The platform that powers every PANITH solution
Built once, scaled everywhere
The same secure data spine, cloud-native services and open interfaces run across COST & REVENUE INTELLIGENCE, PREDICTIVE MAINTENANCE, DEMAND FORECASTING, QUALITY & VISION ANALYTICS, PROCESS AUTOMATION & OPTIMIZATION and RISK & COMPLIANCE ANALYTICS. One platform means faster roll-outs, lower support cost and a single source of truth from edge sensor to executive dashboard.
Reference architecture
Data spine
A governed lakehouse on your AWS, Azure or GCP tenant ingests batch and streaming data through ELT pipelines. Kafka handles high-velocity feeds. Iceberg keeps historical and real-time data in one format for analytics and machine learning.
Compute layer
Containerised microservices run on Kubernetes with auto-scaling for peak loads. Serverless functions cover bursty jobs such as overnight model scoring or ad-hoc report generation.
AI and ML services
A feature store, model registry and automated retraining pipelines deliver repeatable machine learning. Models are tracked, versioned and promoted through dev, test and prod with MLOps best practice.
Application layer
GraphQL and REST APIs expose data, predictions and optimisation results to any downstream system. Event webhooks push changes instantly to ERP, MES or mobile apps.
Experience layer
Front-end applications use React, TypeScript and Tailwind CSS for fast, accessible interfaces. Role-based access gives every user the right view, from line operator to CFO.
Security and privacy by design
- Encryption in transit and at rest with AES-256 and TLS 1.3
- Zero-trust networking with micro-segmentation
- Hardware security modules for key storage
- Multi-factor authentication and single sign-on with SAML or OIDC
- Continuous penetration testing and 24×7 monitoring
Open and interoperable
All services publish OpenAPI specifications. SDKs in Python, JavaScript and Java speed up custom integrations. Data export to Parquet, CSV and JSON keeps you in control.
Explainable and responsible AI
SHAP values, bias metrics and model cards ship with every model. Audit logs record who trained, approved and deployed each version.
Toolchain
- Apache Spark, Python and SQL for analytics
- TensorFlow, PyTorch and XGBoost for modelling
- Go and Rust for low-latency services
- GitHub Actions, Terraform and Helm for CI-CD
- Prometheus, Grafana and OpenTelemetry for observability
Sustainable engineering
Model compression, GPU utilisation tuning and policy-based workload placement minimise carbon footprint. Compute regions are selected for renewable energy where available.
Compliance ready
Architected to meet ISO 27001, SOC 2, GDPR, CCPA, UK DPA, PIPEDA and India DPDP 2024. Mapping tables help your auditors trace each control.
Delivery methodology
- Thin-slice proof in two weeks to validate data flow and security
- Six-week pilot for first value in one business unit
- Eight to twelve week scale-out across sites or regions
- Quarterly value realisation and roadmap sessions
What this means for you
- Faster time to value with reusable components
- Lower total cost through shared services
- Future-proof integrations with open standards
- Confidence that data, models and users are protected
See how PANITH technology can accelerate your own roadmap.
Contact us to arrange a technical deep dive with our architecture team.