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Data Analytics & AI/ML Implementation

Turn intelligence into Innovation, with AaensaTech

Artificial intelligence and machine learning are not just tools at AaensaTech; they are the imaginative centrepiece that will turn products into something intuitive, predictive and thought-provoking. We unite data science, embedded intelligence, and scalable cloud models to develop solutions that are smart, evolve over the years, and bring quantifiable business value. Our AI/ML services enable you to unlock new value, whether you are creating a connected device, an industrial system or a consumer application and as you do this, you have maintained robustness, security and compliance.

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360°

End-to-End Solutions

100%

Security Compliant

2-6X

Faster Deployment

24/7

Support & Maintenance

Why Choose AaensaTech?

Your AI/ML Development Partner

Layered Intelligence Integration

We integrate AI/ML across every aspect of your product, embedded devices, cloud, and edge, in order to ensure that intelligence is not an afterthought, but a part of the product designed to suit each environment.

Business + Data Science + Engineering Synergy

We are a multi-disciplinary group comprising data scientists, software engineers, embedded systems specialists and UI/UX designers. This will make your AI models accurate, deployable, usable and efficient.

Scalable & Responsible AI

● We scale: graph inference, cloud training, hybrid deployments.
● Our AI practices are ethical: data governance, explainability, detection of bias, and security.
● We are in agreement with the regulatory provisions like GDPR, HIPAA, and their domain standards.

Quick Product Development and Testing

Agile development cycles allow us to quickly prototype ML models, confirm them with real data, and provide feedback, which removes risk and fastens time to market.

Long-Term Intelligence Retention

AI is not "build once." Our beliefs include regular retraining of models, monitoring of models, identifying drift, as well as model governance throughout the product lifecycle.

Our Process

Our Data Analytics & AI / ML Process

Discovery & Data Strategy

● Know your business objectives, end-user issues and data sources.
● Evaluate the data preparedness, data quality, volume and gaps.
● Establish data management, privacy, and ethics.

Design Ideation & Architecture

● Research appropriate modelling strategies (supervised, unsupervised, reinforcement)
● Architecture, end-to-end design: ingestion, training, deployment of data.
● Create pipeline prototype models and specification of evaluation measures.

Model Training & Validation

● Prepare, label, and clean datasets.
● The baseline and advanced models of trains are developed with modern ML frameworks.
● Authenticate accuracy, robustness, equity, elucidativeness, and performance.

Edge / Cloud Deployment

● Execute models with low resources on edge devices (microcontrollers, gateways)
● Use large-scale cloud training and inference pipes.
● Apply continuous integration / continuous deployment (CI/CD) to models.

Security & Quality Assurance

● Check the performance of models, identify concept drift and data drift.
● Automatizing retraining pipes.
● Offer transparency, audit logs and explainability dashboards.

Launch & Post-Launch

● Integrate intelligence into the consumer experience: personalisation, automation, predictive alerts.
● UI Design UX to display AI insights in an understandable and human-friendly manner.
● Check the user processes and interface with actual users.

Technologies and Frameworks

We Use

Data science and ML

Python (NumPy, pandas) scikit-learn TensorFlow PyTorch XGBoost

Data Engineering

Apache Spark Kafka Hadoop Data Lakes ETL Pipelines

Model Deployment

TensorFlow Lite ONNX Edge TPU Docker Kubernetes

Infrastructure

AWS SageMaker Google AI Platform Azure ML Serverless Compute

Monitoring & Governance

MLflow Kubeflow Prometheus Grafana SHAP LIME

Security & Privacy

Differential Privacy Federated Learning Model Encryption

Industries

Sectors Empowered by AI / ML

Healthcare / MedTech

Prognostic diagnostics, patient risk assessment, treatment recommendations

Consumer Electronics

Intelligent assistants, recommendation systems, and responsive interfaces.

Industrial / Manufacturing

Predictive maintenance, anomaly detection, process optimisation.

Energy / Sustainability

Predicting energy, predicting load on the grid, optimisation of resources

FAQ

Frequently Asked Questions

1. What type of data must I begin working with AI/ML? +

You must have high-quality and relevant historical data. Nevertheless, despite the small data, we can assist in data strategy, synthetic data generation, and incremental model construction.

2. What is the average duration of an AI/ML project? +

According to the complexity and maturity of the data, a pilot model will require 8-12 weeks; a fully production-scale model can require 4-6 months or longer.

3. Is it able to deploy models on devices that have very limited resources (edge)? +

Yes, our edge inference software is our edge to run models on microcontrollers or gateways without performance loss.

4. Does AaensaTech ensure that my AI model is explainable and fair? +

We apply explainability software (such as SHAP/LIME), bias identification methods, and model governance frameworks as a way of promoting transparency, fairness, and trust.

5. Would I be able to have the ownership of the trained models and data? +

Yes, you can keep all your data, data sets, model architecture, and trained models. We offer documentation and codebase as well.

6. What are your security and privacy of sensitive data? +

We use strong data governance and encryption, anonymisation, and access control, and, when necessary, such methods as federated learning or differential privacy.

Are You Ready to Turn Data into Intelligent Products?

Collaborate with AaensaTech and get your devices and systems full of predictive ability, intelligent automation, and insights into actionable data.

Get started on Data Analytics & AI / ML today!

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