Retain the power of AI automation, with stronger infrastructure control.
SVCE is the execution environment that keeps the Clevi-X platform’s AI agents operating safely by isolating, governing, and validating them at the infrastructure layer. किसने क्या किया और कब किया, यह सब स्वचालित रूप से रिकॉर्ड किया जाता है।
Built for environments like yours
SVCE fits organisations that must meet regulatory requirements, operate complex integrated systems, or maintain direct control of their infrastructure.
Financial services · Public sector
ऐसे वातावरण जहाँ विनियमन और ऑडिट अनिवार्य हैं
Enterprise IT
Unified operation of complex systems
ऑन-प्रिमाइसेज़
Direct control over your own infrastructure
Cloud native
Containerised workload operations
How SVCE works within the Clevi-X platform
SVCE is not a standalone solution. It is the control layer between your infrastructure and the Clevi-X platform that governs every agent execution.
Customer infrastructure
ऑन-प्रिमाइसेज़ · प्राइवेट क्लाउड · मल्टी-क्लाउड
↓
SVCE · इन्फ्रास्ट्रक्चर नियंत्रण परत
Isolation · Access · Audit · Execution control
↓
Clevi-X platform
AI agents · Business automation workflows
How does SVCE compare with conventional approaches?
Agents directly on a server are lightweight but risky; virtual machines are secure but resource-intensive. SVCE bridges the gap with lightweight containers.
Comparison
सर्वर-आधारित एजेंट
VM-based
SVCE
अलगाव
कम
उच्च
High (lightweight)
Access control
Implemented in application code
Requires configuration
रनटाइम में अंतर्निर्मित
प्रति-कार्य अलगाव
Difficult
Inefficient
Automatic for each container
प्रावधान · हटाने की गति
तेज़
Slow
तेज़
लागत दक्षता
उच्च
कम
उच्च
Audit logs
कस्टम बिल्ड आवश्यक
कस्टम बिल्ड आवश्यक
अंतर्निर्मित केवल-जोड़ने योग्य लॉग
AI agent boundaries
कस्टम डिज़ाइन आवश्यक
कस्टम डिज़ाइन आवश्यक
Standard policies included
The risks of running agents directly inside a server
Embedding an agent directly in a server may be quick to build, but isolation is weak and control depends on application code.
One failure can spread across the service
When agents run as internal server logic, an error, malicious code, or external attack in one task can propagate across the entire service.
Risk — Potential service-wide outage
Access control depends on application code
जब अनुमतियाँ एप्लिकेशन कोड में होती हैं, तो संवेदनशील डेटा और API पहुँच पर एकसमान नियंत्रण लागू करना कठिन होता है।
Risk — Limited control over sensitive data and APIs
परिणामों का सत्यापन करना कठिन है
Without a fixed execution environment, the same task may run differently, making reproduction, auditing, and result verification difficult.
जोखिम — विश्वसनीय पुनरुत्पादन, ऑडिट या सत्यापन नहीं
The four foundations of SVCE
Treat agents not as simple response systems, but as production-grade workers with security boundaries and explicit execution privileges.
अलगाव
Container-based isolation prevents malicious code, abnormal commands, and external attacks from spreading beyond an AI agent's execution space. The container is destroyed after each task to reduce residual-data risk.
Keep every execution within a secure boundary
नियंत्रण
एजेंट कभी भी अपनी अनुमतियाँ स्वयं निर्धारित नहीं करते। Command Mediator और Orchestrator प्रत्येक कार्य के अनुसार पहुँच प्रदान और प्रतिबंधित करते हैं, तथा Research, Code और Executor जैसी भूमिकाओं के लिए फ़ाइलों, नेटवर्क, API, सिस्टम कमांड और सीक्रेट्स पर अलग-अलग सीमाएँ लागू करते हैं।
Control what agents can and cannot do at the infrastructure layer
Efficiency
Lightweight containers start faster than VMs and are created only when work is ready. CPU, memory, I/O, and GPU resources are limited and allocated per task to balance cost and performance.
Use only the resources each task needs
Scale
Run multiple users, tasks, and agents simultaneously. Containers scale automatically as requests increase, failures remain isolated to individual tasks, and agents can be separated by role.
Scale reliably across many users and agents
Requests are never executed immediately. Every request goes through the Command Mediator gate, where policy, permission, and approval checks must pass before execution in an isolated container.
User / Workflow
AI or operator submits a task
→
Command Mediator
निष्पादन से पहले नीति, अनुमतियाँ और स्वीकृतियाँ जाँचें
→
Isolated agent container
Run work as an independent execution unit
→
Tools · API · Data
केवल वही पहुँचें जिसकी नीति अनुमति देती है
↑ Every request passes through
Policy validation
अनुमति जाँच
Command transformation
Approval flow
Orchestrator determines the container, permissions, network policy, CPU and memory allocation, and maximum execution time for each task.
Audit log · Example live operations record
2026-05-14 02:31:04अनुरोधresearch-agent → Request access to the production database for payment-log analysis
2026-05-14 02:31:05Deniedcommand-mediator → नीति उल्लंघन · प्रोडक्शन DB तक सीधी पहुँच अवरुद्ध · स्वीकृति आवश्यक: req_8c4a
2026-05-14 02:33:18Approved@kim.ops → approve(req_8c4a) · केवल रीड-ओनली पहुँच तक सीमित
2026-05-14 02:33:20Executionorchestrator → Isolated container created · Read only · Network restricted · TTL 10m
2026-05-14 02:33:24ऑडिटsvce → Commands, results, and access records stored (append only)
