Rpa-En — TechCom

Preparing enterprise operations for recursive AI self-improvement

Wed, 17 Jun 2026 06:09:02 +0300

Artificial intelligence is evolving into an autonomous agent capable of learning and improving with minimal human intervention. While companies are actively integrating AI solutions into their operations today, the next stage of transformation is already on the horizon. The concept of Recursive Self-Improvement (RSI), being researched by an R&D company specializing in AI/ML, posits that AI systems will be able to enhance their own algorithms and architecture. This ushers in a new era of automation but simultaneously introduces new risks. Let's examine how to prepare businesses for this transformation, focusing on data readiness and proactive risk management.

Evaluating RPA integration with ERP: digital bridge or temporary fix?

Mon, 15 Jun 2026 15:39:49 +0300

Following an ERP deployment, manual tasks rarely vanish entirely. Large organizations often face persistent integration gaps involving legacy software, Excel spreadsheets, paper-based workflows, and email-driven approvals. RPA offers a rapid solution to these gaps by mimicking user actions to transfer data without requiring extensive integration projects. However, for CIOs and COOs, the critical question remains: is the robot addressing a temporary technical deficit, or is it legitimizing an ERP workaround that should have been eliminated during the initial implementation?

Automation success: evaluating risk and data for AI and RPA

Mon, 01 Jun 2026 16:45:34 +0300

Robotic Process Automation (RPA) has long been a standard for efficiency in many organizations. It enables the automation of routine, repetitive tasks, freeing up specialist resources for more complex assignments. However, this year has already seen a qualitative leap in RPA development in practice, driven by deep integration with artificial intelligence. This synergy transforms automation from a tool for simple tasks into a platform for optimizing complex, cognitive processes.

Maintaining continuity during phased legacy ERP system migrations

Fri, 29 May 2026 23:18:39 +0300

Legacy ERP systems in the public sector have become bottlenecks for development and adaptation to modern requirements. Any change, integration with new government services, or functional update takes 3–6 months and often requires downtime. This leads to departments creating their own "shadow" IT solutions to bypass limitations, and the launch of new electronic services or adaptation to legislative changes occurs significantly slower than among competitors.

As an integration solutions architect with 15 years of experience, I believe that instead of trying to revive a monolith or replace it with a single "big bang," the path to successful digital transformation lies in phased decomposition of legacy ERP. This means extracting individual functions into microservices with API access, allowing for system modernization without business interruption and with minimal risks.

Business low-code: platform capabilities for 2026

Fri, 22 May 2026 20:20:23 +0300

In today's dynamic business environment, the speed of innovation is a key competitive advantage. For CIOs and IT Directors, this means constantly seeking solutions that allow for efficient business process automation without turning every project into a lengthy and resource-intensive IT marathon. One such powerful approach is the synergy of Artificial Intelligence (AI) and low-code platforms.

What is AI low-code and Why is it Important for Business?

The AI low-code approach combines the capabilities of low-code platforms for rapid business process modeling with the functionality of artificial intelligence, which adds intelligent features: document recognition, classification, response generation, intelligent search, and decision support. As noted in industry articles, this allows companies to launch workflows faster, reducing reliance on traditional development and eliminating manual execution of repetitive steps.

Securing APIs against emerging threats with AI technology

Wed, 13 May 2026 06:08:01 +0300

By 2026, Gartner predicts that 40% of web application attacks will utilize APIs as their primary vector, underscoring the critical importance of strengthening application programming interface security within system integration contexts. The increasing complexity of enterprise landscapes, encompassing hybrid and multi-cloud environments, expands the attack surface for potential adversaries. Traditional defense methods are no longer sufficient to effectively counter dynamic and adaptive threats, demanding the integration of artificial intelligence-based solutions.

How API-centric integration improves enterprise time-to-market

Thu, 30 Apr 2026 06:05:48 +0300

According to Gartner, by 2025, over 65% of global companies will use APIs as the primary integration mechanism for their critical business applications. This trend is driven by the need to accelerate time-to-market, enhance operational efficiency, and ensure flexibility amidst rapid market changes. API-driven system integration allows businesses to quickly adapt their IT landscapes by integrating new services and solutions without significant rework of existing systems.

Role of APIs in modern IT landscapes

APIs (Application Programming Interfaces) act as bridges between different software components, enabling them to interact and exchange data. In the context of system integration, APIs provide a standardized and secure way to connect enterprise applications such as ERP, CRM, ECM, and specialized industry systems. This facilitates the creation of modular, flexible, and scalable architectures that easily adapt to new business requirements.

MDM and data integration strategies for large enterprises

Fri, 17 Apr 2026 06:08:19 +0300

In a large industrial enterprise with a long history, there are multiple ERP systems, separate CRM solutions for different departments, legacy databases with information on equipment and suppliers, and new cloud services for logistics management. Each department works with its own data, which is often duplicated, contradictory, or simply missing in other systems. The marketing department launches a campaign based on one set of customer data, the sales department uses another, and the finance department cannot even compile a unified profit report because information about the same products has different identifiers in different systems. This leads to operational delays, incorrect decisions, lost profits, and reduced competitiveness. This is where system integration and Master Data Management (MDM) become not just desirable, but critically important tools.

Managing digital transformation and BPM for better results

Thu, 16 Apr 2026 18:50:10 +0300

BPM (Business Process Management) is often seen as simple task automation. But there is a fundamental difference between “digitizing a form” and truly managing processes.

In the first case, a company just performs the same mistakes faster. In the second — it changes the way it operates.

From automation to an operational system

Modern BPM is not about scripts or isolated forms. It is a system where processes are defined as executable models, connected with each other and integrated with core business systems.

Corporate ECM and Document Management Outlook for 2026

Mon, 13 Apr 2026 23:27:51 +0300

Modern business is rapidly shifting from chaotic file exchange to systematic digital transformation. ECM (Enterprise Content Management) is becoming not just a technology, but the foundation of information management in organizations — from workflow automation to building full-fledged digital workplaces. In 2026, the focus is shifting toward AI support, low-code platforms, security, integrations, and flexible solutions.

1) AI becomes part of every document

Artificial intelligence turns documents from “static files” into data sources. Systems can already:

automatically classify and recognize documents;
extract metadata, counterparty data, and key contract terms;
generate summaries, detect risks and anomalies;
answer questions about document content in chat mode.

2) Low-code and no-code — the new standard

Companies no longer want to wait months for custom development. Low-code tools allow business users to:

create approval workflows,
modify document routing,
launch integrations with other systems without extensive IT resources.

3) Integration and API ecosystems

ECM is becoming part of the digital ecosystem: CRM, ERP, electronic signatures, banks, registries, and cloud services. The API-driven approach makes document management part of end-to-end business processes, not just a separate “folder”.

4) Hybrid and cloud model

Organizations combine on-premise and cloud solutions to balance control, security, and scalability. This is especially important for the public sector, finance, and critical infrastructure.

5) Security and audit “by default”

Encryption, access roles, version control, event logs, and full auditability are becoming baseline requirements rather than “optional extras”. Regulatory compliance is becoming a built-in part of the platform.

How enterprise solution vendors adapt their products to modern conditions

The companies within the group have been working for many years in ECM, process automation, and digital transformation. A key contribution in this area is made by a specialized provider of document management systems and digital transformation solutions.

Among the key products and approaches:

Corporate document management based on a specialized platform — a full cycle of working with documents: from creation and approval to archiving, control, and audit. Business process management using a low-code platform — for fast creation and modification of processes without deep programming. Electronic archiving and content management through a dedicated repository — centralized storage, fast search, secure access. AI-oriented tools in document management systems — document processing automation and intelligent content classification. A development and integration platform for building custom systems, complex integrations, and scalable services. In practical implementations, the provider achieves key results: significantly reduced document approval times, lower paper-related costs, increased process transparency, and rapid scalability of solutions to meet new needs. Experience from projects in the financial sector, government, agriculture, energy, and retail shows that ECM combined with BPM and AI becomes a strategic transformation tool rather than just an auxiliary system.

What’s next?

In 2026, ECM is becoming an “intelligent layer” of corporate architecture:

documents become sources of analytics;
AI supports decision-making;
low-code accelerates change;
security and audit are built in “out of the box”.

Organizations that are already investing in ECM gain not just a digital archive, but a managed, transparent, and scalable business process — a foundation for further digital transformation.

System Integration Strategies Replacing Monolithic ERP

Fri, 10 Apr 2026 09:00:00 +0300

Implementing a large monolithic ERP has traditionally been considered the answer to enterprise needs for a unified management system. However, reality shows that monolithic ERPs are difficult to adapt to specific business needs, are expensive, and often evolve into a rigid, 'concrete' system that stakeholders are hesitant to modify.

The Problem with the Monolithic Approach

Any configuration often requires extensive customization, making upgrades painful. Unused modules incur significant licensing costs. Implementations can stretch for years. Furthermore, vendor lock-in becomes virtually impossible to overcome without a complete re-engineering of processes.

Scaling Beyond Google Drive for Enterprise Document Needs

Thu, 09 Apr 2026 13:57:59 +0300

A recent analysis examines the transition from basic cloud storage solutions like Google Drive to specialized Electronic Document Management Systems (EDMS) for growing businesses. While Google Drive is a convenient tool for collaborative file storage and editing, its capabilities become insufficient when a company faces increasing document volumes, complex approval workflows, and the need for automation.

The key difference lies in that cloud storage answers the question 'where is the document stored,' whereas an EDMS focuses on 'how the document moves, who is responsible for it, which version is current, and what needs to happen next.' For businesses, this signifies a shift from passive storage to active management of a document's lifecycle. EDMS provide version control, transparent approval routes, role-based access, action history, and advanced attribute-based search, rather than just file name searches.

AI Agents in Enterprise: Automating Tasks and Supporting Decisions

Wed, 08 Apr 2026 09:00:00 +0300

Large Language Models (LLMs) have redefined the capabilities of software. However, in an enterprise context, the true value of AI is unlocked through integration with business processes, where an AI agent doesn't just respond but actively performs actions within systems.

What is an AI Agent in an Enterprise Context?

An AI agent is a software component capable of independently planning a sequence of actions to achieve a specific goal, leveraging a set of available tools. In an enterprise environment, these 'tools' typically refer to the APIs of corporate systems such as ERP, ECM, CRM, databases, and external registries.

Distinguishing between workflow automation, RPA, and BPM

Tue, 10 Feb 2026 09:17:22 +0200

Amid the rapid adoption of AI and automation tools, IT architects and COOs face a critical challenge. The drive to optimize operations quickly often leads to the chaotic implementation of point-based solutions. Business leaders frequently confuse tactical task automation (RPA) with strategic process management (BPM). This triggers the emergence of "shadow" processes, new bottlenecks, and the accumulation of technical debt from custom integrations. To avoid fragmentation and inefficiency, organizations must clearly distinguish between these technological layers and their roles within the overall enterprise architecture.

2026 outlook for SCADA systems and Industrial IoT

Fri, 30 Jan 2026 13:03:46 +0200

In 2026, Industrial Internet of Things (IoT) and Supervisory Control and Data Acquisition (SCADA) systems continue to evolve, transforming operational efficiency and security in critical infrastructure, manufacturing, and energy sectors. According to industry observations, a significant portion of enterprise clients are actively implementing hybrid models that combine on-premises SCADA with cloud platforms for IoT device analytics and management.

IT and OT convergence: new challenges and opportunities

The traditional gap between IT (Information Technology) and OT (Operational Technology) is rapidly narrowing. Data from IoT sensors and SCADA systems are no longer just monitored but are integrated into corporate ERP and MES systems, feeding analytical platforms and decision support systems. This convergence demands new approaches to architecture, data governance, and, most importantly, cybersecurity. Standards such as ISO/IEC 27001 are becoming mandatory not only for IT but also for OT environments, especially in the context of NIS2, which extends to critical infrastructure operators.

Integrating RPA and low-code for advanced BPM automation by 2026

Fri, 30 Jan 2026 12:39:06 +0200

By 2026, over 80% of large enterprises will utilize a combination of Robotic Process Automation (RPA) and low-code platforms to optimize business processes. This Gartner forecast highlights the growing need for tools that not only automate routine operations but also allow for rapid adaptation of business logic to changing conditions. Complex Business Process Management (BPM) processes, spanning multiple departments, integrating with diverse systems, and involving dynamic execution conditions, demand a flexible and efficient approach that merges robotic capabilities with rapid application development.

Business benefits of combining AI automation with low-code

Tue, 13 Jan 2026 11:21:17 +0200

A new article has been released focusing on AI-driven business process automation using modern low-code platforms and intelligent document processing (IDP) technologies.

AI automation combines traditional workflow automation with artificial intelligence to handle complex tasks that previously required human intervention. Unlike traditional systems that halt when encountering non-standard situations, AI solutions can recognize unstructured data, understand context, make decisions, and learn. This enables software systems to independently read, verify, and route corporate data, freeing employees from routine operations.