Author Archives: Sydney Pujadas

A new year offers more than a symbolic clean slate. For organizations, it is a critical checkpoint to ensure their cloud strategy still aligns with evolving business goals, regulatory requirements, and security threats. The cloud architecture that worked well several years ago may now create unnecessary expenses, performance challenges, or operational risk as organizations adopt AI, modernize applications, and support distributed workforces.

For many mid-sized organizations, cloud transformation has been ongoing rather than a single milestone. With rapid changes in cloud services and rising cyber insurance expectations, the start of a new year is the perfect time to reassess the environment and identify opportunities to optimize.

Evaluate What’s Working and What Isn’t

Cloud environments change quickly as new technology and temporary fixes accumulate. What once operated efficiently may be fragmented or oversized. An internal annual review can help identify whether workloads are properly sized, if performance has degraded, and whether or not security controls still match today’s standards.

Over-provisioned resources and aging architectures often create unnecessary costs and vulnerabilities for organizations. By stepping back and examining utilization, performance, and operations holistically, business leaders can gain the insights needed to streamline their cloud environment and eliminate hidden risk.

Revisit Cloud Spend and Optimizations

Cloud costs can rise gradually without notice, especially when unused services remain active or workloads use larger tiers than required. Reviewing usage patterns can uncover opportunities to better align resources with demand, shift workloads to more efficient tiers, or take advantage of reserved instances and long-term pricing models.

Organizations should also reevaluate their data storage practices. High-cost tiers are often used to store data that rarely changes or is no longer needed in the database. A clear data lifecycle approach helps reduce waste while preserving compliance and accessibility.

Strengthen Cloud Security and Compliance

Security and compliance expectations continue to expand, especially as cyber insurers require stronger controls across identity, access, and monitoring. An annual New Year assessment should examine how well current architectures align with zero trust principles, whether backups and recovery plans remain resilient, and whether threat detection covers multi-cloud environments.

Ensuring ongoing compliance with frameworks such as Cyber Essentials, CMMC, HIPAA, or other industry mandates is equally important. Revisiting these controls annually helps reduce the likelihood of data breaches and operational downtime.

Modernize Legacy Applications

Legacy applications are a major source of inefficiency and technical debt for organizations. They often limit automation, complicate integrations, and increase maintenance costs. A review in the new year creates an opportunity to identify which systems can be refactored, containerized, migrated to managed services, or retired altogether.

Modernizing even a few core applications can significantly improve performance, reduce risk, and support future digital initiatives.

Prepare for AI and Automation

As AI adoption accelerates across the mid-market, organizations must determine whether their cloud environments are ready to support data-intensive workloads. This includes evaluating data quality and governance, scalability, and security. Establishing these foundations early on allows companies to take advantage of AI without disrupting critical operations or exposing themselves to new vulnerabilities.

Improve Efficiency with Managed Services

IT teams are managing increasingly complex environments with the same limited time and resources. Partnering with a managed security service provider (MSSP), like Thrive, can help organizations maintain visibility, performance, and security across their cloud environment. MSSPs can also guide modernization efforts, support compliance requirements, and automate routine tasks so internal teams can focus on strategy.

Build a Future-Ready Roadmap

After assessing the current state, organizations should translate insights into a clear roadmap that outlines modernization priorities, security improvements, financial goals, and opportunities to integrate automation and AI. A focused roadmap helps ensure investments align with business objectives and provides a structured path for continuous improvement.

Start the Year with a More Strategic Cloud Approach

A well-tuned cloud strategy allows organizations to grow, innovate, and stay secure in an increasingly challenging digital landscape. Whether the goal is to optimize workloads, modernize legacy systems, or strengthen security posture, an annual reassessment provides the clarity needed to plan confidently for the year ahead. Contact Thrive today to learn more about how your cloud strategy can be taken into the year ahead.

Build the data foundation your AI strategy depends on.

Strong AI strategies fail without strong data foundations. Before organizations can turn AI investments into real business outcomes, they need data that is accurate, governed, secure, and accessible across the organization.

The AI Strategy Playbook: Data Foundations is a practical guide designed to help mid-sized organizations evaluate, strengthen, and operationalize the data capabilities required to support a successful AI strategy. Whether you are early in your AI journey or preparing to scale, this playbook helps ensure your strategy is built on data you can trust.

Financial services firms face unique pressures when choosing a productivity and collaboration platform. Beyond day-to-day usability, your choice must support stringent regulatory expectations, reduce operational risk, streamline compliance workflows, and enable long-term scalability.

Two leading platforms dominate this decision: Google Workspace and Microsoft 365 (M365). Both platforms deliver secure, cloud-native productivity environments, but each offer distinct advantages depending on your organization’s size, operational model, regulatory exposure, and technology strategy.

Business Functionality

Both Google Workspace and M365 offer competitive pricing with entry tiers starting around $6 per user per month, with scaling costs as functionality increases. The best fit depends largely on how your firm collaborates and what tools your workflows rely on.

Google Workspace

• Purpose-built for real-time collaboration.
• Google Docs, Sheets, and Slides are great for team co-authoring and lightweight workflows.
• Clean, intuitive UI; often preferred by teams that value simplicity and speed.
• Google Meet for video conferencing.
• Integrates well with cloud-native tools and lightweight web applications.

Microsoft 365

• Provides a rich, widely adopted productivity suite (Word, Excel, PowerPoint).
• Strong fit for firms that regularly exchange documents with custodians, fund administrators, clients, or partners who expect Microsoft formats.
• Teams offers unified messaging, conferencing, and optional enterprise-grade telephony.
• Automation capabilities through PowerApps and Power Automate.
• Copilot integrates deeply with Office apps and organizational data.

Takeaway: Both platforms support modern collaboration. Google Workspace excels in simplicity and real-time editing, while Microsoft shines in document-heavy workflows, complex spreadsheets, automation, and communication unification. Thrive helps organizations map these features to their business operating model.
Security

Financial services firms must implement strong encryption, access controls, threat protection, and incident response processes. Both Google and Microsoft provide secure baselines, but they differ in maturity, granularity, and ecosystem depth.

Google Workspace Security Highlights

• Strong encryption at rest and in transit.
• Straightforward administrative interface.
• Effective built-in protections against phishing and malware.
• Enterprise-tier MDM capabilities.
• Ideal for firms favoring simplicity and minimal overhead.

Microsoft 365 Security Highlights

• Encryption standards that match Google’s for both data at rest and in transit.
• More granular identity and access controls through Entra ID and Conditional Access policies.
• Deep integration with Microsoft Defender for EDR and XDR.
• Advanced SIEM capabilities through Sentinel.
• Stronger device management through Intune (MDM + MAM).

Takeaway: Both platforms provide secure environments that can meet financial services expectations. Google prioritizes streamlined, intuitive security management; Microsoft provides more customizable controls for firms that need granular policies or are scaling rapidly. Thrive ensures that either environment is configured to meet compliance expectations, not just vendor defaults.

Compliance

Regulated financial firms must address requirements such as:

• SEC and FINRA books and records
• Regulation S-P data protection and breach notification
• Marketing Rule compliance
• Business continuity and disaster recovery
• Communications archiving
• Access governance and privilege management

Neither platform alone guarantees compliance – controls, configuration, and workflow design matter most. But they offer different strengths.

Google Workspace Compliance Strengths

Supports integrations with leading compliance archiving platforms like Global Relay and Smarsh.

• Offers 17a-4 compliant retention capabilities.
• Provides data protection and DLP features, especially at higher tiers.
• Microsoft 365 Compliance Strengths
• Includes Microsoft Purview for advanced governance, classification, labeling, and auditing.
• Supports third-party archiving solutions with mature connectors.
• Offers complete visibility into data access patterns, which can be helpful for demonstrating compliance during exams.

Takeaway: Both platforms can be made fully compliant, but neither is compliant “out of the box.” The difference lies in their governance tooling and the level of insight needed for audits, reporting, and incident response. Thrive helps firms implement the right guardrails, regardless of the selected platform t.

Business Continuity & Global Footprint

Both Google and Microsoft operate on highly resilient cloud infrastructures with strong uptime SLAs.
Google Workspace emphasizes simplicity, fast recovery times, and strong backup ecosystem integrations.
Microsoft 365 offers advanced multi-geo capabilities and active-active configurations suitable for firms operating across regions.

For either platform, Thrive typically recommends off-platform backups to strengthen redundancy and improve recovery scenarios.

How Thrive Helps Financial Services Organizations

1. Strategic Platform Evaluation
We assess your workflows, regulatory obligations, risk profile, collaboration patterns, document management needs, and growth plans to determine whether Google or Microsoft is the better long-term fit.

2. Secure Implementation & Migration
Whether moving to Google Workspace or Microsoft 365, Thrive ensures:

• Identity and access controls are designed to support Zero Trust.
• MFA, Conditional Access (where applicable), and role-based access are enforced.
• Tenant configuration aligns with financial-sector expectations, not out-of-the-box defaults.

3. Compliance-Ready Architecture
We help implement:

• Books and records retention (via native tools or third parties like Smarsh/Global Relay)
• 17a-4 compliant storage setups
• Data governance policies
• Email and messaging archiving
• Backup policies that meet regulatory expectations

4. Security Hardening & Threat Detection
Thrive optimizes native Microsoft or Google security capabilities and integrates them with:

• Security operations
• Threat detection and analytics
• Incident response workflows
• Device management strategies

5. Ongoing Support & Optimization
The platform choice is only the beginning. Thrive supports your team with:

• 24x7x365 monitoring and management
• Continuous compliance alignment
• Regular configuration reviews
• Guidance as regulations evolve

Both Google Workspace and Microsoft 365 are viable platforms for financial services firms. The “better” choice depends on your organization’s structure, client base, regulatory obligations, preferred workflows, and long-term technology strategy.

The most important differentiator isn’t the platform, it’s how well it’s architected, secured, and governed. Contact Thrive today to learn more about how we can help you choose the right platform for your business needs.

Across industries, technical debt has become one of the most pressing obstacles facing IT and business leaders. It acts as a silent tax on productivity, a barrier to innovation, and a growing risk within legacy systems, outdated processes, and under-maintained infrastructure.

Technical debt isn’t simply a technology challenge, it is a business challenge. Mid-market organizations are especially impacted as cyber threats evolve, compliance pressures increase, and IT teams operate with limited time and resources. When modernization efforts, patching, or strategic updates are postponed, technical debt accumulates until it becomes too complex and costly to ignore.

Understanding Technical Debt: More Than Just Aging Technology

While outdated servers, unsupported applications, and legacy infrastructure contribute to technical debt, the root causes go deeper than old equipment.

Technical debt forms whenever short-term decisions overshadow long-term strategy.

Common contributors include:

• Postponed patches, updates, and upgrades
• End-of-life technologies still deployed in production
• Missing or outdated documentation
• Uncontrolled or poorly governed customizations
• Failure to adopt automation
• Underinvestment in essential cybersecurity controls

These issues compound over time, leading to environments that are fragile, difficult to maintain, and increasingly vulnerable to cyber threats.

The Real Cost of Technical Debt

Although delaying modernization may appear cost-effective initially, technical debt ultimately increases risk and inefficiency across the organization.

1. Heightened Cyber Risk
Unsupported, unpatched, and legacy systems are prime targets for cyberattacks. Many ransomware incidents and major breaches stem from vulnerabilities residing in outdated environments.

2. Increased Operational Costs
Aging or unstable systems require more time, expertise, and manual intervention. IT teams become stuck in a reactive cycle, limiting their capacity to support strategic initiatives.

3. Compliance and Cyber Insurance Challenges
Modern regulatory frameworks and cyber insurance policies demand strong controls and consistent patching practices. Technical debt can put organizations at risk of non-compliance and jeopardize eligibility for insurance coverage.

4. Reduced Ability to Innovate
Modernization initiatives, whether cloud adoption, automation, or AI, require a secure, stable foundation. Technical debt hampers agility and slows progress toward digital transformation goals.

Why Technical Debt Is Difficult to Solve Internally

Even with clear recognition of the risks, most mid-market organizations struggle to overcome technical debt on their own.

Key barriers include:

• Lack of internal capacity to manage modernization efforts
• Skill gaps around cloud, automation, and emerging technologies
• Budget constraints that favor short-term fixes over long-term strategies
• Legacy systems that appear functional but mask underlying vulnerabilities

These challenges underscore the importance of having experienced external support to guide modernization and reduce accumulated debt safely.

How Thrive Helps Organizations Reduce Technical Debt

Thrive supports mid-market organizations in eliminating technical debt through a modernization approach grounded in security, scalability, and operational efficiency.

Strategic Modernization Roadmaps
Thrive evaluates the existing environment, identifies high-risk and high-impact areas, and builds a structured, phased roadmap that supports long-term resilience and growth.

Comprehensive Managed IT & Security Services
From cloud modernization and automation to identity management, endpoint protection, and advanced security controls, Thrive delivers next-generation capabilities that reduce complexity and operational burden.

Security-First Architecture
Every solution is built with security in mind. Managed patching, vulnerability management, and proactive monitoring reduce exposure and help organizations meet compliance and cyber insurance requirements.

Engineered for Mid-Market Needs
Thrive’s model combines deep engineering expertise, automation-driven operations, and 24×7×365 support to help mid-market IT teams shift from reactive maintenance to value-driven strategic work.

Technical Debt Doesn’t Have to Define the Future

While every organization carries some level of technical debt, the differentiator is how effectively and proactively it is addressed. With the right strategy and the right partner, organizations can reduce risk, lower operational costs, improve user experiences, and create a resilient IT foundation capable of supporting future innovation.

Explore additional insights, best practices, and actionable guidance on managing and eliminating technical debt, and download the Thrive Technical Debt eBook today.

While many mid-market organizations are eager to tap into AI, success doesn’t come from simply deploying a new tool, it comes from detail-oriented planning, governance, and execution. A poorly designed AI project can waste an organization’s resources and increase risk, while a well-structured one can deliver measurable ROI and competitive advantage.

The path to a successful project isn’t complex, but it does require a methodical, well-defined process to ensure that the appropriate foundation is in place.

Step 1: Define Business Objectives

Every AI initiative should begin with identifying a clear business problem to solve. Whether your goal is to reduce manual IT workloads, improve customer experiences, or detect cyber threats faster, tie the AI project directly to business outcomes that matter. This ensures leadership buy-in and measurable success.

Step 2: Assess Data Readiness

AI thrives on high-quality data. Before your project begins, ask yourself:

• Data quality: Is it accurate, consistent, and complete?
• Data accessibility: Can teams access it securely when needed?
• Data governance: Are privacy, compliance, and security requirements being met?

If your organization’s data foundation is weak, prioritize improvements there before deploying AI.

Step 3: Build the Right Team

Successful AI projects require cross-functional collaboration. Bring together IT, business leaders, compliance officers, and data specialists to build a cohesive team that can deploy an AI project successfully. Define roles early, such as, who owns governance, who monitors outputs, and who ensures the AI aligns with the organization’s business goals.

Step 4: Start Small with a Pilot

Don’t launch an AI project organization-wide on day one. Begin with a focused pilot project that targets one process or department. This allows you to internally measure ROI, identify challenges, and refine before scaling. A successful pilot also helps build organizational confidence in AI.

Step 5: Monitor and Measure Success

Establish metrics tied to your original business objectives. These might include reduced costs, faster response times, improved accuracy, or enhanced customer satisfaction. Continuous monitoring ensures AI delivers ongoing value and adapts to changing business needs.

Step 6: Scale and Optimize

Once the pilot proves its worth, you can deploy AI across more processes or departments, scaling it appropriately as you go. Keep governance, compliance, and security at the core of every rollout. AI requires ongoing optimization for maximum results.

Partner With an Expert for Support

Launching an AI project internally can be overwhelming. A partner, like Thrive, helps organizations accelerate AI adoption while reducing risk. From assessing readiness to managing pilots, governance, and optimization, Thrive provides the managed AI services needed to ensure AI projects deliver real business outcomes. Contact Thrive today to learn more about how your organization can turn AI into a true driver of growth and resilience.

As organizations continue to modernize their IT environments, the cloud remains a cornerstone of digital transformation. Yet, despite its widespread adoption, one key question often arises: should your organization choose a public or private cloud environment?

While both offer scalability, flexibility, and cost efficiency compared to traditional on-premises infrastructure, understanding the differences between public vs. private cloud solutions is essential for making the right choice, one that aligns with your organization’s performance, security, and compliance goals.

What Is a Public Cloud?

The public cloud is a shared infrastructure model operated by third-party providers such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP). In this model, computing resources, such as servers, storage, and networking, are owned and managed by the provider, and multiple customers share the same infrastructure.

Organizations benefit from:

• Scalability on demand: Instantly scale resources up or down based on needs.
• Cost efficiency: Pay only for what you use, with the ability to change compute or storage resources easily since there is no need to buy hardware.
• Global accessibility: Applications and workloads can be accessed securely from anywhere.
• Rapid innovation: Take advantage of the provider’s continuous upgrades, automation tools, and emerging technologies.

However, since resources are shared, control and customization are limited, and compliance or data requirements can be more challenging to manage in certain industries.

What Is a Private Cloud?

The private cloud is a dedicated environment used by a single organization. It can be hosted on-premises or within a third-party data center, but unlike the public cloud, all resources, such as servers, storage, and networking, are isolated and customized to the organization’s requirements.

Key advantages include:

• Enhanced security and control: Ideal for organizations with strict compliance mandates or sensitive data, such as in financial services or healthcare.
• Customization and performance optimization: Resources are tailored for specific applications and workloads.
• Predictable costs: Fixed resource allocation enables consistent budgeting.
• Regulatory compliance: Easier to meet frameworks such as HIPAA, PCI-DSS, or GDPR.

That said, private cloud environments generally require greater investment and management oversight, particularly if maintained on-premises.

The Best of Both Worlds: Multi-Cloud Strategies

For many mid-market and enterprise organizations, the choice isn’t simply public vs. private. It’s both.
A multi-cloud approach integrates public and private environments, allowing organizations to run sensitive workloads in a private cloud while leveraging the public cloud for scalability and innovation.

This flexible model enables organizations to:

• Balance security and performance needs
• Optimize costs across workloads
• Improve disaster recovery and business continuity
• Support cloud-native application development

Thrive’s Approach: Building the Right Cloud for Your Business

At Thrive, we understand that every business has unique performance, compliance, and budgetary requirements. Our experts help organizations assess their workloads, define cloud strategies, and deploy secure, scalable environments, whether public, private, or multi-cloud.

Through Thrive’s private cloud and partnerships with leading public cloud providers, we deliver:

• NextGen managed services for monitoring, patching, and optimization
• Cloud security and compliance management aligned to industry standards
• 24x7x365 support from our U.S.-based network operations centers
• Cost governance and performance visibility across all cloud environments

Whether you’re migrating from on-premises infrastructure or looking to modernize existing workloads, Thrive helps you achieve the right balance of performance, security, and agility in your cloud journey.

The choice between public and private cloud isn’t one-size-fits-all, it depends on your organization’s data sensitivity, compliance and budget requirements, and business goals. With Thrive as your strategic partner, you can design and manage a cloud environment that supports innovation, efficiency, and resilience, now and for the future. Contact Thrive today to learn more about how we can help your business migrate to the cloud that’s right for you.

Many organizations are rushing to adopt the latest AI technology trends, only to struggle with unclear outcomes, wasted resources, or poor adoption. The key to success lies in identifying the right AI use cases; those that deliver measurable business value, align with strategy, and can be supported by the right data.

Figure Out the Problem You’re Trying to Solve

One of the most common mistakes is starting with AI as the goal rather than the solution. Instead, organizations should ask themselves:

• What are our biggest challenges?
• Where do inefficiencies or risks exist today?
• Which business outcomes do we want to improve?

By starting with clearly defined business goals, you can align AI opportunities with measurable impact rather than chasing hype.

Prioritize Use Cases by Feasibility and Impact

Not every AI use case is equally achievable. Evaluate each opportunity based on:

• Business impact: Will this improve revenue, reduce costs, or minimize risks?
• Data readiness: Do you have clean, accessible, and sufficient data to train AI models?
• Technical feasibility: Is the process measurable and digital and trainable, or does it rely heavily on human judgment?
• Adoption potential: Will employees and customers embrace the solution?

An impact matrix is a helpful tool for visualizing and prioritizing potential projects.

Engage Stakeholders Across the Organization

AI adoption is more than an IT project; it requires input and buy-in from across the business. To successfully deploy an AI project, organizations will want to foster collaboration between:

• Executives to ensure alignment with strategic objectives
• Line-of-business leaders to identify pain points and opportunities
• End users to understand workflows and adoption challenges

This cross-functional approach ensures that AI use cases are relevant, actionable, and supported at every level.

Don’t Overlook Compliance and Risk Management

AI use cases that handle sensitive data (e.g., healthcare, financial services, or legal) must be evaluated through the lens of compliance and governance, such as:

• Data privacy regulations (GDPR)
• Industry-specific security requirements (HIPAA, PCI-DSS)
• Explainability and transparency to maintain trust

Keeping compliance top-of-mind early in the process prevents rework and builds confidence in AI systems.

Pilot, Measure, and Scale

Once high-potential AI use cases are identified for your organization:

• Start with a pilot project to test feasibility.
• Measure success with clear KPIs such as cost savings, reduced downtime, increased productivity or improved response times.
• Scale successful projects across departments or geographies.

This approach balances innovation with risk management, ensuring that AI investments pay off.

How Thrive Can Help

At Thrive, we help mid-market organizations support their AI-based business goals. Our NextGen managed AI, security services and advisory teams guide clients through the process of evaluating, prioritizing, and implementing AI use cases, ensuring these decisions are grounded in security, compliance, and business outcomes. With a strong information architecture and data governance foundation, we help ensure your organization’s AI initiatives are scalable, cost-effective, and future-ready. Contact Thrive today to learn more about identifying use cases for your AI initiatives.