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AI & DATA ENGINEERING

AI that delivers. Data that connects.

Connect AI, data and engineering to solve real business challenges.

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WELCOME TO AI THAT DELIVERS

Bring AI into the way your business works

Turn data into operational insight. Combine computer vision, data processing and application integration to bring AI into practical workflows.

From field cameras and sensors to business data, AQPTech connects information sources with applications, alerts and workflows. Each project starts with a specific need and is validated before scaling.

01

Data

Collect · normalize · connect

02

AI

Design · test · evaluate

03

Integration

APIs · events · workflows

04

Operations

Deploy · monitor · improve

OUR AI PORTFOLIO

From data foundations to AI applications

Three connected capabilities across your solution journey.

DATA ENGINEERING

Data foundations

Consistent data ready for analytics and AI.

  • Data collection and normalization
  • Pipelines and data stores
  • API, event and IoT integration
  • Quality checks and access control
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AI ENGINEERING

AI & GenAI engineering

Apply models to specific problems and workflows.

  • Business knowledge assistants with RAG
  • Model integration into applications
  • Output quality evaluation
  • Versioning and operations
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VISION & EDGE AI

Computer vision

Connect field imagery with operational insight.

  • Image and video analytics
  • Object, PPE and zone detection
  • OCR and information extraction
  • Edge processing and alert integration
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OUR DIFFERENTIATORS

Engineering grounded in operational goals

A useful model needs suitable data, clear architecture and a way to bring results into daily work. AQPTech combines software, AI and systems integration in one approach.

Industry understanding

Connect data, technology and workflows with your business’s operational goals.

  • Domain understanding
  • System integration
  • Measure outcomes
  • Risk management
  • Operational improvement
  • Applied innovation
  • Flexible scaling
From understanding to integration, validation and improvement.

Engineered with real data

Assess sources, quality, usage rights and field conditions before choosing technology.

Designed around business workflows

Connect AI to software, devices and people so outputs can be used in day-to-day work.

Validated through a PoC

Agree on a baseline, test data and acceptance criteria. Evaluate quality, latency and cost before scaling.

Flexible from edge to cloud

Consider edge, on-premise or cloud deployment based on connectivity, resources and data control requirements.

Security and oversight by design

Define access, logging, data retention and human review steps for each project.

DISCOVER WHAT’S POSSIBLE

Discover the right AI & data solution

Start with a specific business need.

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OUR OUTCOMES

Outcomes you can validate

Goals and acceptance criteria are agreed for each project. Quality is assessed using representative data and operating conditions.

Usable, connected data

Connect fragmented sources, standardize structures and monitor data quality.

Better-informed workflows

Bring analytics, alerts and knowledge retrieval into working tools.

Applications you can evaluate

Track output quality against agreed data and criteria.

Evidence-based scaling

Use PoC results to decide architecture, resources and the next delivery phase.

INSIGHTS & RESOURCES

Explore AI and data engineering

AI FACTORY · FROM IDEA TO OPERATIONS

Build the foundation for your AI journey

Connect data, models and operations in one roadmap. From selecting use cases and running a PoC to integration and quality monitoring.

Explore AI Factory ↗
Engineers collaborating on system trials
ENGINEERING CONVERSATIONS

Define the challenge before choosing technology

What data is available? Who will use the results? How should systems connect? A technical discussion helps define assumptions, constraints and a suitable trial scope.

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Engineering team discussing a system
DELIVERY SPOTLIGHT

From discovery to delivery

01

Discover & design

Assess data and infrastructure; agree on scope, architecture and success criteria.

02

Prototype & evaluate

Test with representative data, measure quality and refine the approach.

03

Integrate & operate

Connect systems, hand over and monitor according to project requirements.

Frequently asked questions about AI

Which problems can AI help with?

Applications include video analytics, object detection, OCR, knowledge retrieval and data processing assistance. Scope is determined after reviewing data and workflows.

How do we start if data is not ready?

Start by assessing data sources and quality, then identify collection, cleaning, normalization or labeling work needed before model trials.

Can AI connect to our existing systems?

AQPTech reviews APIs, databases, device protocols and security requirements to propose a suitable integration approach.

How is a PoC evaluated?

Criteria depend on the use case: output quality, latency, task success, cost and human review needs. Results are compared with a baseline.

Does data have to go to the cloud?

Edge, on-premise, cloud and hybrid architectures can be considered. The choice depends on data requirements, infrastructure and budget.

How do we begin a project?

Share your challenge, existing systems and goals through the form. We clarify discovery scope, a PoC and evaluation criteria together before delivery.

LET’S TURN DATA INTO VALUE

Talk to our AI experts today

Share your requirements and let’s define the next step.

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AQPTech · GROW WITH US

Supercharge your career with us

At AQPTech, we connect people, technology and real-world challenges. Learn together, grow your skills and build solutions that create value for businesses.

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AQPTech

Powering Decisions

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