STRELI

EDGE NATIVE AI FOR PROCESS MANAGEMENT

Streli: Autonomous​ optimization for plants that cannot afford guesswork

Streli turns operator expertise, noisy sensor data, and plant constraints into physics-grounded control logic that runs close to production.

5-10%

targeted yield and energy improvement at source

Edge

local execution for plant-floor reliability

GBA

Hong Kong base with China deployment focus

24/7

decision support for volatile process conditions

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EDGE-NATIVE AI FOR PROCESS MANUFACTURING

Industrial AI fails when it stays in dashboards

Process manufacturers already have data, historians, controls, and experienced operators. The missing layer is a repeatable way to turn that knowledge into trusted decisions at the machine, line, and plant level.

About Us

STRELI Technology Limited was founded in 2024 to bridge the gap between complex industrial challenges and virtual AI solutions. Our journey began when industry leaders needed more than just advice—they needed AI that worked. We stepped in to solve complex industrial cases using our Data Science expertise, and delivered measurable impact.​

The Streli System

Cognitive edge computing for whole-plant optimization​

A two-part architecture translates messy industrial reality into executable control logic, then runs it locally where latency, uptime, and plant context matter.

The Streli System

Operator knowledge

Plant documents, historian tags, operating rules, and production targets.

Cognitive Engine

little m

Builds physics-grounded process context and recommends stable operating actions.

Industrial edge

Industrial Edge

Builds physics-grounded process context and recommends stable operating actions.

Our Services & Products​​

Tailored Solutions

World leading AI research team with over 15+ year experience in industrial sectors

AI Agent “little m”

Advanced AI software suite for industrial process control. Pre-trained on manufacturing logic

purple box

Secure edge-computing hardware. Hosts AI directly on your factory floor for real-time process optimization.

Built for process conditions where quality, yield, and energy are tightly coupled.

Specialized AI Agent​

Start with one constrained process. Expand after measurable value

Streli pilots should be framed around four plant-level outcomes: quality, throughput, energy, and material efficiency.

Map the process

Identify the line, variables, operating constraints, energy drivers, and production KPIs.

Capture expertise

Convert operator rules, SOPs, and historical data into a usable process baseline.

Deploy at the edge

Run recommendations close to the plant floor, validate improvement, and prepare scale-out.

Scale what works

Use validated results to expand across adjacent equipment, lines, and plant-level optimization targets.

Bring autonomous optimization to one high-value process.

A focused pilot should prove measurable impact in yield, energy, stability, or engineering time before broader deployment

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