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Industry: Industry 4.0 & Manufacturing

We build digital systems that drive manufacturing forward.

  • IoT dashboards and real-time production monitoring systems
  • Predictive maintenance — reduce unplanned downtime by 30-40%
  • AI in quality control, process optimization and demand forecasting
  • Integrations: MES, ERP (SAP/Oracle), SCADA, OPC-UA, MQTT
  • Full code ownership — zero vendor lock-in

IoT dashboard: 6 weeks → MVP, 40% fewer unplanned downtimes

No obligations. NDA on request. Response within 24h.

50+ B2B Deployments SLA 24h Zero Vendor Lock-in
THE COST OF INACTION

Every month without digitalization costs you efficiency, quality and competitive edge.

  • Paper-based production reports — data outdated before it reaches management
  • Equipment maintenance based on schedule, not condition — costly downtimes
  • No real-time OEE visibility — decisions made on gut feeling
  • Data silos: MES, ERP, SCADA don't communicate with each other

Source: McKinsey — digital leaders in manufacturing achieve 20-30% higher OEE.

Manual processes vs. digital automation

80% 60% 40% 20% 0% Q1 Q2 Q3 Q4 Manual (%) Automated Savings
THREE PILLARS

3 pillars of digital transformation for manufacturing.

CUSTOM DEV

Dedicated platforms and dashboards

IoT dashboards, MES systems, quality control panels, supplier portals. Full-stack TypeScript, real-time websockets, edge + cloud architecture.

80%+ test coverage
NITRO

Performance and data processing

Processing millions of sensor readings/min. Time-series DB, stream processing, edge computing. Dashboard loads in <2s even with 10k+ data points.

LCP < 2s
NEURAL

AI and intelligent automation

Predictive maintenance, anomaly detection, computer vision for quality control, demand forecasting. RAG chatbots for operator support on the shop floor.

AI-powered
HARD PROOF

Results you can verify.

Automotive Manufacturer • CUSTOM DEV

Problem

Production monitoring on paper-based reports. Downtimes detected with 4h delay.

What we did

IoT dashboard integrating 200+ sensors, real-time OEE, automated alerts.

OEE: 67% → 82%, downtime −35%

FMCG Manufacturer • CUSTOM DEV + NEURAL

Problem

Quality control based on manual inspection. 5% defects after delivery.

What we did

Computer vision system on the line + AI anomaly detection. Quality dashboard with real-time SPC.

Customer defects −80%, savings 400k PLN/yr

Manufacturing Plant • NITRO + CUSTOM DEV

Problem

Legacy MES with 12s response time. Reports done in Excel.

What we did

New MES dashboard with SAP integration. Pipeline optimization, automated reporting.

Response 12s → 0.8s, reporting: 2 days → real-time

IRONCLAD PROCESS

From diagnosis to result — no guessing.

Each step has a measurable deliverable. You know what you're getting before we start.

1 Week 1-2

Audit & Discovery

OT/IT systems mapping, KPI baseline, integration audit. Pain point analysis and target setting.

2 Week 2-3

Architecture & Scope Lock

IoT architecture design, API contract definition, integration plan. Fixed scope document — no scope creep.

3 Week 4-14

Build sprints + demos

2-week sprints with working demo after each. Sensor integrations, dashboard modules, data pipelines. Daily standups.

4 Week 15-16

QA, release & pilot

Full regression, security scan, pilot on production line. Blue-green deployment, rollback plan, performance validation.

5 Ongoing

Maintenance & Growth

SLA-based support, monitoring, new features. Knowledge transfer to your team or continued development partnership.

Definition of Done

  • 80%+ test coverage (unit + E2E)
  • All OT/IT integrations verified
  • Security scan passed (OWASP)
  • Pilot on production line completed
  • Performance budgets met (CWV green)
  • Knowledge transfer completed
PACKAGES

Packages for digital transformation of manufacturing.

RECOMMENDED

IoT Dashboard

Real-time production monitoring

8-12 weeks

  • IoT sensor integration
  • OEE dashboard with real-time data
  • Automated alerts & notifications
  • Trend analysis & historical data
  • Mobile-responsive interface
  • ERP API integration

Predictive Maintenance

AI-driven equipment care

12-18 weeks

  • ML models for failure prediction
  • CMMS integration
  • Maintenance dashboard
  • Smart alerts & scheduling
  • Cost optimization reports

MES Integration

Modern MES dashboard

10-16 weeks

  • MES dashboard with real-time data
  • SCADA/OPC-UA integration
  • SAP API connector
  • Automated reporting
  • Role-based access control (RBAC)

Quality Control AI

Computer vision + SPC

12-20 weeks

  • Computer vision defect detection
  • Statistical Process Control (SPC)
  • Anomaly detection AI
  • QMS integration
  • Compliance & audit trail

Final price depends on system complexity and number of integrations. Free estimate after consultation.

What's included in the price

  • Full source code ownership
  • Git repo with complete history
  • CI/CD pipeline setup
  • Staging + production environments
  • Knowledge transfer session
  • Post-launch support (30 days)

What we DON'T do

  • "Quick fixes" without measuring results
  • Integrations without API contract
  • Copy-paste templates without customization
  • Promises without data and timeline
TECH STACK

Stack and integrations for manufacturing.

Frontend

React / Next.js TypeScript Tailwind CSS React Native

Backend & API

Node.js / NestJS PostgreSQL / TimescaleDB Redis GraphQL / REST

Integrations

SCADA (OPC-UA) MES (Siemens, Rockwell) ERP (SAP, Oracle) MQTT / Kafka

Infrastructure

Docker GitHub Actions Terraform AWS / Azure

Full code ownership. Your repo, your infra — zero vendor lock-in.

COMMON CONCERNS

Most common concerns — our ironclad principles.

FAQ

FAQ: production digitalization, IoT systems, MES platforms.

OEE (Overall Equipment Effectiveness)
A key manufacturing metric that measures production efficiency by combining availability, performance, and quality. World-class OEE is typically 85%+.
MES (Manufacturing Execution System)
Software that tracks and documents the transformation of raw materials to finished goods. MES bridges the gap between ERP planning and shop floor operations.
Predictive Maintenance
An AI-driven approach to equipment maintenance that uses sensor data and machine learning to predict failures before they occur, reducing unplanned downtime by 30-50%.
GET STARTED

Ready to digitize your production?

You'll get: systems audit, integration plan, quote. NDA on request. Zero spam.

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