seleta✳
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AI SYSTEMS FOR MANUFACTURERS

Turn industrial datainto decisionsand action.

We build AI software for equipment service and manufacturing analytics.

Connect machine data, production records and business systems. Give your teams traceable evidence to diagnose faults, investigate quality issues and decide what to do next.

Built close to the work.
Designed for real decisions.

Turn time-consuming work
into everyday AI workflows.

Based in Shanghai, Seleta focuses on industrial digitalization and trusted manufacturing analytics. We work inside real operations, connecting existing machines, software and business documents. Scattered data becomes verifiable evidence, helping service, quality, production and management teams make decisions together and improve over time.

Shanghai · Yuanli Community, Xuhui

What we build

Start with one operational task.
Connect data and action on existing systems.

Connected machines

Equipment software & service · Core focus

Connect equipment status, alarms and maintenance records while preserving existing PLCs, HMIs and safety systems. Give service engineers evidence from the field before they plan remote diagnosis and action.

Evidence to decisions

Trusted manufacturing analytics · Core focus

Turn paper production records, Excel and MES/ERP data into traceable evidence. Deterministic calculations produce the numbers; AI explains the results; business teams confirm the next step.

SEO Flow

Global manufacturing growth · Project capability

Connect brand websites, keyword research, AI content, human review and publishing with search, advertising and sales feedback. Make every content investment part of a measurable workflow.

Selected work

From the factory floor to manufacturing analytics.
Every step has a defined scope of validation.

Industrial sawing and automation equipment manufacturerInitial field validation · 2026.08

Keep the controls. Connect the field.

Equipment data was confined to PLCs, HMIs and engineering documents. Remote service teams struggled to collect evidence, while new software had to leave the existing control system undisturbed.

Progress so far

Completed read-only validation on a reference machine, bringing live controller data into an on-site web interface. The trial did not modify PLC programs, write to the controller or trigger machine movements.

Delivery approach & next steps

Added read-only data acquisition, a local API and a status interface above the existing control layer. Data sources, timestamps and disconnections are made explicit, establishing a foundation for maintenance records and remote service.

Next: validate long-term reliability and the complete service workflow before expanding to more machine types.

Tape, adhesive and functional materials manufacturerAnalytics development & acceptance preparation · 2026.08

One question. A shared body of evidence.

Paper production records, quality data and purchasing spreadsheets were scattered across departments. Inconsistent definitions led to double counting, and key figures could not be traced back to their source files.

Progress so far

Initial capabilities include reports, batch tracing and purchasing price comparisons. When matching samples are missing, the system reports insufficient data rather than presenting possible associations as confirmed causes.

Delivery approach & next steps

Brought OCR records and spreadsheets into a versioned data foundation. Key figures retain file, page and cell references, with defined calculations, batch relationships and approved corrections.

Next: validate consistent results, source traceability and correction workflows against a fixed set of business questions.

Industrial equipment brand serving overseas marketsLive · Early growth validation · 2026.07

Give every publication a next step.

The website, SEO content and traffic data were disconnected. The team struggled to maintain a regular publishing process and decide what to do after each change.

Progress so far

The content production and publishing workflow is live. Search and advertising signals feed a shared analysis process and a queue of page improvements. The team can track publishing progress, page performance and who owns the next action.

Delivery approach & next steps

Improved the website’s technical foundation and mapped keywords to pages. Connected AI drafts, human review, WordPress publishing and analysis of Search Console, GA4 and advertising data.

Next: establish an attribution baseline using sales-qualified inquiries, quotations and closed deals.

From evidence.
To action.

Detect → Gather evidence → Human review → Act → Verify.
Validate one complete workflow, then build for the long term.

01Define the outcome.Discovery & pilot

Start with a problem worth solving. Record the existing process, sample data and business metrics. Define the pilot scope, users, human handover points and acceptance criteria, then deliver a complete working flow.

02Connect what exists.Integration & deployment

Connect authorized data from existing PLCs, MES, ERP and Excel. Choose local, on-premises or private-cloud deployment to suit the use case, with access controls, monitoring, rollback and training. People confirm consequential actions.

03Close the loop.Operations & improvement

Record actions, actual outcomes and rule corrections in the system. Continuously evaluate models and workflows, comparing data preparation time, incident handling and real usage on a consistent basis.

Equipment service, manufacturing analytics, or a business problem worth solving?

Let’s make
it matter.

We work with people who care about what they build,
turning complex problems into a clear next step.