🎯 The Problem Most Organisations Face

AI pilots are everywhere. But pilots don’t equal progress.

Most organisations hit a wall when trying to bring AI into day-to-day operations. The problem isn’t the models. It’s that enterprise data isn’t ready to support AI agents in a secure, structured way.

That’s where Verodat comes in.

🧠 What Makes Verodat Different

We don’t just connect to your systems—we turn your data into an operational layer that AI agents can act on with confidence.

✔️ Real-time data from 600+ sources
✔️ Embedded metadata, supply awareness & governance
✔️ Agent-safe architecture (supports natural language, approved SQL, and AI-native access)
✔️ Full visibility for audit and compliance teams

In short, we remove the friction between your data and your ambition.

Beyond Co-Pilots: Unlocking the Future of AI in Your Org

Getting your data AI-ready isn’t just about enabling existing tools. It’s the critical first step toward:

• ✳️ Building AI agents that automate decisions and workflows

• ✳️ Generating real-time briefing notes and stakeholder updates

• ✳️ Enabling cross-system intelligence without manual overhead

• ✳️ Scaling AI securely, with governance built in

Verodat’s lean data management approach supports all of this—and more—with zero disruption to your existing infrastructure.

Unlocking Workflow Readiness for AI in Specialty Insurance

In Oxbow Partners’ recent Generative AI in Specialty and Reinsurance report, the message is clear: AI is coming—but most insurers aren’t ready.

The standout takeaway?

“At the moment we’re getting other things fixed, like our internal data.”

From underwriting ops to compliance, every AI opportunity hinges on one thing: workflow and data readiness.

The Governance Gap

While AI use cases are being scoped across exposure management, portfolio analytics, and risk ops, the most urgent blockers are foundational:

• ⚠️ Broken or delayed internal workflows

• 🧩 Fragmented data sources with poor quality controls

• 📉 Document extraction tools dropping to 80% accuracy

• 🔐 Internal resistance due to governance and compliance risk

These aren’t AI problems—they’re data problems.

How Verodat Helps You Get Ready

Verodat is built for insurance data complexity. Our lightweight governance layer helps specialty insurers move fast—without cutting corners on trust, auditability, or compliance.

Here’s how:

✅ Governance Built In
Attach context, ownership, and supply history to every dataset
→ Perfect for delegated authority oversight and audit reporting

✅ Process Automation Without Uplift
Link data across brokers, coverholders, and internal teams
→ Eliminate duplicative manual work in underwriting operations

✅ Full Traceability
Every number, document, and report has a visible, provable source
→ Pass compliance audits in hours, not weeks

✅ AI-Ready by Default
Your governed data layer powers the next generation of insights
→ When you’re ready for AI, your data already is

Why Excel Feels Familiar — and Fails Fast

We get it. Excel is easy, flexible, and everywhere. But when your business depends on reliable data, it becomes a fragile foundation.

• One broken formula = one broken forecast

• No audit trail = no trust

• Version 37_final_FINAL.xlsx = total confusion

Sound familiar?

Excel Wasn’t Built for Today’s Data Challenges

Modern business moves fast. Your data sources are growing, your teams are remote, and your reporting needs are real-time. Excel was never meant to handle this.

That’s where Verodat comes in.

How Verodat Transforms the Way You Work

Verodat connects, cleans, and governs your data — so you never have to second-guess a number again.
Whether you’re reporting for a regulator, briefing the board, or training your first AI agent, Verodat gives you:

✅ One Source of Truth – governed, live, and audit-ready
✅ AI-Ready Data – structured and enriched with business context
✅ Less Manual Work – no more chasing down broken links or updating 10 versions of the same file
✅ Real-Time Visibility – your data, as it actually is, not as it was last week

We’re thrilled to be recognised as a finalist in the 2025 Tech Excellence Awards. The nomination reflects the real-world impact of Verodat’s technology — giving enterprises the control layer they need to unlock operational AI, not just AI experiments.

But what does it actually mean to run production-grade AI? And why are more clients turning to Verodat to bridge the gap between ambition and reality?

Why AI Pilots Often Fail

Most organisations already have AI initiatives underway — yet few have successfully moved beyond pilot projects.

What’s missing isn’t intent or investment. It’s infrastructure.

Inconsistent updates, fragmented systems, and lack of metadata all block automation. Even the best agents struggle when they don’t know whether the data they’re using is complete, current, or compliant. That’s where Verodat comes in.

Where Verodat Fits

Verodat provides the data supply and governance layer needed to move AI out of the lab and into the business. It:

• Defines what agents can query, when, and under what conditions

• Provides real-time supply status and metadata for every dataset

• Supports human-led queries and AI-generated logic side by side

• Works with your existing systems — no need for a full data overhaul

In short, Verodat is how AI becomes operational.

Real Results from Real Clients

One client cut payroll reporting effort by over 80% within three weeks by implementing a Verodat-powered AI agent. Another deployed geolocation-triggered executive briefings with fully auditable, compliant data.

Clients include:

• Pen Underwriting

• Cairn Homes

• Sammin Engineering

• Covéa

• The Irish Times Group

Verodat is enabling automation securely, at scale, and across sectors.

Why It Matters Now

While many are still preparing for AI, Verodat is powering it today.

This award nomination isn’t just about innovation — it’s about execution. We’re proud to lead the way in operational AI, giving teams the structure they need to deliver real business outcomes without compromise.

The Evolution of Data Management

Traditional ETL platforms focus on one primary goal: streamlining the creation of data pipelines without extensive engineering resources. With pre-built connectors and basic transformation tools, they certainly solve the immediate challenge of data movement.

But here’s the reality check: as your organization matures in its data journey, you’ll inevitably outgrow simple ETL capabilities.

The Real Business Value

The differences between basic ETL and ETL++ aren’t just technical distinctions—they translate to measurable business advantages:

• Reduced Compliance Risk: With regulations like GDPR, NIST, DORA, and the AI Act expanding globally, native governance capabilities become essential
• Accelerated AI Implementation: When data is inherently structured for AI consumption, deployment time decreases by months
• Enhanced Decision Confidence: Auditability and provenance tracking increase trust in data-driven decisions
• Future-Proofed Architecture: As data regulations evolve, an ETL++ approach adapts without requiring architectural overhauls

Is Your Data Strategy Future-Ready?

Ask yourself these questions:

1. Can you trace the exact provenance of critical business data?
2. Is your data structured appropriately for safe AI agent interaction?
3. Does your current solution provide enterprise-grade auditability out of the box?
4. Can you confidently meet emerging AI governance requirements?

If you answered “no” to any of these questions, your organization might be outgrowing basic ETL capabilities.

Take the Next Step

Don’t wait until compliance requirements, AI initiatives, or governance challenges force a rushed solution. Explore how Verodat’s ETL++ approach can transform your data strategy from simple pipelines to comprehensive, future-ready data management.

Unlocking Workflow Readiness for AI in Specialty Insurance

In Oxbow Partners’ recent Generative AI in Specialty and Reinsurance report, the message is clear: AI is coming—but most insurers aren’t ready.

The standout takeaway?

“At the moment we’re getting other things fixed, like our internal data.”

From underwriting ops to compliance, every AI opportunity hinges on one thing: workflow and data readiness.

The Governance Gap

While AI use cases are being scoped across exposure management, portfolio analytics, and risk ops, the most urgent blockers are foundational:

• ⚠️ Broken or delayed internal workflows

• 🧩 Fragmented data sources with poor quality controls

• 📉 Document extraction tools dropping to 80% accuracy

• 🔐 Internal resistance due to governance and compliance risk

These aren’t AI problems—they’re data problems.

How Verodat Helps You Get Ready

Verodat is built for insurance data complexity. Our lightweight governance layer helps specialty insurers move fast—without cutting corners on trust, auditability, or compliance.

Here’s how:

✅ Governance Built In
Attach context, ownership, and supply history to every dataset
→ Perfect for delegated authority oversight and audit reporting

✅ Process Automation Without Uplift
Link data across brokers, coverholders, and internal teams
→ Eliminate duplicative manual work in underwriting operations

✅ Full Traceability
Every number, document, and report has a visible, provable source
→ Pass compliance audits in hours, not weeks

✅ AI-Ready by Default
Your governed data layer powers the next generation of insights
→ When you’re ready for AI, your data already is

AI adoption is accelerating—but without data governance, the risk grows faster than the rewards.

From copilots to autonomous agents, the enterprise AI stack is expanding. Yet most businesses still lack the traceability, validation, and permission layers needed to safely scale AI.

In a recent visual summary by policy researcher Oliver Patel, the top governance challenges for AI in enterprise settings were made clear:

• ⛔️ Lack of oversight of what LLMs access

• ❓ Uncertainty over data provenance

• 🔓 Gaps in access control and validation

• 🔍 No audit trail to support compliance or explainability

🔑 Key Challenges Facing AI Governance Today

These are the governance questions that every enterprise deploying GenAI must answer:

1. What data is available to my AI tools?
Without centralised metadata and permissioning, there’s no visibility into what LLMs are using—or worse, misusing.

2. Is the data up-to-date and validated?
AI hallucinations often stem from outdated, incomplete, or low-trust inputs. Without real-time validation, you’re gambling with your decisions.

3. Who approved access to this data?
A lack of audit trails can create compliance bottlenecks and operational risk.

4. Can we explain the AI’s outputs?
Explainability isn’t optional—especially as regulations like the EU AI Act and NIS2 demand it.

✅ How Verodat Enables AI Governance, by Design

Verodat solves this by giving you a governed AI-ready data layer with built-in traceability and control.

• Context & Provenance Built In
  Every dataset carries metadata about where it came from, when it was last updated, and what it’s valid for.

• Supply Status & Completeness Flags
  Your AI agents don’t just pull data—they know whether it’s fresh, complete, and approved.

• Certificate IDs & Full Audit Trails
  Every data point can be traced back to its source, enabling full compliance reporting.

• Control for Human or Agent
  Whether it’s a human analyst or an AI agent, Verodat ensures only approved, high-trust data is used.

🧠 Why This Matters Now

We’re moving into a world of autonomous decision-making and fast-moving AI systems.

You can’t scale AI without governance.

With Verodat, governance doesn’t slow you down—it accelerates your adoption by:

✔️ Meeting compliance mandates proactively
✔️ Empowering teams to use AI safely
✔️ Enabling faster rollout of copilots and agents
✔️ Making data trustworthy and explainable

💡 The Problem with Traditional Bordereaux Pricing

Most vendors in the bordereaux space price by:

• Number of binders

• Number of submissions

• Or total volume processed

That might make sense for outsourced manual work—but not for automated, governed data processes.

When your pricing is tied to volume, you’re disincentivized to scale.

✅ The Verodat Model: Disruptive by Design

Verodat’s pricing flips the industry standard on its head.

We price based on value delivered, not the number of binders processed. That means:

• More business doesn’t mean more cost

• Automated processes are repeatable with zero incremental admin

• Your cost-per-use-case decreases as you grow

This isn’t just cost-effective—it’s operationally scalable. One client processes dozens of bordereaux submissions without any offshore support or added headcount.

They didn’t have to hire.
They didn’t have to pay by binder.
They just turned on Verodat—and scaled.

🔁 What It Looks Like in Practice

Verodat automates the entire bordereaux workflow:

• Ingests raw claims and premium data

• Structures it according to each binder’s specifications

• Pushes final outputs to systems like VYPR

• Tracks all changes and submissions for full auditability

This same flow runs on a schedule, with no human intervention.

And because the infrastructure is already in place, adding a new binder doesn’t increase the workload or the price.

🔐 Governed, Compliant, and Audit-Ready

Every data point in Verodat is:

• Traceable

• Validated

• Governed

No more spreadsheets passed between teams.
No more manual cut/paste.
No more scrambling for audit evidence.

With Verodat, you don’t just get automation.
You get governance and compliance by default—something few vendors offer.

🧠 Why It Matters Now

With rising regulatory scrutiny and tighter margins in insurance, every efficiency gain matters.

Our pricing is aligned with your growth, not stacked against it. It empowers underwriting and operations teams to scale faster, at a lower cost, and with better data.

The Bouncer at the Door Approach

In the world of business reporting, there’s a familiar scenario that plays out too often:

A report shows unexpected numbers. Someone questions the data. The person responsible breaks into a cold sweat, frantically digging through spreadsheets, tracing data lineage, and questioning every step of their process.

As our CEO Thomas Russell explains: “What happens typically is people build reports at the edge—like a solution inside the house—and this works… it works and then the numbers start to creep off or they look unusual and somebody goes ‘hey that doesn’t look right.’ The person in the room gets a cold sweat going ‘what did I do wrong?’ And they go back trying to figure out and they’re pulling a thread and trying to find data…”

This scenario is familiar because it’s universal. Organizations build reporting solutions that work temporarily, but they’re built on shaky foundations. When questions arise (as they inevitably do), panic ensues.

This approach is backward. Adding another reporting layer to systems built on systems only increases complexity and risk.

At Verodat, we focus on ensuring your data is clean and validated at the point of entry – like a bouncer at the door, only letting quality data through. Instead of reporting at the edge of systems, you’re focusing on ensuring that your source data is clean.

Why This Matters Now

This shift is particularly crucial in today’s business environment for three reasons:

• Audit requirements are increasing: Regulators want to see not just your data, but how you ensure its accuracy
• Decision speed is accelerating: Waiting days to verify numbers is no longer acceptable
• AI adoption demands quality data: AI systems amplify data quality issues – garbage in, garbage out at scale

Beyond Reporting: The Foundation for AI-Ready Data

When you fix your data foundation, everything pointing to it works correctly. Reports become trustworthy not because you’ve added more validation layers, but because the source itself is impeccable.