AI Data Platform &
MLOps Infrastructure
RDP is building India’s sovereign AI Data Platform & MLOps infrastructure — GPU-accelerated data engineering, feature stores, experiment tracking, model registry, and CI/CD pipelines for production AI lifecycle management. The complete.
Why AI Data Platform & MLOps Infrastructure, Why Now
India’s enterprises and research institutions are building AI models, but most lack the data infrastructure to operationalise them. Data teams spend 80% of their time on.
Target Segments
Enterprise AI Teams
Data engineering, feature stores, and MLOps for banks, insurers, telecom, and.
AI Startups
Scalable data platform and CI/CD pipelines for rapid AI product development and iteration
Research Institutions
Experiment management, dataset versioning, and reproducible research pipelines for.
Government AI Programmes
Sovereign data platforms for national AI initiatives, digital government, and smart city.
AI Consulting & Services
Reusable MLOps templates and data platforms for multi-client AI project delivery
AI Startups & Industry R&D
Private sector R&D labs, AI product companies, deep-tech startups
Full Stack Architecture
Three integrated layers — hardware, software, and AI — purpose-built for research at institutional, state, and national scale.
INTELLIGENCE — MLOps & AI Lifecycle
Experiment Tracking · Model Registry · CI/CD Pipeline · Monitoring · Feature Store
SOFTWARE — AI Data Platform
Lakehouse · ETL Engine · Feature Store · Notebook Hub · Orchestrator · Governance
HARDWARE — RDP Proprietary Infrastructure
AI-POD · Data GPU Server · Lakehouse Storage · Lossless Fabric · HA Cluster
RDP Proprietary Infrastructure
| Component | RDP SKU | Data Platform Role | Key Specification |
|---|---|---|---|
| Compute Node | RDP AI-POD (Rack Scale) | GPU-accelerated data processing, feature computation, and model training | 8× GPU per node, NVLink |
| Data Server | RDP Data AI SKU | ETL processing, feature engineering, and batch inference workloads | A100 / L40S, high memory |
| Lakehouse Storage | RDP NVMe All-Flash Array | Unified lakehouse — structured, semi-structured, and unstructured data | Up to 1 PB, 20 GB/s |
| Network Fabric | RDP Lossless Fabric | High-bandwidth interconnect for data-intensive pipelines | 100GbE / 400GbE |
| Archive Storage | RDP Object Store | Long-term dataset archive, model artifact storage, and compliance | 10+ PB, S3-compatible |
AI Data Platform
Apache Spark / Dask
GPU-accelerated distributed data processing and feature engineering
Delta Lake / Apache Iceberg
Open lakehouse format for unified batch and streaming data management
Feast / Hopsworks
Feature store for online/offline feature serving and management
Apache Airflow / Prefect
Workflow orchestration for data pipelines and model training schedules
JupyterHub / VS Code Server
Interactive development environments for data scientists and ML engineers
Apache Ranger / Atlas
Data governance, access control, lineage tracking, and audit trail
GPU Data Engineering
NVIDIA RAPIDS-accelerated ETL, joins, aggregations, and feature computation
Feature Store Platform
Centralised feature management with online/offline serving and feature versioning
Experiment Tracking
MLflow/W&B-integrated experiment logging, comparison, and reproducibility
Model Registry & CI/CD
Versioned model registry with automated testing, validation, and deployment pipelines
Data Quality AI
Automated data validation, drift detection, and quality scoring for pipeline reliability
Model Monitoring
Production model performance tracking, drift detection, and automated retraining triggers
Pre-Validated AI Models
| MLOps Domain | Model Type | Application | Performance |
|---|---|---|---|
| Data Engineering | RAPIDS + Spark | GPU-accelerated ETL processing 10× faster than CPU-only Spark | 10× ETL speedup |
| Feature Store | Feast + Redis | Online/offline feature serving with sub-ms latency for real-time models | <1ms online serving |
| Experiment Tracking | MLflow + W&B | Experiment logging, hyperparameter tracking, and model comparison | 100% reproducibility |
| Model Registry | MLflow + Git | Versioned model storage with staging, production, and archive lifecycle | Automated CI/CD |
| Model Monitoring | Evidently + Prometheus | Drift detection, performance tracking, and automated retraining triggers | Real-time drift alerts |
| Data Governance | Ranger + Atlas | Access control, data lineage, PII detection, and compliance audit trail | DPDP Act compliant |
Deployment Configurations
Three pre-validated tiers — each with hardware, software, AI models, and RDP SLA support. Custom BOQ on request.
Starter
Single AI Team / Startup
Professional
Multi-Team Enterprise
Enterprise
Platform / National Scale
End-to-End on Sovereign Infrastructure
Complete pipeline from data ingestion to actionable intelligence — every step on RDP infrastructure.
INGEST
& FEATURE
EXPERIMENT
& REGISTER
SERVE
& RETRAIN
Build With Us · Sell With Us
RDP’s Research AI platform is designed for India’s ecosystem. We’re inviting technology and channel partners, and direct inquiries from organisations.
Technology Partners
- Certify your platform tools on RDP GPU infrastructure
- Access test environments for integration validation
- Joint go-to-market with RDP AI team
- Co-branded solution briefs for enterprise procurement
- Lakehouse / feature store integration support
Channel Partners
- Sell complete AI data platform solutions
- Pre-configured MLOps deployment packages
- RDP-backed implementation & SLA support
- Partner margins on hardware + software
- Data platform training & certification
AI Teams & Organisations
- Schedule a data platform workshop
- Request a proof-of-concept deployment
- Get a custom Bill of Quantities
- Evaluate starter tier with your data
- GeM / enterprise procurement support
India’s Sovereign Research AI Infrastructure
Make in India Hardware
All RDP systems designed and assembled in India. GeM-listed for institutional procurement.
Research Data Sovereign
Research data, model weights, and IP stay on Indian institutional infrastructure. Zero export.
NVIDIA Certified Stack
DGX-Ready validated, CUDA optimised, and certified for HPC and AI research workloads.
DST / MeitY Aligned
National science and technology mission aligned. Eligible for research infrastructure funding.
5-Year Lifecycle Commitment
Hardware support, HPC engineering, and continuous performance optimisation throughout lifecycle.
Full Stack — Single OEM
Servers, storage, networking, software, and AI from one Indian OEM. One BOQ, one SLA.
Regulatory Alignment
| Standard | Scope | RDP Coverage |
|---|---|---|
| DPDP Act 2023 | Data Protection | On-premise data processing — consent management, PII detection, data minimisation |
| IT Act | Information Technology | Compliant data platform for Indian IT regulatory requirements |
| ISO 27001 | Information Security | RDP infrastructure ISO 27001 certified |
| SOC 2 Ready | Security Controls | Infrastructure supports SOC 2 Type II audit for data platform operations |
| GFR / GeM | Government Procurement | GeM-listed for government and institutional procurement |
| Apache License | Open Source | Core platform built on Apache-licensed open-source software — zero vendor lock-in |
Projected Impact
| Metric | Before RDP AI | After RDP AI | Impact |
|---|---|---|---|
| Data pipeline speed | Hours (CPU Spark) | Minutes (GPU RAPIDS) | 10× faster |
| Model to production | 3–6 months | 2–4 weeks | 5× faster |
| Experiment tracking | Manual, spreadsheets | Automated MLflow | 100% reproducible |
| Model failures | Detected by users | Auto-detected, retrained | Proactive quality |
| Data governance | Manual, reactive | Automated lineage + audit | DPDP compliant |
| Data sovereignty | Cloud vendor risk | 100% on-premise | Zero exposure |
Ready to Build Research AI Capability?
From pilot to production — RDP designs, builds, and deploys sovereign AI infrastructure for India’s research ecosystem.
Trademark Notice: All product names, logos, and brands mentioned are property of their respective owners. NVIDIA, CUDA, L40S, A100, H100, H200 are trademarks of NVIDIA Corporation. Use is for identification only.
Disclaimer: RDP Technologies provides AI compute infrastructure. Research outcomes, model performance, and scientific conclusions are the responsibility of the deploying research organisation.
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