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Case Studies — Anonymized Client Engagements

Engineered Results

Every engagement starts with an operational problem and ends with a measured outcome. These are anonymized studies from real systems we've built.

Book a Strategy Call How We Work
$1M–$20M+Client revenue range
4.2xAvg ROI in 12 months
37%Cycle time reduction

01 Case Studies

Real systems. Measured outcomes.

Revenue Workflow Engineering

Service Company — $3.2M Annual Revenue

A commercial services company doing $3.2M in annual revenue was losing 12–15% of billable work to administrative friction. Quotes were generated manually in Word documents. Invoicing happened weeks after service delivery. Payment collection averaged 47 days.

Operational friction

Quoting process required 3 people and took 2–4 days per quote

No connection between quoting system and invoicing

Field teams recorded work on paper, transcribed later

Revenue recognition lagged actual delivery by 3–6 weeks

Collections had no automated follow-up process

System engineered
01

Custom quoting engine pulling from service catalog and pricing rules

02

Automated quote-to-invoice pipeline triggered by job completion

03

Mobile field reporting integrated with job management system

04

Real-time revenue dashboard with aging receivables alerts

05

Automated payment reminder sequences with escalation rules

Also measured
Invoice cycle time cut from 3–6 weeks to same day
1.5 FTE of admin headcount reallocated to operations
Learn about Revenue Workflow Automation
Measured outcomes
15 min Quote generation time — down from 2–4 days
19 days Days sales outstanding — down from 47
$410K Revenue recovered annually from billing gaps
AI Operations Engineering

Distribution Company — $8.5M Annual Revenue

A regional distribution company processing 400+ orders daily was drowning in manual data entry and classification. Customer purchase orders arrived in dozens of formats — email, PDF, fax, portal. Each required manual reading, data entry, and routing. Error rates were climbing with volume.

Operational friction

Order processing required a 4-person team working full shifts

Average order entry time: 12 minutes per order

Error rate on manual entry: 6.2% — causing returns, credits, customer friction

No standardized classification — routing decisions were tribal knowledge

Scaling required linear headcount increases

System engineered
01

AI document extraction pipeline for multi-format purchase orders

02

Automated classification and routing engine with confidence scoring

03

Exception handling workflow for low-confidence extractions (human-in-the-loop)

04

Integration with existing ERP for direct order creation

05

Monitoring dashboard tracking accuracy, processing time, and exception rates

Also measured
Processing team cut from 4 FTE to 1 FTE — now focused on exceptions
Daily processing capacity up from 400 to 1,200+ orders without added staff
Learn about AI Operations
Measured outcomes
45 sec Automated order processing time — down from 12 minutes
0.8% Error rate — down from 6.2%
$185K Annual labor cost savings
Architecture & CTO Advisory

Professional Services Firm — $12M Annual Revenue

A growing professional services firm with 80+ employees had operational data spread across 6 disconnected platforms. Financial data in one system. Project management in another. Resource allocation in spreadsheets. Client data in a CRM that nobody trusted. Leadership couldn't answer basic questions about profitability by service line or utilization rates without a week of manual analysis.

Operational friction

6 disconnected data systems with no integration

Monthly financial close took 3 weeks of manual reconciliation

Utilization reporting was done quarterly in spreadsheets — always stale

No single source of truth for client or project data

Every new tool added another silo — tech stack was 14 platforms deep

System engineered
01

Unified data architecture on PostgreSQL with dimensional modeling

02

Cloud infrastructure on AWS with managed services for cost efficiency

03

ETL pipelines connecting all 6 source systems to the central warehouse

04

Real-time operational dashboards: utilization, profitability, pipeline, cash flow

05

API layer enabling future system additions without architectural changes

06

Reduced platform count from 14 to 6 through consolidation

Also measured
Utilization visibility moved from quarterly spreadsheets to real-time
Profitability analysis automated — refreshed daily instead of manually
Learn about Cloud Architecture
Measured outcomes
3 days Monthly financial close — down from 3 weeks
$96K Annual SaaS savings — platform count cut from 14 to 6
Minutes To answer leadership data questions — down from days

02 Engineered Results

Across all engagements.

37%

Average reduction in revenue cycle time

$2.1M

Revenue recovered from workflow automation

68%

Reduction in manual data entry across clients

4.2x

Average ROI within 12 months of deployment

03 Next Step

Ready to engineer your revenue system?

These results came from businesses that recognized a simple truth: operational friction is a choice. The systems underneath your business can be engineered for leverage, or they can continue costing you margin. Book a strategy call and we'll diagnose where your biggest operational leverage is hiding.

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