AI and AI agents
Practical artificial intelligence inside information systems
We apply AI where it produces a measurable result: documents, citizen requests, data, video streams and routine operations. Every agent action is logged, and accountable decisions are confirmed by an employee.
- AI analyses data and documents.
- AI prepares a recommendation.
- AI assists the operator in real time.
- An authorised employee confirms the decision.
TEQ Intelligence Layer
TEQ Intelligence Layer
A platform layer shared by every solution in the ecosystem.
- 1DataDocuments, registries, databases, event streams, video and source APIs.
- 2Knowledge baseA secured knowledge base with access control and versioning.
- 3ModelModel Gateway: the right model per task, quotas, private perimeter.
- 4AI agentAn agent with a role, instructions, constraints and audited actions.
- 5ToolsPermitted tools: search, calculation, API calls, MCP servers.
- 6Information systemWriting the result back through controlled interfaces.
- 7EmployeeAn authorised employee reviews and confirms the decision.
orchestration
- Agent OrchestratorManages agent roles, step sequencing and task handover between agents.
- Model GatewayA single entry point to models: task routing, quotas, cost control and private perimeter.
- API GatewayControlled access for agents and external systems with authentication and rate limits.
- MCP-серверыConnecting tools and data sources to agents over a standardised protocol.
- A2A-интеграцииAgent-to-agent interaction with fixed contracts and audit logging.
- Инструменты и API агентовThe list of permitted operations: search, calculations, reads and writes to information systems.
knowledge
- Enterprise RAGRetrieval and answer generation over corporate documents, respecting the user's access rights.
- Защищённая база знанийA store of approved materials with versioning, sources and validity periods.
control
- Identity and Access ManagementA single rights model: an agent acts only within the user's or role's authority.
- ЖурналированиеAn immutable trail of requests, answers, sources used and operations performed.
- Human-in-the-loopMandatory human confirmation points for accountable operations.
- AI ObservabilityObservability of quality, latency, cost and tool usage frequency.
- AgentOpsAgent operations: versions, releases, regressions, incidents and on-call.
- GuardrailsConstraints on topics, actions and data, including prompt injection protection.
- Evaluation pipelinesTest sets and metrics that gate the release of an agent version.
- Защита персональных данныхMasking, minimisation and control over personal data passed to models.
deployment
- Казахский и русский языкиTwo-language support in voice and text scenarios, including domain terminology.
- On-premise и private cloudDeployment inside the client's perimeter, including closed network segments.
Types of AI agents
An agent is a role with a limited set of tools, access rights and audited actions.
The AI modules are built and connect to the solutions. They are not yet running in production at client sites — they are available for a pilot or a deployment project.
Citizen AI Agent
AI module availableAnswers routine citizen questions and explains required documents and the service procedure in Kazakh and Russian.
- Search over the service knowledge base
- Document checklist generation
- Escalation to a human operator
Makes no service decisions. Answers come only from the approved knowledge base; ambiguous cases are escalated to an operator.
Operator Copilot
AI module availableAssists the operator in real time: surfaces the regulation, drafts the conversation summary and a reply.
- Dialogue summarisation
- Regulation hints
- Reply draft
- Topic classification
A reply is sent only after the operator confirms it. All hints are logged.
Document AI Agent
AI module availableRecognises documents, checks completeness, detects discrepancies and prepares a routing card.
- OCR and field extraction
- Checklist validation
- Registry cross-check
- Request routing
Approval or rejection is decided by an authorised employee. The agent records the basis of every check.
Workflow AI Agent
AI-readyMonitors process flow: deadlines, owners, deviations and reminder preparation.
- Deadline control
- Deviation detection
- Reminder generation
- Escalation
Process status changes happen only through permitted, logged operations.
Analytics AI Agent
AI module availablePrepares analytical commentary on metrics, detects anomalies and drafts reports.
- Data mart queries
- Anomaly detection
- Scenario modelling
- Report draft
Every conclusion references its data source. Publishing a report requires confirmation.
Project Portfolio Agent
AI module availableAnalyses the project portfolio: risks, resource load, likely delays and related assignments.
- Delay forecasting
- Workload analysis
- Project document search
- Minutes preparation
A risk score is a recommendation. Project priority is decided by the manager.
Vision AI Agent
AI module availableProcesses computer vision events, builds an incident card and supports natural language video search.
- CV event processing
- Object tracking
- Licence plate recognition
- Video archive search
An event is a signal for operator review, not a basis for automatic enforcement.
Network AI Agent
AI-readyTracks network health, forecasts load and assists with diagnostics and routine support.
- Anomaly detection
- Load forecasting
- Diagnostics
- Ticket automation
Configuration changes are applied by an engineer. The agent prepares the action plan.
CRM Copilot
AI module availableBuilds the customer profile, summarises communications and suggests the next best action.
- Customer 360
- Communication summaries
- Task creation
- Semantic search
Commercial commitments are made by employees. The agent never messages customers without confirmation.
IT Support Agent
AI-readyHandles routine user requests, drafts solutions from the knowledge base and routes incidents.
- Request classification
- Knowledge base search
- Solution draft
- Service Desk routing
Incident closure is confirmed by a support engineer.
AI Delivery Framework
AI deployment as an engineering process with verifiable results at every step.
- 1DiscoverDefine the task and the expected result.
- 2AssessAudit data, processes, risks and infrastructure.
- 3PrototypeBuild a limited working prototype.
- 4EvaluateTest quality, safety and economic effect.
- 5IntegrateIntegrate with data, documents, APIs and systems.
- 6DeployDeploy to cloud, private cloud or a closed perimeter.
- 7OperateMonitoring, AgentOps, quality and cost control.
AI credibility rules
We separate existing features, deployed AI capabilities, available modules and development directions. The phrasing “AI makes the decision on its own” is never used for government, financial or security-related processes.
- ImplementedThe capability is implemented in the product.
- In productionThe system is running at a customer site.
- AI-readyThe architecture is ready for the AI layer.
- AI module availableThe AI module is built and connected separately.
- Available for pilotA limited pilot deployment is possible.
- In developmentThe capability is under development.
- Development conceptA development direction that requires further work.
Languages and hosting perimeter
Kazakh and Russian language support in voice and text scenarios. Deployment on-premise or in a private cloud.
AI capabilities per solution
Every solution in the ecosystem has a defined set of AI features and a specialised agent.
- Project management system7 · AI layer
- Unified contact centre9 · AI layer
- Digital budgeting6 · AI layer
- Digital checkpoint6 · AI layer
- Ashyq Ukimet service akimat6 · AI layer
- Customer relationship management system7 · AI layer
- Participatory budgeting7 · AI layer
- Special economic zone digitalisation6 · AI layer
- Sardar intelligent video analytics9 · AI layer
- Guest Wi-Fi network system6 · AI layer
Have a challenge that needs to become a working system?
Tell us about the project — the TEQ team will propose a possible format for research, development or deployment.
- TEQ World
- +7 7172 677 178
