The architecture behind
every result.

RootN doesn't sell automation as a concept. We deploy it as engineered infrastructure. This is how we think — and how we build — across every engagement.

Microsoft 365 Power Automate · Forms · SharePoint · Plumsail
Python Systems pandas · ReportLab · win32com · openpyxl
Document Intelligence PDF generation · classification · dispatch
API Integration B2W · ERP connectors · REST pipelines
Governance Audit trails · error handling · sustainment

Workflow Waste
Identification

Every automation engagement starts with a diagnostic — not a sales conversation. We map your existing operational processes in detail, identify where time is being consumed by work that produces no marginal value, and quantify the cost of that waste against your organization's actual labor rates and throughput requirements.

Most organizations are surprised by what they find. Workflows that feel necessary are often fully automatable. The discipline here is asking: "Who is doing this, how long does it take, and what exactly would break if a system did it instead?"

  • End-to-end process mapping across departments and systems
  • Time-and-motion analysis on recurring manual tasks
  • Cost quantification against actual loaded labor rates
  • Automation feasibility scoring per workflow
  • Priority sequencing by ROI, risk, and deployment complexity
  • Dependency identification for cross-system workflows
Typical Waste Discovery
Workflows that are fully automatable
68%
Tasks with zero strategic human value
82%
Cross-system manual data entry
91%
Recurring report generation (automatable)
96%
Output

A ranked automation roadmap with estimated ROI, deployment sequence, and resource requirements — delivered within 2 weeks of diagnostic start.

Architecture Coverage
Legacy system compatibility
95%
Data transformation accuracy
99%+
Integration test coverage
100%
Manual sync tasks eliminated
88%
Connected Platforms

B2W · SAP · Microsoft 365 · Salesforce · SQL Server · Excel · SharePoint · Custom ERP

Data Flow
Architecture

The failure mode of most automation projects isn't bad code — it's an inability to move data reliably between systems. We design the data layer first. Every integration is built with clear transformation rules, validation logic, and rollback capability before any automation layer is built on top.

This is where engineering discipline matters most. A workflow that reads from a live operational database, transforms records, and writes to a downstream platform without error or data loss requires a fundamentally different approach than a simple task automation.

  • Source system data model analysis and schema mapping
  • ETL pipeline design with transformation and validation rules
  • Cross-platform connector configuration and testing
  • Error detection, logging, and automatic recovery flows
  • Data integrity verification at every pipeline stage
  • Real-time and scheduled sync architecture

Microsoft 365
Automation

Most enterprise organizations are already paying for the infrastructure that can eliminate their most time-consuming manual workflows. Power Automate, Microsoft Forms, SharePoint, and Outlook together form a capable automation backbone — when configured by engineers who understand what it can actually do.

We have built production flows that handle meter reading updates, bulk timecard approvals via UI automation, location change synchronization, and end-to-end PDF generation pipelines — all running inside M365 without additional infrastructure.

  • Power Automate flow design, build, and production deployment
  • Microsoft Forms → PDF generation pipelines using Plumsail connector
  • UI automation on platforms with no API (RPA via Power Automate Desktop)
  • SharePoint-integrated document workflows and approval routing
  • Scheduled data sync flows between Excel, SharePoint, and external systems
  • Automated Outlook dispatch with dynamically generated attachments
  • Conditional logic, branching, and structured exception handling within flows
Discuss Your M365 Stack
Deployed in Production
Eclipse Hour Update Weekly meter reading sync — 4h manual reduced to 20min automated
Timecard Approval Flow UI automation on B2W — bulk approvals without human intervention
Location Change Automation Excel → B2W machine location sync, zero manual entry required
Digital Timesheet System MS Forms → Power Automate → Plumsail PDF — $300k/yr labour cost eliminated
Dummy Purchase Order Flow Automated PO creation to satisfy accounting system pre-requisites
Core Python Libraries
pandas Data manipulation, transformation, and analysis across large file sets
ReportLab Programmatic PDF generation — contractor reports, confirmations, statements
win32com / Outlook Automated email dispatch with dynamically generated PDF attachments
openpyxl / xlwings Excel file reading, writing, and structured report output
PyPDF2 / pdfplumber PDF parsing, classification, and splitting by embedded document codes

Python-Based
Systems

When Microsoft 365 hits a complexity ceiling, Python takes over. For computationally intensive operations — financial modeling engines, document batch processing, data scanning across large file repositories — Python gives us the precision, speed, and programmatic control that no low-code platform can match.

Every Python system we deploy is built for repeatability. It runs the same way on the hundredth execution as the first. No manual steps, no human judgment required in the loop — just structured input, defined logic, and verified output.

  • LCC model automation — full lifecycle cost analysis engine, wks → hrs
  • Payroll file processing — splitting, classification, sorting by employee type
  • PDF classification and splitting by embedded codes (Maintenance vs Operations)
  • Labour cost tracking per machine, per component, across all timesheets
  • Contractor confirmation system — bi-weekly PDF generation and Outlook dispatch
  • Expense categorization scanning across large document repositories
  • Structured data extraction from unstructured operational document sources
Discuss a Python Build

Document & Reporting
Automation

Document generation is one of the most time-consuming, error-prone activities in any administrative-heavy organization. Producing PDFs, filling templates, dispatching reports, and filing records — all of it is fully automatable once the source data is structured correctly.

We have built systems that generate hundreds of PDFs daily from form submissions, dispatch them automatically via email, classify incoming documents by reading embedded codes, and route them to the correct downstream system — all without a human in the loop.

  • PDF template design and automated population via Plumsail and ReportLab
  • High-volume document generation pipelines (90+ documents per day, sustained)
  • Intelligent PDF classification by content pattern and embedded codes
  • Automated dispatch via Outlook with dynamic attachments and recipient routing
  • Bi-weekly contractor hour confirmation — automated generation and delivery
  • Reporting pipeline design: daily, weekly, and on-trigger delivery schedules
  • Document archival and SharePoint filing automation
Document Pipeline Performance
Manual document handling eliminated
94%
Generation error rate (production)
<2%
PDF classification accuracy
99%+
Time-to-dispatch after form submit
<3 min
Tools Used

Plumsail · ReportLab · Power Automate · Outlook (win32com) · SharePoint · PyPDF2

Integration Architecture
Manual data re-entry eliminated
100%
Cross-system sync latency
<60s
Error propagation blocked upstream
97%
Audit log completeness
100%
In Development

B2W API integration for direct timesheet entry — eliminating the final human step in the digital timesheet pipeline.

API Integration
Strategy

When UI automation and file-based data exchange reach their limits, APIs provide the highest-fidelity, highest-reliability integration path between systems. We design API integration strategies that connect platforms directly — eliminating the data quality degradation that comes from indirect sync methods.

Where APIs don't exist or are restricted, we apply UI automation as a precision bridge — replicating human clicks at machine speed and scale, with validation logic to catch errors that human operators would miss.

  • REST API integration design and implementation
  • Authentication architecture (OAuth, API keys, token refresh)
  • Webhook-driven event automation for real-time downstream sync
  • UI automation fallback where API access is unavailable
  • Rate limiting, retry logic, and upstream error propagation control
  • B2W platform integration — timesheets, machine data, and cost records
  • ERP and field management system connectivity
Discuss API Integration

Governance &
Sustainment

A system that works in the first week and breaks in the third is not a deployment — it's a liability. Every automation RootN delivers is built with production-grade error handling, monitoring hooks, and documentation that makes it maintainable by anyone who inherits it.

We don't disappear after deployment. Our sustainment model is designed so that your team can operate, monitor, and extend what we build — while RootN remains available to evolve the system as your operations change.

  • Full audit trail design — every action logged with timestamp and actor
  • Structured error handling with automatic alerting on failure
  • Fallback and recovery logic for network, API, and data exceptions
  • Operator-facing documentation — what runs, when, and why
  • Handoff protocols and internal training for system ownership transfer
  • Monitoring architecture for live production systems
  • Version control and change management for all deployed automations
System Health Standards
Production uptime target
99.7%
Documented processes (100% required)
100%
Exceptions with alert coverage
100%
Mean time to recovery (MTTR)
<2h
Standard Deliverable

Every deployment includes a system runbook, error escalation protocol, and a 90-day sustainment support window.

You already know what's
costing you time.
Let's eliminate it.

Book a diagnostic session. We'll walk through your current workflows, identify the highest-value automation targets, and give you a concrete picture of what the build looks like — before any commitment.