Tool Fragmentation
Must navigate UI and settings across multiple tools like Kubeflow, MLflow, ArgoCD, Prometheus, Grafana, KServe.
Agentic AI Operations Layer Understanding and Supporting Operations
SAMANDA
AI Services Grow, But
Operations Still
Depend on People.
Operating AI as real services requires more than models. SAMANDA connects operations flows from status checking through incident analysis to deployment and rollback with natural language and Agentic AI structure.
Operations Burden
When incidents occur, SREs manually combine logs, metrics, events and trace root causes.
Deployment Complexity
Model deployment and rollback repeat YAML, approval, and validation procedures.
Air-Gapped Constraints
Secure environments cannot use external LLM APIs, requiring internally-operated AI operations structure.
Executes When Spoken, Observes Status,
Works in Air-Gapped Networks.
SAMANDA connects request, reasoning, and execution flows needed for AI infrastructure operations as single agent.
› Check cluster status for me!
✓ Failed pod detected: sar-ship-predictor
✓ Root cause: Harbor auth secret expiration likely
→ After approval: renew secret and restart pod
Natural Language MLOps Execution
Execute pipelines spanning data preparation, training, evaluation, deployment, and rollback in one sentence.
MLOps ExecutionAutomated FlowJupyterVS Code
Agentic Operations Automation
Check cluster status, logs, metrics, events together and organize anomalies, root cause candidates, and next actions.
State ObservationIncident AnalysisRecovery Guidance
Air-Gapped AI Operations
Use AI operations agents based on proprietary LLMs in on-premise and air-gapped environments without external API dependence.
Local LLMSecure NetworkModel Routing
One Agent Core,
Different Faces by Role
SAMANDA is not single chatbot but
Operations agent split by Ops, Apps, Code personas.
SAMANDA Ops
AI Operations Agent Reading Infrastructure Status
Check cluster status, logs, metrics, failure events and organize anomalies and root cause candidates.
SAMANDA Apps
Business Agent Supporting AI Task Execution
Connect data preparation, training, evaluation, deployment, and inference service management with natural language requests.
SAMANDA Code
Code Agent Working Together in Dev Environment
Support development work like file editing, cell execution, package installation in JupyterLab, VS Code.
SAMANDA Analyzes First,
Controls Execution Per Operations Policy.
Information Queries Execute Immediately
Non-system-changing queries like logs, metrics, events execute immediately.
Light Recovery Actions Are Approval Candidates
Low-impact actions like pod restart, scale adjustment are suggested with root causes.
High-Risk Actions Approved or Blocked
High-impact actions like deployment changes, data deletion, permission changes execute after approval or are blocked.
Infrastructure Operations Tasks
Change with SAMANDA.
Tasks
Before
After with SAMANDA
Model Training and Deployment
BeforeManually handle data preparation, training, evaluation, deployment across multiple tools and configurations.
AfterConnect data preparation, training, evaluation, deployment flow as single pipeline with natural language.
Incident Response
BeforeOperators manually check logs, metrics, events to trace root causes.
AfterSAMANDA detects anomalies and pre-organizes root cause candidates and next action direction.
Air-Gapped AI Operations
BeforeCannot use external APIs making AI-based operations automation difficult.
AfterCan use AI operations agents based on internal LLMs even in on-premise and air-gapped environments.
Operations History Management
BeforeIncident causes, remediation process, approval records scattered across people and tools making repeat response difficult.
AfterRecord analysis results, approval flow, remediation history as foundation for future operational decisions.
SAMANDA FOR AI OPERATIONS
Convert AI Infrastructure
Operations to Approval-Based Agentic Operations.
SAMANDA connects repeated MLOps, LLMOps tasks and incident response flows with faster, consistent operations structure.
Important actions execute through approval flow and results remain as operations history.