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Cloud Document Management Benefits Everybody knows the benefits that a digital document management system offers compared to traditional paper storage in file cabinets. Going digital lowers office costs. Suddenly, your documents want less office space, furniture, and paper usage. And your workers start to spend less time accessing documents. Physical handling from employee to employee no longer makes sense for this reason. Since it’s widely known, let's stay focused on the advantages of moving such important assets as documents to the cloud. Security If the U.S. Department of Defense selected the cloud, specifically Amazon, there was a reason. The main one is to offload security from the internal IT teams in the face of the growing number and complexity of cyber threats. By default, up-to-date security means automatic control that assigns and revokes appropriate document access, encryption to protect stored and shared data, anti-disaster digital storage, backup, recovery and restore, and, of course, software updates. It's worth focusing on how cloud content is backed up. It does this after each edit and in multiple data centers. Business continuity is supported, and data and services aren’t down regardless of any reason. Remote access At first sight, remote access does not appear to be something completely new. Maybe your workers already connect to a corporate network using a VPN. The key here is the VPN. Your IT team has to set this up for each new team member and help with management and solving issues (there may be a lot of them). The major drawback of VPN is dramatically slowing down and lengthening an employee's journey. Traffic is slowed by taking longer routes. Transferring large files comes with significant long loading times. Encrypting/decrypting further slows down the connection. Direct access to cloud resources eliminates the extra twists that VPNs introduce. Cloud-based document management systems are accessible on any device, regardless of the user's location. They just need an internet connection to log in through a web browser. Budget Optimization No capital expenditures. Monthly subscription costs for cloud services are operational expenses. IT staff is not necessary to manage servers, disk space, or to buy new computers. The number of servers, processor speed, and the amount of storage automatically increase with the growth of files and traffic. For heavily regulated finance or healthcare industries, compliant cloud solutions are always at hand. Extensive tech resources at your side are no longer required. Features of a Document Management System Some features are already set up in the described system. Others can be customized on request, which is fairly easy to do since the system is deployed on AWS. AWS provides many options for integrating ready-made solutions, which makes customization simpler. Convert Scanned Documents to Texts and Process them With AI Optical Character Recognition technology (OCR), implemented in modern document management systems, automatically, quickly, and accurately extracts large amounts of text from scanned documents, images, or PDFs. After such preprocessing, users can quickly find and edit information from scanned documents. OCR is not a new thing in document management. It has established itself as a tool to process banking documents (checks, loan applications, and account statements), automate extraction of information from invoices (vendor details, amounts, and dates), and retail documents (labels, receipts), digitize healthcare documents (patient records, prescriptions), and assist in the analysis of legal documents (contracts and case files). But AI makes a difference. It not just improves text recognition accuracy due to machine learning but is also able to deal with it like a human acts in a business process (know what to do with it) thanks to natural language processing technology (NLP). It may read content and compare it with other documents to check accuracy (data validation) and forward it to the head of the department for further actions (decision-making). For example, it’s reported that AI-based invoice processing times can be reduced by 90 percent, equating to a 400 percent increase in employee productivity, making turnaround time for invoices from days to minutes. Each industry has specific forms to process, and this can also be automated with AI-enabled recognition. We talk about insurance claims forms, logistics driver logs or delivery receipts, banking credit card applications or loan and mortgage forms. When needed to verify addresses at scale, AI can analyze driving licenses, passports, bank statements, and utility bills in bulk. The modern low-code/no-code document management solution can be easily integrated with AI-based OCR software with pre-trained, ready-to-go models or custom extraction models based on specific business requirements. Document Classification ML, computer vision, and NLP are technologies to categorize documents. They automatically add predefined categories, or tags to documents. Computer vision is the fastest method. It can understand the type of document without reading its text just by seeing the visual structure during the scanning phase. As to text-based classification, documents can be segmented based on the complete document, specific paragraphs, particular sentences, or even phrases. In general, business case influences how to segregate documents. Document classes might be user-defined, and document sorting is possible by type, level of confidentiality, vendor, or project containing a set of documents, and more. AI can understand various types of documents in each industry: legal documents, notarial deeds, and contracts for law firms; medical records, patient files, and clinical research documents for healthcare organizations; financial statements, loan applications, or insurance claims for banks, insurance companies, debt collection agencies, and other financial institutions. AI-based document classification can work with structured documents (tax return forms and mortgage applications), semi-structured documents (invoices), and unstructured documents (contracts). Machine learning models are able to understand whether the uploaded document is complete and flag missing or incomplete inputs and pages, and mark any documents with errors. It identifies fraudulent documents through anomalies, helping to reduce document fraud. After the classification process is finished, documents can be automatically routed to the appropriate department and respective team members. Document Summarization AI creates text summaries of lengthy documents, scanned files, and images for those who are short on time. It can even transcribe video and audio files so one can search within that content. It’s not about shrinking text but rather extracting the main points. For example, it can highlight key points like pricing and terms from a lengthy contract. AI rephrases complex sentences and technical jargon using plain language. It can explain specific clauses so simply that a reader can understand the legal implications much faster and more precisely. Interactive Q&A To Replace Traditional Search Traditional document repositories are text-searchable by keywords. But this may overwhelm. You have to comb through too many search results to find something valuable. Disappointment is usual. Can't you often find relevant records even after spending a lot of time? AI-powered search makes a difference. No more manual searching through each document to quickly find specific information within some of them. Now, searching is like an interview. The chat understands the context, asks you questions, and narrows down the results. It works best with complex requests like "What is the total amount spent with Company X last month?" or "List documents from 2023 that mention topic X." Responses are accurate because they are based on your document's content. Integration Integrated document management systems allow employees to view, edit, and save documents directly in their daily-use software. Users from different industries like retail, banking, finance, insurance, or manufacturing can work with their documents without switching applications.  For example, when a bank employee is processing a client's account in a core banking system, they can also access account opening forms, loan, or mortgage agreements stored externally. They can edit such documents right there, and their line-of-business app will automatically save the modified document back to the document management tool. A document management system, integrated with other vital systems in your organization, helps your employees avoid unnecessary challenges. Document status visibility A document management system provides an interface that helps to understand the status of each document in the workflow, like whether it’s in draft, in progress, awaiting review, under review, feedback provided, revised, awaiting approval, approved, rejected, finalized, published, archived, completed, or expired. Document versioning Since documents can be shared with several teams, departments, or even external stakeholders, the system includes a tracking feature. The log may save all changes made to a document, including who made them and when.  Nested Folders  The nesting (organization of items within a hierarchy) helps us establish relations between things. Using nesting, end-users can define the order they like for grouping related documents.  Document Security The owner can analyze who accessed each document, what changes were made, who uploaded or downloaded it, and what comments were left. They can also restore a document to its earlier versions if something goes wrong. Admins may apply access rights (view, edit, or comment) to different types of folders, subfolders, or individual documents, which is a best practice for security. An enterprise-level document management system provides powerful tools for sharing and collaborating on files within your company. Multiple team members can work on the same document simultaneously, making changes and leaving comments for each other. A good document management system lets you create rules for how your employees can share documents. Automated alerts and actions on certain conditions This feature allows a document management system to keep an eye on your documents and notifies you when something needs your attention or when a specific action needs to be taken.  For example, if a contract is about to expire, the system can send you a reminder email so you don't forget to renew it. If a document containing sensitive data is accessed by an unauthorized user, the system can immediately alert the security team.  The system can also be set up to automatically perform certain actions based on predefined conditions or schedules. For instance, it can automatically archive old documents or delete after a certain retention period as mandated by legal regulations or company policies like freeing up storage space.  Metadata extraction Metadata is extra information about a document that helps describe what's inside the document without you having to open it and read through the whole thing.  It may be the date when the document was added and the user identity of who uploaded or edited the document.  For example, claim documents with digital photographs may contain the date the photograph was taken and even geolocation. This feature makes it simple for the user to access what they seek and allows documents to be found easily.  Metadata is automatically extracted and stored for each document. The system may also offer the user to manually add metadata. 

Unexpected high costs post-migration challenge To mitigate the risk of unexpected cost increases after moving to the cloud, our team employs the following strategies: ✅ Smart budget planning. To manage and predict these costs, we use tools like the Azure Pricing Calculator and AWS Pricing Calculator. We meticulously consider all important cost factors such as resource types, size, features, services, scalability, backup and recovery options. This way, you can anticipate and limit cloud costs. ✅ Cloud-native cost control methods. We professionally configure the auto de-provisioning feature, that turns off resources when they are no longer needed, and elastic pools, the set of resources like CPU, memory, and storage that automatically adjust resources based on actual demand. These methods help prevent overpaying. While cloud providers offer these tools, effective cost management requires expertise of specialized third-party or in-house professionals. They can help you select resources, integrate with existing systems, and enhance them regularly to optimize cost control. Challenge of uncontrolled cloud spending due to poor access management In some on-premises scenarios, especially in smaller organizations with fewer than 500 employees, in-house developers often have sysadmin-level privileges. This means they have almost unlimited control over the system, including the ability to delete databases. The financial implications of this are generally limited to the existing infrastructure in on-premises setups. In cloud computing these control issues present more significant challenges, where costs directly correlate with usage. Developers with extensive cloud privileges can unintentionally activate expensive features, leading to uncontrolled spending. ✅ Strict role-based access. This ensures only authorized personnel have specific data access, reducing the risk of unplanned expenses. Using systems to track who accesses what data and when provides oversight and helps in maintaining control over cloud spending and data security. See the full guide on Cloud Security and Compliance for more insights. Sudden costs challenge by making changes in production Organizations accustomed to implementing live changes in on-premises production environments may encounter immediate cost implications when they move to the cloud without modifying their practice. Consider an IT engineer adjusting auto-scaling settings to enhance system responsiveness during peak traffic. Incorrect thresholds can cause the cloud system to deploy more servers than necessary, significantly increasing the monthly bill and straining the budget. Prioritizing data migration testing before deploying the system is key to identifying and addressing cost-related issues early. This testing phase ensures cost-effective cloud modifications. In such cases, we focus on keeping the service available by temporarily increasing resources, even at higher costs. Once the demand returns to normal, it is important to quickly optimize the settings for cost-efficiency. The broad cloud access often granted to developers, particularly those with sysadmin privileges, poses additional risks. Unintended access can trigger expensive cloud features, causing unforeseen costs and uncontrolled spending. Furthermore, allowing the IT department unrestricted ability to make live changes in the cloud can invite operational challenges, including service disruptions from unresolved bugs. ✅ A robust change management process is crucial for cloud migration strategy, requiring review and approval of changes, particularly in production. This process includes thorough impact assessments, with a focus on potential cost implications. Changes should first be tested in development or staging environments. For instance, simulating peak traffic in staging can effectively evaluate auto-scaling responses, identifying any issues before they affect the production environment. Increased cost challenge due to pursuing a swift single-phase migration Many inexperienced IT managers rush their cloud migration, often transferring the entire on-premises setup in one move. This overlooks key differences in cloud architecture, impacting storage and computing needs. Additionally, such a fast migration approach strains the IT team, and the lack of historical data is causing further challenges. This can cause either paying for unnecessary cloud resources (over-provisioning) or not having enough resources to handle the workload (under-provisioning). Both scenarios can lead to avoidable expenses and operational issues. ✅ Progress in application modernization can be achieved with less funding. We recommend incremental migration for complex on-premises applications. This method involves breaking migration projects into smaller chunks that require fewer resources. At the technology stack level, each iteration adds modernized code, gradually reducing the percentage of legacy code until the legacy system is completely modernized. Throughout this process, the system remains fully operational. Cloud migration experts also use time-tested approaches, such as API-first modernization approach, migrating customizations separately from the core app to microservices, or modernizing critical user journeys first – all minimizing risks and costs. Why Belitsoft For your cloud migration project, we provide skilled and experienced cloud migration experts. They are trained to analyze project requirements, assess alternatives, and make the best choices. Here are some of the core responsibilities of our cloud migration experts that are pivotal to the project's success: assess current data estate, infrastructure, and application(s) to be migrated and, in response, develop a migration plan compare pilot requirements to technical implementation options and recommend a migration strategy to the team deploy the production application with adjustments from earlier migration stages conduct a post-migration analysis with an eye on future enhancements, such as recoverability at a cheaper cost Belitsoft provides external talent to navigate complex technical and management challenges, ensuring a smooth and successful migration of your enterprise applications. Contact us for more details.

The Challenge of Accurately Assessing Cloud Workload If not planned well, moving from on-premises to cloud systems can use up a year's budget much faster than expected. The difficulty arises from accurately assessing the performance requirements of workloads in the new cloud environment. There are also differences between on-premises and cloud provisioning, leading to poor resource allocation decisions if not timely addressed. To avoid these issues, our cloud experts apply a step-by-step pipeline to ensure that you don't overspend by overprovisioning resources in the cloud nor your users experience a lack of performance due to underprovisioning resources. Here is how we do it. Collecting on-premises performance data as a benchmark We start with collecting information - metrics, logs, and traces - from your on-premises infrastructure to create a comprehensive performance profile. This step is fundamental, as it establishes a baseline against which we can measure the success of the migration. A customizable dashboard with metrics, logs, and traces Logs provide detailed information about system activities and events. For example, we see that the database makes 10 user data requests for a single page load. Traces track the execution of specific processes through the entire system, like an order processing trace in an e-commerce system. It tracks the entire order processing workflow, recording each step, such as order creation, payment processing, and shipment. Traces help identify bottlenecks or failures in the process to prevent them further. Metrics capture system functioning at a specific point in time. Page load time, throughput, errors, and performance are measured by Work Metrics. Resource Metrics, like CPU utilization, measure a system's current state, looking at factors like utilization. Setting precise benchmarks for cloud environment sizing Data migration testing is essential before transitioning to the cloud as it validates expected cloud performance. We can refine benchmarks to reflect accurately cloud capabilities and address limitations by scrutinizing data and applications. This process helps in avoiding overprovisioning resources in the cloud, ensuring cost-efficiency, and maintaining performance without compromising on user experience. Rather than duplicating your on-premises setup in the cloud, we establish clear benchmarks based on your existing metrics, traces, and logs. These benchmarks are instrumental in determining the expected values and usage patterns for your system in the cloud. For example, we may set a CPU utilization benchmark around 80% for typical operations, ensuring efficiency without overwhelming resources. We also strive for high accuracy, aiming to keep the error rates below 1% for over 99% of all transactions. These benchmarks serve as reference points for ongoing performance monitoring and future adjustments, so we can guarantee that your cloud system operates within optimal parameters. Setting actionable and relevant alerts for timely responses Once we establish precise benchmarks using your on-premises data, our focus shifts to optimizing performance and cost management in the cloud. Your team receives alerts through a robust system to maintain software health and respond to deviations from benchmarks. There are two types in our alert system that can be used and combined: We apply fixed alerts to prevent exceeding a defined absolute value. For example, we are aware that the search index size is 2GB. With cloud changes, it may occasionally increase to 4GB. However, if it exceeds 5GB, we set an alert because it surpasses our defined limit. This type of alert is crucial for detecting and responding to critical issues that require immediate attention. We also apply adaptive alerts, that are more dynamic and tailored to monitor and respond to abnormal behavior in metrics over time. For instance, in cloud migration, adaptive cost alerts help manage your expenses by analyzing factors like storage, bandwidth, and computing resources. Let's say your usual monthly cloud budget is $2,500, but you're gradually adding more resources like virtual machines or database storage. These alerts automatically adjust your spending limit accordingly, up to $3,000 over a year, without notifying you. However, if there's an unexpected surge, such as a sudden increase in database storage usage, your team will be promptly alerted, just like with fixed alerts. This approach allows for flexible and intelligent cost management, adapting to your evolving cloud resource needs. By combining both alert types in your monitoring system, you're equipped to resolve issues promptly and minimize non-actionable alerts. Disparate Data Collection as a Barrier to Performance and Cost Management The challenge of using multiple monitoring tools lies in their separate data outputs. This complicates a unified analysis of performance issues or cost overruns, and hinders obtaining a single view of the impact or root cause of incidents or overspending, ultimately prolonging their duration. To address this, we integrate various tools into a singular analytics platform. This platform merges technical metrics from different monitoring tools through APIs and presents them in a customizable dashboard for relevant stakeholders. We help transition from reactive to proactive monitoring, preventing potential incidents from escalating. Streamlining monitoring with AWS/Azure tools integration For enhanced continuous monitoring after migrating to the cloud, our cloud specialists can integrate monitoring tools provided by AWS and Azure into your single custom monitoring system for convenient and unified access to all your data through a single platform. Integrating Microsoft's Azure Monitor provides a dashboard with essential information and detailed insights for effective cloud environment health management With all data in one place, managing cloud performance and expenses becomes more efficient, helping you avoid overprovisioning and unexpected costs. Our development team can create unified custom analytics to help you avoid poor performance and overspending in the cloud. Talk about your specific case with the cloud expert.