ELI
Learn

juna.ai - Business Process Automation Tool

Business Process Automation · Founded by Matthias Auf der Mauer in 2024

juna.ai

juna.ai

Autonomous AI agents optimizing industrial processes for enhanced efficiency and reduced emissions.

Cost

Demo

Rating

People love it

Time to value

Moderate Setup (1-3 hours)

You can use juna.ai to deploy AI agents that autonomously manage and optimize complex industrial processes. These agents analyze real-time data to adjust control settings, improving production throughput, enhancing energy efficiency, and maintaining process stability. By integrating juna.ai, you can reduce operational costs, minimize emissions, and ensure consistent product quality, all while freeing up your team to focus on strategic initiatives.

What juna.ai does

Deploy AI agents to manage industrial processesAnalyze real-time data for process optimizationAdjust control settings to improve efficiencyMonitor energy usage and identify savings opportunitiesGenerate compliance reports automaticallyIntegrate AI solutions with existing manufacturing systemsProvide operators with real-time guidanceTrack and improve product quality metricsAutonomous process control for real-time optimizationEnergy consumption monitoring and reductionPre-trained agents for specific industrial equipmentLow-code agent builder for custom AI solutionsCompliance with ISO50001 standardsReal-time production insights and recommendationsContinuous improvement through AI-driven analyticsIntegration with existing industrial systems

Pricing breakdown

PlanPrice10 seats / yr
Basic$29.00 / mo$3,480
Pro$79.00 / mo$9,480
Business$149.00 / mo$17,880

Annual estimates assume continuous billing at the listed list price. Volume discounts typical above 50 seats.

Frequently asked

Want a tailored answer?

See whether juna.ai fits your stack.

Techbible weighs juna.ai against what you already pay for, your team shape, and the work that's actually happening. Free to start.

juna.ai, industrial AI agents, process optimization, energy efficiency, production throughput, autonomous process control, manufacturing AI, industrial automation, AI-driven manufacturing, process stability, emissions reduction, AI in manufacturing, industrial process management, AI for operations, manufacturing efficiency, AI process control