The Platform
Intelligent Infrastructure for
Enterprise AI.
Built for enterprise teams who want to move fast. We've simplified the technical foundations
into one coherent Agentic AI system, supporting rapid prototyping of various use cases,
enabling enterprises to go production quickly.
Architecture
One engine. Every layer.
Prescience.one spans the full AI infrastructure stack as a single, cohesive system —
from data ingestion to production monitoring.
Prescience IDE
Use case definition · data connectors · deployment settings · performance targets
Monitoring Dashboard
Pipeline health · model metrics · cost visibility
API Gateway
REST · gRPC · webhook endpoints
Deployment Orchestrator
Architecture selection · component wiring · pipeline generation · cost optimization
Lifecycle Manager
Deploy · scale · monitor · retire
Compute Fabric
Dynamic resource provisioning · multi-cloud
Data Infrastructure
Warehouses · lakes · streaming
Feature Store
Auto-built · versioned
ML Frameworks
Classical + deep learning
GenAI Services
LLMs · embeddings · RAG
Serving Layer
Real-time + batch inference
AWS
S3 · SageMaker · Bedrock
Google Cloud
GCS · Vertex AI · BigQuery
Microsoft Azure
ADLS · Azure ML · OpenAI
On-Premises
Private cloud · bare metal
Platform Capabilites
Every Layer of AI
Infrastructure, unified
The core primitives that work together to eliminate the infrastructure gap between your team and production AI.
AI Use-Case Builder
An intuitive IDE that lets domain SMEs define AI use cases without engineering overhead. Captures intent, data context, and operational requirements — then hands off to the orchestrator automatically.
- Natural language use case definition
- Visual data source connector
- Performance and cost requirement capture
- Multi-modal data support
Deployment Orchestrator
The intelligent engine that determines optimal end-to-end pipeline architecture. Selects and connects data infrastructure, compute layers, ML frameworks, and GenAI services — automatically.
- Automatic architecture selection
- Hyperscaler and on-prem compatibility
- Cost and performance optimization
- Infrastructure-as-code output
Lifecycle Manager
End-to-end production management for AI applications. Built-in monitoring, auto-scaling, model versioning, and drift detection — so your team maintains visibility and control without custom observability tooling.
- Real-time pipeline health monitoring
- Auto-scaling via Compute Fabric
- Model drift detection and alerting
- Compliance audit trails
Compute Fabric
Prescience's Compute Fabric abstracts cloud infrastructure complexity, automatically provisioning and scaling compute capacity based on use case load — without manual configuration or vendor lock-in.
- Automatic provisioning and teardown
- Multi-cloud resource optimization
- GPU / CPU workload routing
- No vendor lock-in architecture
Your next AI use case
deserves to be Live.
Connect with us to discuss how we can built intelligent, scalable solutions for your organisation.
Our team is ready to collaborate.
The unified AI infrastructure platform for enterprise data and AI teams. From prototype to production — automatically.