Agentic Systems Division

Autonomous Agentic AI.

Deploy secure networks of AI agents running stateful cognitive loops — decomposing objectives, writing connection scripts, syncing edge telemetry, and validating logical correctness without human intervention.

Request Technical AuditWatch Simulation
agent_consensus_node.config
const consensusNetwork = new ConsensusNetwork({)
nodes: [
{ id: "planner", validationWeight: 1.0 },
{ id: "executor", sandboxAccess: ["fs", "db"] },
{ id: "validator", rules: "validation.rs" }
]
});
CONSENSUS ACTIVE
3 AGENTS RUNNING
Security
Sandbox Locked
Validation
All Checks Pass
Core Mechanics

The Three Layers of Execution

Our agent architectures run continuous state loops to query data, write self-correcting logic, and verify schemas against production guidelines.

Goal-Oriented Decomposition

The planning agent breaks high-level objectives into ordered sub-tasks, verifying dependencies and data availability before writing a single line of code.

Stateful Sandbox Execution

Agents are granted scoped tool privileges—MQTT nodes, SQL write connections, file I/O—to implement production-grade integrations autonomously.

Consensus QA Validation

A dedicated verification agent runs schema checks and logical assertions on every output, requesting targeted refactors if any condition fails.

< 2s
Agent Response Time
99.9%
Uptime SLA
3-layer
Security Validation
∞
Tool Integrations
Console Simulation

Interactive Multi-Agent IDE

Watch real-time task decomposition and tool usage across agent nodes. Click Run to execute the pipeline.

1. Objective
2. Planner
3. Executor
4. Validator
5. Done
WORKSPACE_FILES
orchestrator.ts
○ READY
import { AgentExecutor, ConsensusNetwork } from "@urjavikas/agent-sdk";

export async function runOrchestration(objective: string) {
  // Decompose into sub-tasks
  const planner = new AgentExecutor({ role: "Planner" });
  const plan = await planner.decompose(objective);

  // Execute sub-tasks
  const executor = new AgentExecutor({ role: "Executor" });
  const result = await executor.execute(plan.tasks);

  return ConsensusNetwork.validate(result);
}
runtime_logs (~/stdout)
Waiting for simulation... Click 'Run Pipeline' to execute.
SANDBOX READY○ IDLE
Integrations

Real-World Agent Scenarios

We deploy agent environments that sync telemetry streams and execute serverless pipelines securely at scale.

IoT / Edge

Self-Healing MQTT Telemetry Ingest

Edge-hosted agents monitor incoming MQTT streams from solar installations. On detecting connection failures, the agent autonomously switches to local SQLite caching, then re-syncs to the cloud when connectivity is restored — zero data loss.

MQTT BrokerSQLiteFailover HandlersEdge Runtime
Data Engineering

Structured Data Extraction Pipelines

AI agents parse raw unstructured log streams, PDFs, and API responses. The executor normalises formats, validates schemas against production rules, and inserts clean records directly into PostgreSQL — all without human oversight.

Schema ValidationAPI GatewayRust CorePostgreSQL

Zero-Trust Sandbox

All agent tool access is scoped, token-authenticated, and audited in real time.

Self-Healing Loops

Agents retry, reroute, and escalate autonomously without manual intervention.

Edge-Compatible

Deployable on MQTT brokers and edge nodes across remote industrial sites.

FAQ

Common Questions

Get Started

Deploy your first
Agentic System.

Speak to a systems architect to design secure task-loops and real-time syncing pipelines tailored to your infrastructure.

Consult an Architect