UNIFIED DATA-TECH SOLUTIONS READIES SECURE, SCALABLE ENTERPRISE AI FOR 2026

PRANAV PARIKH
CTO, Unified Data-Tech Solutions Ltd.

Unified Data-Tech Solutions is progressively capable of delivering enterprise-scale AI from pilots to production, thanks to our mature partnerships with major infrastructure and cloud providers. Access to GPU-accelerated compute, container platforms, cloud-native AI services, and zero-trust security platforms helps us deliver scalable compute, modernized data platforms, and secure production environments. While skills gaps, poor data foundations, and infrastructure remain significant barriers, embedding risk controls and security against data privacy threats and specialized attacks—such as manipulating inputs, model theft, and others—remains the top blocker for responsible and trustworthy AI deployments.

The rise of AI has introduced sophisticated threats, including deepfakes, AI-generated illegitimate business documents, and unauthorized model access and exfiltration. Traditional security measures alone are insufficient. Our partnerships with MSSPs and leading security vendors provide 24/7 threat monitoring, alerting, and rapid response, with integrated behavioral analysis and anomaly detection to mitigate AI-based fraud, automated impersonation, and contextual spoofing. Identity and Access Management, Multi-Factor Authentication, device-bound cryptographic passkeys, and Data Loss Prevention ensure only authorized developers and data scientists access sensitive AI environments, safeguarding confidential training data, including PII.

Cloud-native and hybrid architectures are both enablers and transformative in shaping our AI roadmap. Cloud-native environments enable rapid experimentation, elastic scaling, and dynamic GPU/TPU provisioning for model training and GenAI innovation, while hybrid setups retain sensitive data on-premises to meet regulatory obligations. Aligned with Digital India and IndiaAI initiatives, our solutions enhance secure digital interactions, offer passkey-based authentication, and add intelligent human-authenticity and fraud-detection layers, protecting regulated institutions from AI-driven threats while advancing scalable, indigenous AI technologies.