Use Cases

Real problems, real solutions

Each project starts with understanding a specific challenge. Here are examples of the types of problems we solve and the outcomes we deliver.

Operations

E-Commerce Order Automation

Problem

A growing e-commerce company was manually processing orders from 4 different sales channels, leading to fulfillment delays and data entry errors.

Solution

We built an automated order processing pipeline that ingests orders from all channels, validates data, routes to the correct fulfillment center, and updates inventory in real-time.

Outcome

Order processing time reduced by 85%. Error rate dropped from 12% to under 1%. The team reallocated 20+ hours per week to growth activities.

PythonAPI IntegrationAutomationWebhooks
Reporting

Executive KPI Dashboard

Problem

Leadership relied on manually compiled weekly reports that were often outdated by the time they were reviewed. Data lived in 8+ different tools.

Solution

We consolidated data from their CRM, billing platform, support system, and marketing tools into a real-time dashboard with automated anomaly alerting.

Outcome

Real-time visibility into 15 key metrics. Weekly report preparation time eliminated entirely. Faster decision-making across all departments.

ReactNode.jsPostgreSQLREST APIs
Customer Support

AI-Powered Support Triage

Problem

A SaaS company's support team was overwhelmed with tickets. Average first-response time was over 4 hours, and priority tickets often got buried.

Solution

We implemented an AI triage system that classifies incoming tickets by urgency and topic, auto-responds to common questions, and routes complex issues to the right specialist.

Outcome

First-response time reduced to under 30 minutes. Customer satisfaction scores improved by 40%. Support team handles 3x more tickets with the same headcount.

NLPPythonAPI IntegrationAI/ML
Sales Ops

Lead Scoring & Routing Engine

Problem

Sales reps spent hours qualifying leads manually. High-value prospects were treated the same as low-intent visitors, resulting in missed opportunities.

Solution

We built a machine learning model that scores leads based on behavior signals, company data, and historical conversion patterns, then routes hot leads to the right rep instantly.

Outcome

Sales conversion rate improved by 35%. Reps now focus on the leads most likely to close. Average deal cycle shortened by 2 weeks.

Machine LearningCRM IntegrationPythonAutomation
Data Pipelines

Automated ETL Pipeline

Problem

A healthcare company needed to consolidate patient data from legacy systems into a modern data warehouse, but manual exports were unreliable and time-consuming.

Solution

We designed and deployed automated ETL pipelines that extract, transform, and load data from 5 legacy systems into a unified cloud data warehouse with data quality checks.

Outcome

Data freshness improved from weekly to near real-time. Data quality issues reduced by 90%. Analysts gained self-serve access to clean, consolidated data.

PythonAWSPostgreSQLData Engineering
Internal Tools

Employee Onboarding Portal

Problem

Onboarding new employees took 2-3 weeks of manual coordination across HR, IT, and department managers. Tasks were tracked in spreadsheets and often fell through the cracks.

Solution

We built a custom onboarding portal with automated task assignment, progress tracking, document management, and integration with HR and IT systems.

Outcome

Onboarding time reduced to 3 days. 100% task completion rate. HR team saved 15+ hours per new hire. Employee satisfaction with onboarding improved significantly.

Next.jsNode.jsAutomationCustom Software