Representative examples of automation and AI implementations with measurable outcomes.
These case studies are based on real project patterns but represent sample implementations to protect client confidentiality.
Mid-Market Professional Services Company
A growing professional services firm was processing 800+ invoices per month manually. Their finance team spent 60+ hours each month on:
Pain points:
We designed and implemented an end-to-end invoice processing automation workflow:
Email monitoring with PDF extraction (OCR) and data validation
Automatic matching against purchase orders and contracts
Smart routing based on amount, department, and vendor
Automatic creation of invoice records and payment schedules
Alerts for discrepancies, missing POs, or approval delays
Processing time reduced from 60 hours/month to 24 hours/month
Labor savings + error reduction + avoided late fees
92% of invoices processed with zero human touch
Down from 5–7 days to 1.5–2 days
Discovery & process mapping
Build & testing
Pilot & refinement
Full deployment
Mid-Market Logistics & Delivery Company
A regional logistics company managed 200+ daily deliveries across 50+ drivers. Their dispatch and delivery operations faced critical inefficiencies:
Business impact:
We built an offline-first Progressive Web App (PWA) for drivers that integrates intelligent routing, real-time tracking, and seamless POD capture:
Automated route optimization based on delivery windows, vehicle capacity, and geolocation
Dynamic load distribution with real-time driver availability and vehicle capacity
Intelligent GPS tracking (30-60s sampling) with offline storage and background sync
Mobile barcode scanning, digital signatures, and photo capture with offline queuing
Works fully offline with automatic sync when connectivity is available
On-Time-In-Full rate improved from 68% to 94%
Daily route planning reduced from 2+ hours to 15 minutes
Proof of delivery reduced from 5 min to 1 min per stop
Labor, reroutes, and customer retention
Discovery & dispatch workflow mapping
PWA development, offline sync, APIs
Pilot with 10 drivers
Full rollout to all 50 drivers
Enterprise SaaS Platform (B2B)
An enterprise SaaS company's IT support team received 200+ tickets daily across multiple channels (email, Slack, web portal). Their challenges:
Business impact:
We built an AI agentic system that automatically triages, enriches, and routes support tickets:
LLM-powered agent classifies tickets by category, urgency, and complexity
Vector search across past tickets, documentation, and known issues
Agent calls APIs to pull system logs, user info, and environment data
Routes to appropriate team based on skills, workload, and expertise
High-priority tickets flagged for immediate human review
75% of tickets fully triaged and routed with zero human touch
Down from 2 days to 6 hours (first response under 30 min)
Mis-assigned tickets reduced from 30% to 12%
Customer satisfaction scores increased 18 points
Discovery, data prep, agent design
RAG setup, tool integration, evals
Pilot with 50 tickets/day
Full production rollout
Mid-Market Manufacturing Company
A manufacturing company's legal team reviewed 40+ vendor and customer contracts monthly. Each contract review took 12–16 hours of attorney time:
Business impact:
We built an AI-powered contract analysis workflow with human oversight:
Upload portal with PDF parsing and text extraction
LLM identifies and extracts key clauses (90+ clause types)
Automated flagging of non-standard or high-risk terms
Compare against company playbook and past contracts (RAG)
Auto-generated summary with negotiation recommendations
Review time reduced from 12–16 hours to 3–5 hours
90%+ accuracy in identifying key clauses
Legal time savings + faster deal cycles
Legal review time reduced from 14 days to 5 days
Discovery, playbook review
Agent build, RAG setup, UI
Testing with 20 contracts
Full deployment
Every business has unique challenges. Let's discuss how automation and AI can deliver measurable value for your operations.