Elar began using an AI assistant built into the development environment to support ECM platform implementation specialists

2026: Application of AI assistant to support ECM platform implementation specialists

Elar Corporation began using an AI assistant built into the development environment to support ECM platform implementers. We are talking about a tool that becomes part of everyday engineering practice and helps to work with code faster, more accurate and more stable. Elar announced this on February 6, 2026.

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Фото: Elar

In ECM systems implementation projects, a significant part of the time is traditionally spent on routine operations: writing and adjusting macros, configuring typical scripts, adapting repeated code fragments to the requirements of a particular project. These tasks require accuracy and deep knowledge of the platform, but are often reproduced from project to project, creating an additional burden on the implementation teams.

The AI implementation is implemented as a code assistant built directly into the IDE - a development environment in which specialists work daily with the settings and platform code. This allows you to use the capabilities of AI without switching between tools, documentation and external services.

At the request of the intruder, the assistant can form a macro configuration code block for a specific task. In the development process, a context completion mechanism is also available: AI analyzes the code around the cursor and prompts for relevant constructs, parameters and sequences of actions. Support is built right into the workflow and does not require a separate use case.

The use of code generation and context completion allows you to significantly reduce the amount of manual work associated with typical setup operations. Instead of searching for examples in past projects and their subsequent adaptation, the implementer receives code fragments and hints that already correspond to platform logic and accepted implementation practice.

This effect is achieved due to the fact that the AI engine of the implementation is further trained on the documentation of the ECM platform and a specially prepared set of high-quality examples of macros. Thanks to this, the assistant does not rely on abstract recommendations, but on real architecture and accumulated engineering practice.

• accelerates the implementation of typical scenarios;
• Reduces the possibility of errors in setup operations
• lowers the entry threshold for new specialists, allowing them to quickly understand the logic of the platform.

The AI assistant is used in everyday work by all specialists in the implementation of ELAR, becoming the standard working tool of the team. According to internal assessment, on certain classes of tasks, the reduction in labor costs when using AI reaches 87.5%.

One of the key features of the ELAR AI implementation is work in a corporate closed loop. This means that all development and configuration elements - code, parameters, technical details of customer projects - remain within the company's infrastructure.

Unlike using external AI tools, this approach eliminates the transfer of sensitive technical information outside the corporate environment and provides the necessary level of confidentiality when implementing corporate systems.

The built-in AI assistant is gradually becoming not just a tool for accelerating development, but a universal mechanism for supporting work with configurations and code in corporate systems. This approach can be scaled to other tasks where work with regulated scenarios, complex logic and a large amount of repetitive operations is required - from the maintenance and development of ECM solutions to their adaptation to new requirements and changes in business processes.

In this sense, the AI assistant acts as an infrastructure element that increases the reproducibility of solutions, makes implementation processes less vulnerable to personnel changes and load redistribution in the team, and also allows you to systematically manage the quality and speed of implementation.