Services | Impact Analytics

Impact

Analyze

Core Actions
- Kickstarting your path to AI maturity
- Identify high impact business case
- Deep insights in your infrastructure
Requirements
- Not required
Deliverables
- Advice and documented roadmap
- Insights in the methods for developing, implementing, and deploying machine learning and AI models in a fast and scalable way

Core Actions
- Data gathering from front – to – end
- Machine learning – ready infrastructure
- Algorithmic proof of concept
- Planning for Scaled Implementation
Requirements
- Desire to start AI journey
Deliverables
- Initial modeling results
- Agile project plan

Build

Core Actions
- Structuring your database
- Focus on business users
- Optimization of database environment
- Identifying KPI’s
- Insane Dashboarding

Deliverables
- Innovative IT – infrastructure
- Unique and persistent identifiers
- Actionable BI
- Advice on and knowledge transfer on BI – tooling

Core Actions
- Modeling perfect for Infrastructure
- Modeling beyond requirements
- Data Streaming Pipeline
Requirements
- Time series data (discrete / continuous)
- (Weak) labels
- KPI’s
Deliverables
- Tensorflow / PyTorch model
- Ready – to – Go repository
- Reproducible Jupyter Notebook

Core Actions
- Modeling perfect for Infrastructure
- Modeling beyond requirements
- Data Labeling Pipeline
Requirements
- Image data (discrete / continuous)
- (Weak) labels
- KPI’s
Deliverables
- Tensorflow / PyTorch model
- Ready – to – Go repository
- Reproducible Jupyter Notebook

Deploy

Core Actions
- Selection of the optimal container hosting solution: managed vs unmanaged
- Latest Cloud security implementation
- Reduction of the application cost by decomposing it into separate components (microservices architecture)
Requirements
- Cloud subscription / Willingness to mix on-prem with cloud
Deliverables
- Kubernetes dynamic cluster

Core Actions
- Model profiling
- Optimization of model size
- Optimization of inference speed
- Optimization of performance metrics (Accuracy / F1 – score / FiD etc.. )
- Porting to optimal environment, scaling
Requirements
- Trained model checkpoint / frozen model
- CPU / GPU / TPU (or other Application Specific Integrated Circuit)
Deliverables
- Improved model
- Deep model tests insights
- Advice and knowledge of extension model scope

Core Actions
- Constructing robust CI / CD for machine learning
- Active Learning
- AI Maturity roadmap
Requirements
- Trained machine learning model
- Methods for data preparation, model training and deployment have been defined.
Deliverables
- Decrease of latency
- Scalable horizontally and vertically
- Provides efficient computation with regards to workload management
- Supports batch and real-time processing

We’re Impact Analytics, a data science and machine learning development firm.