Sources and actions are auditable
For each answer, sources, document versions, access rights and confirmations are stored so compliance and risk teams can review results.
Controls models and agents: filters requests and responses, masks personal data and keeps an action log. Pilot from 45 days; being piloted at banks in Uzbekistan.
AI in banks: from pilots to control
Kazakhstan. Three quarters of banks already use AI, but according to a National Bank survey only 2% of financial sector organisations have scaled their deployments, and only 27% have been able to measure the return; meanwhile, since 2026 an AI law has been in force with risk classes and a ban on decisions made solely by automated means. Uzbekistan. AI is driven from the top: the strategy to 2030 names scoring and antifraud as priorities, the Central Bank has built its own scoring model and launched its own GPT, and from August 2026 biometric data may not be stored outside the country.
The company’s models and agents follow common rules: filters, access rights and an action log
The platform connects models, assistants and agents to the company’s systems. It checks requests and responses, applies access rights and records actions for audit.
For each answer, sources, document versions, access rights and confirmations are stored so compliance and risk teams can review results.
The platform applies input and output filters, personal data masking and access rights from the company’s systems.
The pilot tests a selected process and KPIs. Milestones: audit on day 0, launch on day 14, assessment on day 45. Being piloted at banks in Uzbekistan.
Request and response filtering: personal data masking, blocking of harmful prompts and secret leakage.
Sources, document versions, access rights, response rationale, agent actions and approvals are recorded in the audit log.
Company data center or private cloud, zero trust and encryption. Access rights are inherited from the company’s systems.
Document search with source links; preparing documents, creating requests and launching approvals within the employee’s rights.
Configure the agent’s model, instructions and steps in the interface for sales, support, HR and documents. Filters and logging included.
Review of contracts, regulations, specifications, tenders and credit files, including scans. Findings come with sources and versions; disputed points are passed to an expert.
A single queue for requests from the portal, chatbot, messengers, social media and call center. Speech recognition, classification, duplicate merging; complex issues are passed to an employee.
Local models or external ones under contract with Rocket Tech. Switching models keeps rules, the log, data and agents. AI partnerships
Quality and drift monitoring, fine-tuning, cost control — by subscription or by the client’s trained team. AI for teams
Selecting the process, data, pilot KPIs and security requirements.
Deployment within the client’s perimeter or on a pilot environment: filters, log, access rights and first scenarios.
Comparing results against KPIs, reviewing the log with compliance and risk, rollout decision.
Connecting departments and channels, configuring policies and reporting, training the client’s team.
Monitoring, fine-tuning and cost control — by subscription or by the client’s trained team. Delivery
The platform runs in the company’s data center or private cloud; documentation and the log stay with the client. Price and timeline are set in the contract.
Monitoring, fine-tuning, cost control and new agents — by subscription or by the client’s trained team.
Building the AI team and processes, launch, reaching agreed metrics and handover to the client. How it works
“A company doesn’t need another chatbot. It needs AI it can be accountable for: where the answer came from, who had access, who approved it. That’s why we put controls in place before models — and a pilot on one real process shows how it works.”
Oleg SolabayevCTO
Only what is permitted. The platform runs in the company’s data center or private cloud; external models receive only data permitted by company policies and the contract, and personal data is masked.
Filters, data masking, access rights and an audit log; models, search, assistants, agents, speech and document recognition, document verification.
A log with sources, document versions, access rights, answer rationale, agent actions and approvals.
Local or external under contract with Rocket Tech: OpenAI, Anthropic, Qwen via Alibaba Cloud. Switching models keeps data and agent settings.
Within an employee’s permissions: creating requests, launching approvals, preparing documents. Critical and disputed actions are confirmed by a person; actions are recorded in the log.
It starts with choosing the process, KPIs and security requirements. Targets: pilot launch on day 14, results review on day 45; timelines are refined for each project.
The platform controls data, queries, responses and agent actions based on access rights. The log lets you analyze the result and present it to compliance and the regulator.
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