The IntelliSMART Platform
Enterprise-grade infrastructure for building, deploying, and managing AI agents at scale—from digital to embodied robotics.
Core Capabilities
Agent Orchestration
Multi-agent coordination with role clarity and deterministic handoffs
Persistent Memory
Vector and graph memory for context retention and personalization
Native Integrations
Pre-built connectors for CRM, ERP, email, browsers, and more
Policy & Guardrails
Enterprise-grade controls, compliance, and safety mechanisms
Full Observability
Complete visibility into agent behavior, costs, and performance
Flexible Deployment
Cloud, on-prem, or hybrid—deploy where your data lives
Agent Orchestration
Multi-agent coordination with role clarity and deterministic handoffs
- Role-based agent assignment and routing
- SLA enforcement and escalation policies
- Parallel and sequential task execution
- Dynamic workload balancing
- Cross-agent context sharing
Platform Architecture
Five-layer architecture designed for scalability, reliability, and extensibility
Agent Layer
Autonomous agents with specialized roles and capabilities
Orchestration Layer
Workflow engine, routing logic, and state management
Intelligence Layer
LLM inference, vector search, and decision logic
Integration Layer
API connectors, data transformers, and event handlers
Infrastructure Layer
Compute, storage, networking, and security primitives
Technical Specifications
Performance
Security
Scalability
Intelligence
Developer-First APIs
RESTful APIs, SDKs in 7 languages, GraphQL endpoints, and comprehensive documentation. Build custom agents or extend existing ones with ease.
- Comprehensive REST & GraphQL APIs
- Python, JavaScript, Go, Java, Ruby SDKs
- OpenAPI 3.0 specification
- Interactive API playground
- Webhook support for real-time events
- CLI tools for deployment automation
from intellismart import Agent
# Create a custom agent
agent = Agent(
name="invoice_processor",
role="ops_automation",
tools=["pdf_parser", "erp_api"],
guardrails=["pii_filter"]
)
# Deploy to production
agent.deploy(
environment="production",
scaling="auto"
)
# Monitor performance
metrics = agent.get_metrics()
print(f"Success rate: {metrics.success_rate}")Deployment Options
Cloud
Fully managed, auto-scaling infrastructure
- Zero ops overhead
- Global CDN
- Automatic updates
- 99.95% uptime SLA
Hybrid
Agents in cloud, data on-prem
- Data sovereignty
- Reduced latency
- Existing infra leverage
- Flexible networking
On-Premises
Full control in your data center
- Air-gapped support
- Custom hardware
- Your security policies
- Bring your own cloud