Version 2027

Functional capabilities of the IT-Enterprise no-code/low-code platform.
Watch the IT-Enterprise Version 2027 video presentations on YouTube via the link.

IT-Enterprise’s Strategic Development Priorities

1. Digital transformation into a smart business. IT-Enterprise helps companies move from automating individual operations to comprehensive business management powered by data, transparent processes, and technology solutions.

2. A unified digital business ecosystem. IT-Enterprise, SmartTender, MASTER, and Signy bring together business process management, procurement, accounting, and electronic document management. This gives companies an integrated digital environment for day-to-day operations, development, and scaling.

3. AI agents embedded in business processes. Artificial intelligence takes over routine operations, helps teams work with data, and accelerates task execution. Teams can devote more time to analytics, management decisions, and strategic objectives.

4. Transparency and control over business operations. A unified digital architecture provides visibility into transactions, team activities, and business processes. This helps managers see the company as a whole and make decisions based on up-to-date data.

5. Flexibility and speed of change. IT-Enterprise technologies make it possible to adapt business processes to new requirements, market changes, and the company’s internal needs. The digital system evolves with the business, without requiring transformation to start from scratch each time.

6. Scaling without technology-related downtime. IT-Enterprise continues to develop its platform so companies can expand operations, launch new business lines, and improve processes without forced pauses to upgrade their digital infrastructure.

7. Measurable business impact instead of innovation for innovation’s sake. The focus is on the practical value of technology: less manual work, more efficient operations, greater management transparency, and faster decision-making. Innovation should deliver tangible competitive advantages.

8. Technological resilience for Ukrainian businesses. Digital solutions help companies maintain business continuity, use resources efficiently, and adapt to challenges. Business resilience is becoming an important factor in the country’s economic capacity.

A Fully Integrated Digital Assistant Powered by AI

1. The shift to AI-first. AI is becoming part of the ERP working environment, evolving from individual document-recognition features to autonomous assistants that perform tasks for finance professionals, accountants, and logistics teams.

2. AI agents embedded directly in ERP. Assistants operate in the context of a specific module, document, or business process. They do more than provide answers: they can also perform permitted actions in the system.

3. Intelligent document and data automation. AI recognizes documents, extracts key details, and creates records in the system. The MasterData agent maintains resource directories, detects duplicates, and helps resolve data errors.

4. AI agent hub and centralized AI. A unified platform brings agents together and simplifies their connection and management. Users can access the AI functions they need without having to deploy each solution separately.

5. Flexible AI architecture. Companies can use the AI platform as a service, connect their own models, or deploy open-source models within their own IT environment to work with sensitive data.

6. Control over AI usage. Centralized agent management provides visibility into how agents operate, usage statistics, and control over the cost of completed operations.

7. SuperChat / Enti — a single interface for interacting with AI. Users describe a task in text or by voice. The system determines which agents to involve and returns the result. This is another step toward natural interaction with ERP through a single digital interface.

8. Scaling the AI ecosystem. Moving from individual assistants to a centralized agent system makes it possible to scale automation across different business functions and establish a new model of human–AI collaboration.

Enti AI Agent

1. Voice control for business operations. Executives interact with ERP using natural voice commands, receive prompt answers, and manage tasks without having to search for information manually.

2. Real-time analytics. Enti provides up-to-date data on sales, orders, accounts receivable, and payments. This helps executives quickly assess the situation and set priorities.

3. Taking action directly in ERP. The agent does more than answer questions. At the user’s request, it can approve documents, add comments, create requests, and assign tasks to the teams responsible, within the permissions granted.

4. Control over financial obligations. Enti identifies overdue receivables, flags urgent payments, and helps executives manage financial priorities and ensure timely settlements.

5. Coordination of end-to-end business processes. The agent connects sales, contract management, warehouse inventory, procurement, and treasury. This makes it possible to identify dependencies between processes quickly and initiate the actions needed to fulfil orders.

6. A personalized executive assistant. Enti prepares meeting briefings, sends updates to a smartphone, and reminds users of scheduled events. Executives get key information and tasks in one interface, reducing the time spent on operational coordination.

7. From micromanagement to strategic leadership. Automating information gathering, task monitoring, and process coordination reduces executives’ operational workload and gives them more time to focus on decisions that directly affect business performance.

The IT-Enterprise Platform

1. Updated platform architecture. The technology core has been redesigned to handle high workloads, support more users, and accommodate complex enterprise processes.

2. Built-in cybersecurity. Secure SDLC, AI-assisted code review, compatibility with Web Application Firewalls, and annual independent white-box penetration tests help identify vulnerabilities.

3. Secure file uploads. The system checks a file’s actual format based on its contents rather than relying only on its extension. This helps block potentially dangerous files and reduce the risk of unauthorized access.

4. Flexible enterprise authentication. Support for Microsoft Entra ID enables multi-domain access and authentication for employees across different business units. SMS-code sign-in provides an additional access option for employees who do not have corporate accounts.

5. Performance optimization and lower infrastructure costs. Migration to .NET 10 and resource-usage optimization enable more efficient use of server infrastructure. The stated target is to reduce RAM consumption by the application server by up to 20%.

6. Automated performance diagnostics. Watchdog SQL captures the status of a slow query, its execution plan, and blocking processes at the moment the issue occurs. This reduces the time needed to identify the causes of slowdowns and helps IT teams restore normal system performance faster.

7. Flexible AI deployment. AI components can be run locally, on-premises, giving companies control over where sensitive data is stored and allowing it to remain within their own infrastructure.

8. Build AI agents independently. The built-in agent builder lets teams adapt agents to specific business processes without having to involve developers every time.

9. A modern technology stack and freedom to choose the environment. Technologies with long-term Microsoft support, combined with the option to deploy on Windows or Linux, provide infrastructure flexibility and a solid technological foundation for the platform’s continued development.

ForceBPM

1. End-to-end business process lifecycle management. ForceBPM covers three stages: modelling, execution, and technical support. AI is integrated into each stage, from creating diagrams to analysing incidents.

2. Multilevel modelling and accountability management. A hierarchical structure links the company’s process landscape to individual processes and specific actions. The RACI matrix records participants’ roles and responsibilities directly in tasks.

3. Extended low-code capabilities. Flexible business-object configuration and advanced access filters with AND/OR logic, SQL parameters, and Python make it possible to implement business logic with less developer involvement.

4. Automated BPMN diagram generation. AI generates diagrams from descriptions of existing processes and photographs of hand-drawn sketches, recognizing workflow logic and branching. In demonstration scenarios, diagram creation time is reduced from several hours to five minutes.

5. Automatic process documentation. AI generates descriptions of activities, performers, and transitions, and prepares Word documents containing diagrams and attributes. Updating documentation after a process change requires significantly less manual work.

6. Streamlined communication and search in Tasks. Flexible notification settings, centralized discussions and mentions, global search, and support for CAdES-internal signing simplify daily work and help eliminate unnecessary operations.

7. Interactive AI tutor. The AI assistant does more than explain system functionality: it guides users through the interface, highlights relevant elements, and helps them find tasks, participants, and approval history. In the demonstration, it answers a question in 10 seconds.

8. Automated document analysis. AI reviews contracts for legal risks, including clauses related to penalties and termination, highlights key provisions, and refers to specific sections of the document. This shortens initial review time and helps specialists focus on critical terms sooner.

9. AI-powered technical incident diagnostics. Analysis of the BPMN model, logs, stack traces, business logic, and SQL tracing helps identify the causes of errors and distinguish software defects from issues in reference data or configuration. In the demonstration case, diagnostics time is reduced from hours to five minutes.

10. Faster process implementation and support. The combination of low-code tools, automated diagram and documentation generation, and AI diagnostics reduces manual work throughout the lifecycle. The presentation states that process implementation can be accelerated threefold.

HR Ecosystem

1. Managing the entire employee lifecycle. The HR ecosystem covers recruitment, onboarding, training, performance assessment, personnel administration, time tracking, and payroll, including complex piece-rate payroll. This enables end-to-end management of HR processes in a single digital environment.

2. Corporate learning through an LMS. The learning management system brings together training courses, microlearning, and testing. It gives companies a tool for systematic skills development, standardized training, and faster onboarding.

3. AI tutor for onboarding and learning. The AI assistant works with the company’s internal policies, instructions, and procedures and answers employees’ questions directly in the system. 24/7 access to knowledge reduces the workload on managers and HR teams and helps employees learn work processes faster.

4. HR portal and employee self-service. The personal account provides access to HR and payroll information, remaining leave balances, payslips, and income certificates. This reduces routine enquiries to HR, speeds up request processing, and gives employees greater autonomy.

5. Digital HR document management. Applications and orders for leave or business trips can be prepared and signed with a qualified electronic signature, including via Diia.Signature. Moving to electronic documents reduces paper-based workflows and simplifies the approval of HR operations.

6. People management tools for executives. Access to the staffing table and information about direct reports enables managers to work with HR data more efficiently and make decisions based on current information.

7. Reduced HR operational workload. Automating HR operations, enabling employee self-service, and digitizing document workflows reduce manual work and accelerate request processing. The stated results are a 30% reduction in the time needed to process HR information and up to a 50% reduction in employee overwork.

8. More effective onboarding and talent retention. Combining the LMS, AI tutor, and HR portal helps transfer internal knowledge faster, make essential information readily available, and reduce administrative barriers. This gives HR more room to focus on skills development, productivity, and employee retention.

IT-Enterprise WMS

1. Decentralized warehouse network management. Centralized control of dozens of warehouses in one system, with synchronized inventory balances and goods movements between locations.

2. End-to-end control of warehouse operations. Automation of the full cycle, from expected deliveries and incoming inspection to quarantine, bin-location storage, picking, order consolidation, and dispatch. Every operation and movement is traceable.

3. Digital warehouse twin. A 3D view of warehouse zones, storage bins, occupancy levels, and current tasks. This enables real-time monitoring of warehouse space utilization and staff workload.

4. AI-powered warehouse process optimization. Forecasting workloads, optimizing routes for warehouse equipment, and recommending product placement. AI agents help improve operational productivity.

5. Mobile automation for warehouse staff. Employees carry out warehouse tasks using data-collection terminals and tablets, scan barcodes, verify storage bins, and check quantities. This reduces manual data entry and operational errors.

6. A unified collaboration system for warehouse and commercial teams. Synchronization of warehouse staff, logistics teams, and sales managers, with transparent order statuses and access to up-to-date information.

7. Productivity analytics and KPI monitoring. Monitoring employee and shift performance, operation times, warehouse throughput, and resource utilization. These data support day-to-day management and help identify bottlenecks.

8. Faster warehouse processing and higher throughput. Order picking time can be reduced to five minutes, while warehouse throughput can increase threefold, according to the figures presented.

9. Integration of warehouse operations with financial management. Creating a unified digital environment in which data on goods movements, production, and sales underpin management P&L, consolidated reporting, and automated SAF-T UA tax reporting.

Finance

1. Management accounting and profitability control. Flexible configuration of the P&L structure by profit centre, business line, and sales channel. Plan-versus-actual analysis supports the assessment of business profitability.

2. AI-powered financial performance analytics. Automated identification of variances, anomalies, and factors affecting financial indicators. The system generates explanations and recommendations to support management decisions.

3. Cash flow management and payment calendar. Automated payment schedules based on contractual obligations, payment planning, and cash-gap forecasting. Payment priorities can be managed flexibly.

4. Indirect-method cash flow analysis. Identifying the factors behind discrepancies between profit and actual cash movements. The system highlights the impact of inventory, accounts receivable, and other transactions on business liquidity.

5. Liquidity yield and allocation management. Monitoring how funds are allocated between current operating needs, deposits, and other investment instruments. This helps assess how efficiently available financial resources are being used.

6. Financial statement consolidation. Combining data from legal entities into unified corporate reports, with support for IFRS and management reporting standards. Intercompany transactions and elimination entries are processed automatically.

7. Automated statutory SAF-T UA reporting. Generating tax-reporting files with automated data checks and validation in collaboration with CaseWare. Errors can be identified before reports are submitted to the tax authorities.

8. A unified finance environment for management decisions. Integrating accounting, contracts, payments, and financial reporting data. This replaces fragmented indicators with transparent control over profitability, liquidity, and financial risks.

MilTech and Strategic Manufacturing

1. Controlled production scaling. IT-Enterprise solutions are already used by more than 50 defence companies in Ukraine. The stated performance indicators are: 95% of orders delivered on time, an 85% reduction in manual work, a 50% reduction in time to market, and a potential 30% increase in the productivity of existing capacity.

2. End-to-end production lifecycle management. Integrating CAD, PLM/MDM, APS, and MES connects engineering documentation, bills of materials, planning, and production execution. Employees receive tasks on mobile devices, while data on materials, manufacturing, and defects is sent to the system in real time.

3. Warehouse logistics automation. WMS supports bin-location storage, material identification, and movement tracking using barcodes, QR codes, and RFID. This speeds up picking and dispatch, improves inventory accuracy, and helps reduce excess stock. The stated potential inventory reduction is up to 20%.

4. Equipment management and predictive maintenance. SmartEAM provides access to equipment records, maintenance history, and technical documentation via QR codes and mobile devices. The Anna Maly AI agent analyses telemetry, detects anomalies, and helps predict failure risks. In the customer examples presented, unplanned downtime and maintenance costs are reduced by around 30%.

5. AI agents for operational automation. An ecosystem of specialized agents automates work with technical documentation, procurement, finance, maintenance, and documents. AI extracts data from drawings, standardizes item nomenclature, helps create manufacturing process plans, and processes source documents. The stated level of routine-operation automation is up to 85%.

6. Intelligent document processing. DocAI recognizes invoices, contracts, delivery notes, and other documents, reducing manual data entry. In the Come Back Alive Foundation project, the system processes around 70,000 documents per month with accuracy above 99.5%. This increases document-processing throughput and reduces employee workload.

7. Financial transparency and management reporting. Automated accounting provides data for analysing P&L, cash flow, and business-line performance. Traceability from management indicators to source documents supports financial control and investment readiness. One example is IFRS accounting at Ferrexpo.

8. Data-driven procurement planning. The system matches production plans, material requirements, and warehouse balances to help determine what to buy, when, and in what quantities. This reduces reliance on manual Excel-based planning and enables more efficient use of working capital. The presentation states a potential saving of up to 70%; to interpret this figure correctly, the cost base it applies to should be clarified.

9. Actual production cost control. Real-time visibility into material, labour, and logistics costs makes it possible to compare actual and planned production costs while an order is still in progress. The stated target is to keep deviations within 3%. Even a 2% reduction in raw material costs can deliver a significant financial impact in large-scale manufacturing.

10. From a system of record to a business growth tool. Combining production planning, warehouse logistics, equipment management, AI, and financial analytics creates a unified digital environment. It helps reduce operational losses, increase productivity, and manage manufacturing economics using up-to-date data.

Food Industry

1. End-to-end management of the agri-food value chain. A unified digital ecosystem covers crop production, grain storage and handling, livestock farming, processing, logistics, and sales. Integrating production and financial data makes it possible to control costs and assess how operational changes affect product cost.

2. Full product traceability. The system tracks raw materials and finished products by batch, from the supplier through storage to dispatch. Tracking expiry dates and component origins helps identify affected batches more quickly and reduce product-quality risks.

3. Recipe management and material balances. Automated control of recipes, consumption standards, waste, and by-products improves the accuracy of production accounting. Support for multiple units of measure makes it possible to compare quantities of raw materials, semi-finished goods, and finished products consistently.

4. Integration with production equipment and IIoT. The platform collects real-time data on equipment productivity, energy consumption, and process parameters. Automated monitoring helps detect deviations from established operating conditions and respond promptly.

5. Cost control and cost allocation. Integrating production, warehouse, and financial data enables more accurate cost allocation and better visibility into manufacturing economics. According to the presentation, cost allocation takes six times less time, while reports for supplier payments can be prepared 80% faster.

6. Operational analytics and management reporting. Centralized data lets managers monitor production indicators, costs, and resource utilization without lengthy manual data consolidation. This speeds up management decisions and improves operational transparency.

7. Higher productivity from existing capacity. Combining process monitoring, traceability, resource accounting, and operational analytics helps identify losses and use production capacity more efficiently. The stated customer result is a 30% increase in production volume without expanding existing infrastructure.

8. Quality control and lower operational risk. Batch accounting, process-parameter monitoring, and traceability provide a unified information base for quality management. This helps identify the causes of deviations faster, isolate problems, and reduce the risk of losses involving raw materials and finished products.

Electronic Archive

1. End-to-end digital document management. Automating the document lifecycle, from creation and verification to file compilation, archival storage, and transfer to the State Archives.

2. Automated archival file compilation. Organizing documents according to departmental file plans, automatically compiling files, and checking their completeness against established requirements.

3. Control over retention periods and storage rules. Tracking retention periods, checking the number of pages in each file, and ensuring compliance with archival requirements.

4. Automated preparation of documents for the State Archives. Generating inventories, acts, and supporting data in the approved XML format for archival transfer, without re-entering information manually.

5. Electronic signing and legal validity. Using a qualified electronic signature (QES) for the relevant process steps to authenticate documents and ensure that procedures remain traceable.

6. Centralized document storage and classification. Bringing archival materials together in one system, simplifying document search and access, and reducing dependence on paper records.

7. Lower costs for archival administration. Reducing manual work involved in compiling files, carrying out checks, and transferring documents to the State Archives, while improving control over archival processes.

MASTER Ecosystem

1. A unified digital business management ecosystem. Bringing accounting and tax reporting, payroll and HR processes, document management, CRM, procurement, budgeting, and reporting together in one digital environment. Centralized data reduces duplication.

2. Intelligent processing of source documents (DocAI). Automatic recognition of invoices, acts, and other documents; document-type identification; data extraction; and creation of accounting records. The system also detects potential errors and duplicates. According to the figures provided, around 85% of documents are recognized correctly, and processing time is reduced by up to 90%.

3. Built-in MASTER + Signy electronic document management. Documents can be received, signed, and stored directly in MASTER. Integration with other electronic document management services, including Vchasno and M.E.Doc, is available through a unified interface.

4. Extended two-way API. Automated exchange of documents, accounting entries, and HR data between MASTER and other corporate systems. This integrates the accounting environment into the company’s existing IT architecture.

5. Automated SAF-T UA reporting checks. Generating the reporting file, automatically validating data, and running analytical tests before submission to the tax authorities. Potential errors can be detected earlier and reporting data quality improved.

6. MASTER:Trade Online cloud solution. Automating accounting and sales management for individual stores and retail chains through a SaaS model. The system can be accessed without deploying in-house server infrastructure.

7. Centralized e-commerce management. Managing product ranges and orders from different marketplaces within the ERP system. Online sales are integrated with inventory accounting and the company’s business processes.

8. Support for new product-accounting requirements. Functionality for working with electronic excise stamps (eExcise) and tracking goods by unique IMEI codes. The system controls the movement of these product categories within the accounting environment.

9. Industry-specific automation for insurance businesses. End-to-end management of insurance processes, including application checks, tariff calculations, insurance reserve formation, and accounts receivable monitoring. The system synchronizes the work of underwriters, legal teams, risk managers, and finance professionals.

10. Evolving MASTER to meet business needs. Expanding the ecosystem’s functionality, integrations, and industry-specific solutions, with a focus on reducing manual operations, improving data consistency, and making company management more efficient.

SmartTender

1. Procurement market analytics. Structuring data on products, categories, prices, and contracts to assess market composition, a company’s market share, the competitive landscape, and potential growth opportunities.

2. Identifying new procurement opportunities. Analysing missed tenders, regional demand, and competitive positioning. This helps suppliers identify promising procurement opportunities and improve their bidding strategies.

3. Analytics to optimize sales and pricing. Using procurement data to assess competitive prices, identify new customers, and improve commercial decision-making. One practical example is Sheriff, which found that it had participated in only 30% of the tenders matching its business profile.

4. Prozorro data for market and industry analytics. Using procurement information to track pricing trends, changes in competition, and buyer behaviour. For example, the industry publication Naftorynok uses these data to prepare analytical content on the petroleum products market.

5. Developing AI tools for procurement. Creating new AI-powered tools in response to the needs of buyers and suppliers. This expands the platform’s technological capabilities and automates work with procurement data.

6. Launching new procedures on Prozorro. Providing technological support for procurement mechanisms that were not previously available on the platform. SmartTender enabled the first Brave1 grant competition under the UNITE–Brave NATO programme and launched a new procedure for selecting managers of ARMA-seized assets.

7. Digitizing specialized procurement processes. Developing functionality for auction organizers and participants, including the publication of ARMA auctions and submission of bids. One example is the first auction to select a manager for the IDS Ukraine group.

8. Strengthening SmartTender’s technological leadership. Developing analytics, AI solutions, and specialized digital services that address specific market participants’ needs and provide technological support for new procurement procedures.