Our AI Solutions
Together with our vast ISV ecosystem we deliver secure, scalable, and enterprise-ready AI solutions tailored to your infrastructure—on-premises, cloud, edge, or hybrid. Our AI platform offerings span the full life-cycle from data ingestion and model development to deployment, monitoring, and governance.
Enterprise GenAI Platform
Build and operate generative AI workloads with full control, compliance, and performance insight:
Security-first architecture: Zero-trust, supply-chain certified environments with hardened AI stack and compliance blueprints.
Modular and open: Support for a wide range of LLMs, vector databases, orchestration tools, and frameworks.
Flexible deployment: Deployable on air-gapped, on-prem, hybrid, or multi-cloud infrastructure.
Autonomous agents: Design agentic workflows with tool calling, memory, retrieval, and self-healing logic.
Built-in guardrails: Integrate responsible AI with content filtering, prompt moderation, and output validation.
Operational dashboards: Full observability of GPU usage, token consumption, inference latency, drift, and model health.
AI Life-cycle Management Platform
Accelerate model development and deployment across hybrid environments with a unified AI life-cycle platform:
Integrated pipelines: End-to-end support for data prep, model training, fine-tuning, packaging, and deployment.
Optimised inference: Efficient deployment of large models using transformer-serving engines and sparse inference frameworks.
Any infrastructure: Supports bare metal, virtual machines, Kubernetes clusters, or managed platforms.
Multi-model support: Serve multiple models simultaneously with auto-scaling and GPU-sharing capabilities.
Governance & compliance: Central policy controls, audit logging, and performance bench-marking across environments.
Built-in integrations: Connect with automation platforms for AIOps, observability, policy enforcement, and event-triggered remediation.
Predictive & Generative AI Platform
Deliver predictive insights and generative applications with a flexible AI stack:
AutoML pipelines: Automated feature engineering, model selection, hyperparameter tuning, and interpretability.
LLM integration: Out-of-the-box support for integrating custom, open-source, or API-based large language models.
On-device model support: Deploy lightweight, efficient models for offline or edge use cases.
Data apps & notebooks: Drag-and-drop UI for data prep, modeling, evaluation, and visualization.
Model & App hub: Centralised catalog for reusable models, templates, and AI-powered applications.
Token cost control: Monitor and optimize LLM usage with custom billing metrics and alerting.