VK Tech Adds Multi-Level Memory to AI Agents in VK AI Space Platform

VK Tech has introduced a four-layer memory system for AI agents within its VK AI Space platform, enabling them to retain context, reuse materials, and incorporate past employee edits instead of restarting tasks from scratch. The new capability is expected to reduce the share of repeatedly solved tasks by 40–50 percent. Memory layers include session memory for current dialogues, user memory for employee profiles and preferences, project memory for specific project materials and rules, and agent memory for recording successful approaches and human corrections. This transforms AI agents from short-term tools into consistent team participants that can draw on accumulated corporate knowledge during tasks such as tender preparation, incident investigation, and product launches. Access remains strictly limited to information the collaborating employee is authorized to view, with all data stored inside the company perimeter and never sent to external services. Users can review and delete stored information at any time. VK Tech believes the feature will convert individual specialist experience into a persistent organizational asset that carries forward across tasks.

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VK Tech has enhanced its VK AI Space platform by adding multi-level memory capabilities to GenAI agents. The update allows agents to preserve context across interactions, reuse previously prepared materials, and take into account past corrections made by employees.

The company expects the new memory system to cut the proportion of repeatedly solved tasks by 40–50 percent. Memory is organized into four distinct layers that operate together to give agents longer-term awareness while maintaining strict access controls.

Four Memory Layers

  • Session memory stores the current dialogue flow and active tasks.
  • User memory records an employee’s profile and individual preferences.
  • Project memory collects materials, decisions, and rules specific to a given project.
  • Agent memory captures the agent’s own working experience, including approaches that produced results and subsequent human adjustments.

With these layers in place, an agent evolves from a short-term digital assistant into a consistent team participant. For example, when preparing a tender response, the agent can draw on the corporate knowledge base, incorporate previous employee edits, and retain both the original data and the revised versions for future use.

The same mechanism applies to incident investigations, project reporting, and product launches. Agents can locate similar past cases, recall the decisions taken, and factor in the reasoning that led to those decisions.

Access to information remains tightly controlled. An agent receives only the data that the collaborating employee is permitted to see. All stored information resides inside the company’s own infrastructure and is never transmitted to external services. Employees can review the contents of any memory layer and delete unnecessary entries at any time.

VK Tech states that the approach will help organizations convert the experience of individual specialists into a durable corporate asset that persists beyond any single conversation and transfers across successive tasks.

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