Tag: Organisation AI
Data & AI Transformation Without the Overwhelm: Start with a Use Case
Many business inefficiencies are hidden in plain sight. The key is knowing what to look for. The best candidates for AI-powered automation share one (or more) of these traits:
1. Time-Consuming Processes 🔹 The Challenge: Workflows that take hours or days due to manual effort.
🔹 With Verodat: AI automates repetitive tasks while ensuring data quality, compliance, and consistency.
Examples:
✔ Finance teams manually compiling month-end reports from multiple systems.
✔ Customer support teams chasing missing paperwork from clients before approvals.
2. Repeated Manual Tasks 🔹 The Challenge: Processes that happen over and over but lack automation.
🔹 With Verodat: AI streamlines workflow execution, reducing delays and human intervention.
Examples:
✔ Finance teams manually reconciling financial statements before presenting to leadership.
✔ Operations teams assigning customer inquiries manually instead of AI-powered routing.
3. Workflows Involving Multiple Systems 🔹 The Challenge: Employees constantly switching between systems, copying and pasting data.
🔹 With Verodat: Data is automatically structured, unified, and connected across platforms, eliminating manual cross-checking.
Examples:
✔ Finance teams pulling data from different ERPs to reconcile revenue.
✔ Call center agents manually pulling customer details from CRM and ticketing systems before responding.
4. Governance & Compliance Risks 🔹 The Challenge: High-risk data workflows that require manual oversight to meet compliance standards.
🔹 With Verodat: AI-powered governance ensures data accuracy, audit trails, and secure processing.
Examples:
✔ Ensuring audit trails for compliance-sensitive reporting (e.g., regulatory filings).
✔ Manually redacting PII (Personally Identifiable Information) before sharing internal reports.
5. Decision-Critical Workflows 🔹 The Challenge: Processes where data delays lead to errors or inefficiencies.
🔹 With Verodat: AI-driven data structuring ensures real-time, accurate insights for decision-making.
Examples:
✔ Procurement teams making supplier decisions based on outdated cost estimates.
✔ Insurance risk teams assessing claims with incomplete data.
6. Workflows Dependent on Customer or Stakeholder Input 🔹 The Challenge: Teams spending hours chasing approvals, updates, or missing information.
🔹 With Verodat: AI-powered agents automate follow-ups, track responses, and update records in real-time.
Examples:
✔ HR teams manually collecting and verifying employee data for compliance audits.
✔ Sales teams relying on back-and-forth emails to close deals instead of automated contract tracking.
Real-World Examples of AI & Data Use Cases
Instead of starting from scratch, here are real business examples of how organizations have identified their AI use cases:
1. Payroll Automation in Construction
A leading construction firm found that payroll processing took 14 hours per cycle because:
✔ Data came from three disconnected systems (BrightHR, Sage Payroll, Xero).
✔ Manual data entry & verification steps caused bottlenecks and errors.
✔ Errors required rework & extra validation, slowing everything down.
Verodat automated data integration, cutting payroll processing from 14 hours to just 1 hour while ensuring 100% auditability and compliance.
2. Insurance: Automating Bordereaux Data Processing
An insurance firm was processing bordereaux files manually, dealing with:
✔ Inconsistent data formats across multiple carriers & brokers.
✔ Delays in claims & premium reconciliation.
✔ Compliance risks due to lack of audit trails.
With Verodat:
✅ Data was automatically cleaned & structured, ensuring a standardized format.
✅ AI-driven reconciliation sped up bordereaux processing by weeks.
✅ Compliance was built in, eliminating regulatory risks.
3. HR: Automating Compliance-Ready Workforce Reporting
An engineering company was pulling workforce data manually from multiple systems, causing:
✔ Data inconsistencies across HR & finance systems.
✔ Manual work taking nearly a full day each month to reconcile reporting.
✔ Limited flexibility in Power BI dashboards, requiring constant rework.
With Verodat:
✅ AI-powered rule-building automated data mapping, ensuring real-time accuracy.
✅ A structured, high-performing Snowflake database replaced fragmented spreadsheets.
✅ HR & finance teams gained instant access to clean, governed workforce data.
Your Turn: Define Your Own Use Case
With Verodat, AI adoption isn’t a massive, disruptive overhaul—it’s a strategic, step-by-step transformation.
Start by answering these:
✅ What’s an area in your business that takes too much time?
✅ Does this process involve multiple disconnected systems?
✅ Is this process dependent on stakeholder follow-ups or approvals?
✅ What would happen if this process was automated?
Instead of AI struggling with inconsistent, unstructured data, Verodat ensures AI-powered automation delivers scalable efficiency, governance, and trust.
📌 Get in touch & start defining your AI use case today.
Other resources
Check out some of our additional resources and find out why the future of AI for business depends on data.
How Pen Underwriting Cut Bordereaux Processing Time by 94% with Verodat
The Results:
📉 94% Faster Processing – Reports that took hours now run in minutes
📈 Enhanced Transparency – Improved visibility & understanding of partner data
🔒 Governed Data Management – Eliminated bottlenecks & ensured compliance
👨💼 Empowered Users – Business teams can process data with just a few clicks
👉 Want to eliminate manual data headaches?
💬 Let’s talk about how Verodat can streamline your data operations.
The Client:
Pen Underwriting, a virtual insurer, manages over 500 cover holders and processes 400 bordereaux reports monthly. However, inconsistent data formats and manual consolidation caused inefficiencies and delays in reporting.
By adopting Verodat’s data supply chain management tool, Pen Underwriting transformed its data preparation process, achieving:
✅ 94% faster bordereaux processing
✅ Automated data consolidation across systems
✅ Improved transparency & governance
The Challenge:
Partner systems generated bordereaux reports in varied formats, creating operational overhead for the operations team.
- Significant delays in formatting & consolidating data
- Inconsistent data structures affecting downstream processing
- Slow market response times due to inefficient data handling
The Solution:
Pen Underwriting implemented Verodat to standardize and automate data workflows:
🚀 End-to-end data preparation in one platform
🔄 Automated data collection, cleansing & transformation
📊 Integrated partner data into downstream systems
Key Features:
✅ Built-in mapping for governance rules & auditability
✅ Data enrichment for smarter business decisions
✅ Self-service automation—reducing IT dependency
Other resources
Check out some of our additional resources and find out why the future of AI for business depends on data.
How an Engineering Firm Cut Payroll Processing Time from 14 Hours to Just 1 Hour
🚀 Verodat helped an engineering client eliminate manual data entry, reduce errors, and speed up payroll processing by 90%. Here’s how.
The Solution: AI-Powered Payroll Data Automation
📊 The Results: 90% Time Savings in Payroll Processing
📞 Want to streamline payroll like this? Let’s talk!
🚀 Payroll processing time reduced from 14 hours → 1 hour
🚀 Eliminated manual errors & duplicate data
🚀 Created a seamless, automated payroll workflow
With Verodat, the finance team no longer dreads payroll day—it just works. 💡
🔍 The Challenge: A Fragmented Payroll Process
Managing payroll in the engineering sector is more complex than it should be. Between tracking hours, calculating tax and overtime, and ensuring accurate financial reporting, finance teams spend hours manually moving data between disconnected systems.
One of our engineering clients was facing serious inefficiencies in payroll management. Their systems—BrightHR for time tracking, Sage for payroll, and Xero for financial reporting—weren’t connected, forcing them into a slow, error-prone manual process every two weeks.
Before using Verodat, the company faced several payroll issues:
- Data Silos – Payroll, time tracking, and finance systems didn’t communicate.
- Manual Data Entry – Copy-pasting from system to system led to errors.
- Time-Consuming Process – Payroll took 14 hours every pay cycle.
This meant their finance team was spending valuable time on admin instead of strategic work.
⚙️ The Solution: AI-Powered Payroll Data Automation
Verodat seamlessly connected their payroll stack, eliminating manual work. Here’s what changed:
✅ Automated Data Syncing – No more manual input across systems.
✅ Error Reduction – No more duplicate entries or miscalculations.
✅ Time Savings – Payroll now processes in just 1 hour instead of 14.
Other resources