from launching the same thing. Speed wasn't a nice-to-have -- it was the entire strategy.

What we built

A full SaaS MVP with AI-powered risk scoring, subscription billing, and a scalable multi-tenant architecture. Tech stack: React frontend, Node.js backend, Stripe for billing and payouts, PostgreSQL database. Deployed on AWS with CI/CD from day one. Auth, role-based access, admin dashboard, and real-time analytics -- all production-ready, not duct-taped together.

React Node.js Stripe PostgreSQL AWS CI/CD
Results
8wk

Time to Launch

5K+

Users in 90 Days

$0

Infrastructure Issues

RAPID Phase: Research → Architect → Deploy → Iterate Timeline: 8 weeks

Industry: FinTech • Service: SaaS Development

[Project Screenshot / Diagram]
[Project Screenshot / Diagram]
Workflow Automation

A logistics company had a 15-step manual process eating $240K a year. We killed it in 3 weeks.

Problem

Every shipment required 15 manual steps: data entry across three systems, email confirmations to carriers, rate comparisons in spreadsheets, invoice generation, and compliance document uploads. Four full-time employees did nothing but process paperwork. Errors were constant. Late shipments were costing them clients.

What we built

A fully automated shipment processing pipeline using n8n for workflow orchestration + custom Python scripts for rate optimization, carrier API integrations, and compliance document generation. The system ingests shipment requests, compares carrier rates in real time, auto-generates invoices, sends confirmations, and files compliance docs -- all triggered by a single form submission.

n8n Python Carrier APIs PostgreSQL PDF Generation
Results
$240K

Annual Savings

15→1

Steps Remaining

97%

Error Reduction

RAPID Phase: Assess → Prototype & Prove → Deploy Timeline: 3 weeks

Industry: Logistics • Service: Workflow Automation

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