IBM has announced its new quantum processor, dubbed Nighthawk, designed to achieve quantum advantage as early as next year. This marks a pivotal moment in quantum technology, with implications spanning industries from finance and supply chain to materials science and cryptography.
Architectural Highlights & Technical Innovation
120-Qubit Square Lattice Architecture:
Nighthawk introduces a highly structured 120-qubit lattice, with each qubit connected to four nearest neighbours, boosting interaction density and accelerating complex circuit execution.
With a ~20% increase in connectivity over IBM’s Heron processor, Nighthawk supports deeper entanglement pathways and more reliable multi-qubit operations.
Rapidly Scaling Gate Capacity:
~5,000 two-qubit gates supported today
7,500 by end of 2026
10,000 by 2027
Up to 15,000-gate programs across 1,000+ connected qubits by 2028 This roadmap represents one of the most aggressive scalability trajectories in the industry.
Next-Gen Software Stack for Real Workloads:
A powerful C++ quantum programming interface designed for seamless integration with HPC environments
Expanding ML and optimisation libraries to unlock new scientific and commercial use cases
A Quantum Advantage Tracker, built with research partners, to rigorously validate emerging quantum benchmarks in real time
300 mm Quantum-Ready Fabrication Facility:
IBM’s new large-scale wafer facility adopts semiconductor-grade tooling to industrialise quantum hardware manufacturing—improving consistency, yields and delivery at scale.
Why It Matters for Enterprise & Industry
Quantum advantage means a quantum system solving a meaningful problem faster or more effectively than any classical counterpart. IBM’s roadmap projects this milestone as attainable before 2026. For enterprises, this opens prospects for tackling previously intractable problems, large-scale optimisation, molecular simulations, cryptographic legacy systems and AI model acceleration.
Yet the path remains nuanced: fault-tolerant quantum computing remains a significant challenge. IBM aims to deliver large-scale fault-tolerant systems by 2029. Technologies like error-correcting processors and long-range couplers are critical here.
Enterprises already adopting quantum-ready strategies will gain a strategic advantage: preparing algorithms, integrating quantum-software workflows, evaluating hybrid quantum-classical solutions and building a talent base today.
How Prolifics Can Guide You Through This Quantum Leap
As organisations across sectors prepare for quantum disruption, Prolifics stands at the forefront of enabling transformation. Whether you’re a global financial services firm looking to optimise trading or risk models, a manufacturer simulating novel materials, a supply-chain leader tackling complex routing, or a utility company modelling grids for renewable integration, Prolifics brings deep expertise in AI/ML, cloud, DevSecOps and now quantum-ready architectures.
We help you:
Assess your quantum readiness: identify high-value use-cases and hybrid quantum-classical trajectories.
Build quantum-friendly infrastructure and integration pathways into existing systems.
Train your teams on quantum software frameworks and programme design.
Design proof-of-concept quantum experiments aligned to your business goals.
Partner with Prolifics and begin your quantum strategy today. Reach out to discuss how your enterprise can leverage Nighthawk-era advances and position itself ahead of the quantum curve.
Contact Prolifics now to start the quantum journey.
Data privacy in healthcare is essential to safeguarding highly sensitive patient information. Ensuring compliance with regulations such as HIPAA and GDPR in Healthcare, and regional data protection laws is critical for maintaining patient trust, protecting confidentiality, and supporting responsible healthcare delivery.
For healthcare providers, insurers, technology partners, and software vendors, healthcare data privacy compliance goes far beyond ticking regulatory boxes. It’s about earning patient trust, protecting organizational reputation, and enabling innovation in a secure, compliant environment.
At Prolifics, we believe that comprehensive data privacy and governance should be viewed as foundational to delivering high-quality, future-ready healthcare services. This guide outlines key regulatory frameworks, best practices, and how Prolifics helps organizations turn compliance into a competitive advantage.
Types of Healthcare Data
Healthcare organizations manage a wide array of sensitive data, including:
Protected Health Information (PHI) – Personal identifiers, medical histories, lab results.
Electronic Health Records (EHRs) – Comprehensive patient care documentation.
Genomic and Research Data – Highly sensitive data requiring strict access control.
Wearable Device Data – Continuous monitoring information such as heart rate, glucose levels, and activity metrics.
Telehealth Communications – Video consultations, messages, and remote monitoring data.
Why Data Privacy Matters in Healthcare
Healthcare data is among the most sensitive categories of personal information, including physical or mental health conditions, treatments, insurance details, biometric data, and more. Mishandling such data can lead to identity theft, medical fraud, regulatory penalties, and irreversible reputational damage for providers.
Further, patients and regulators increasingly expect transparency, control, and accountability over how personal data is collected, stored, processed, and shared. Privacy isn’t just compliance, it’s ethics, patient trust, and business sustainability. Patient data privacy healthcare practices are becoming a top priority for modern healthcare organizations.
Key Regulatory Frameworks: HIPAA & GDPR
HIPAA
HIPAA defines standards for protecting Protected Health Information (PHI), whether electronic or otherwise. Covered entities – healthcare providers, insurers, and business associates, must implement robust administrative, technical, and physical safeguards to ensure confidentiality, integrity, and availability of PHI.
A robust data governance approach under HIPAA involves policies and procedures that manage data classification, access control, data lifecycle (retention/disposal), audit logging, breach detection/response, and ensure PHI is only accessible to authorized entities, this aligns with HIPAA compliance best practices.
GDPR
GDPR applies when health data of individuals covered under the regulation (e.g. EU citizens) is processed, regardless of where the organization is based. Under GDPR, “data concerning health” is classified as a “special category” requiring higher protection standards.
Key GDPR requirements: obtaining explicit, informed consent for processing; ensuring transparency and purpose limitation; enabling patient rights like data access, erasure (“right to be forgotten”), portability, and restriction of processing
Strict rules govern data transfer, especially cross-border transfers. Healthcare organizations need to ensure adequate safeguards during any data sharing or movement across jurisdictions. This is part of GDPR healthcare regulations.
HIPAA + GDPR: Working Together
Many organizations, especially global healthcare providers or vendors servicing international clients, need to comply with both HIPAA and GDPR in Healthcare. While both focus on protecting personal health data, their emphases differ: HIPAA centers on PHI security and breach prevention; GDPR centers on privacy rights and consent.
This overlap can be challenging – but also presents an opportunity: by aligning governance frameworks to meet both, organizations can build a stronger, future-proof privacy foundation.
Best Practices for Data Privacy & Governance in Healthcare
Building compliance is not a one-time effort, it requires a robust data governance program that permeates people, processes, and technology. Here are some widely accepted best practices:
1. Establish a Clear Data Governance Structure
Form a multidisciplinary data-governance committee composed of stakeholders from IT, clinical operations, compliance, legal, and data management teams. This committee defines policies, oversees compliance, and ensures accountability across the organization.
Define data ownership, stewardship, and decision rights clearly. Roles should include data custodians, privacy officers, and compliance stewards to manage PHI across systems responsibly. Implementing data governance strategies for healthcare providers ensures stronger compliance outcomes.
2. Classify & Inventory Data
Not all data is equal. Begin with comprehensive data classification and inventory, distinguish PHI, sensitive personal data, metadata, and general administrative data. This clarifies what must be strictly secured, who can access it, and under what conditions. Establish how long data is retained and define disposal/archival rules to avoid indefinite storage of sensitive data beyond its purpose.
3. Implement Strong Access Controls and Encryption
Enforce role-based access control (RBAC), multi-factor authentication (MFA), and least-privilege access for systems handling PHI. Ensure that data, both at rest and in transit, is encrypted using modern cryptography.
Ensure audit logging: track who accessed what data, when, and what actions were taken. This supports accountability, compliance audits, and forensic analysis in case of incidents.
4.Consent Management & Patient Rights (for GDPR compliance)
For patients under GDPR scope: implement mechanisms to capture explicit, informed consent; log consent versions with timestamps; provide options for patients to withdraw consent.
Facilitate patient requests for access, rectification, erasure, or portability of their data. Build workflows to respond within regulatory timeframes (e.g., typically one month under GDPR). Following how to comply with HIPAA and GDPR in healthcare ensures organizations meet regulatory requirements.
Deploy systems for continuous security monitoring and anomaly detection: monitor data access patterns, generate alerts for unauthorized access, and track unusual behavior.
Regularly conduct compliance audits, vulnerability assessments, and penetration testing. Also, maintain an incident response plan, with breach detection, containment, notification (to individuals and regulators), remediation, and post-mortem reviews.
6. Data Minimization, Masking & Pseudonymization
Adopt data minimization: collect and store only what is strictly required for stated purposes; avoid hoarding unnecessary data.
Use techniques like pseudonymization or anonymization wherever possible, especially for data used in research, analytics, or shared across third parties. This reduces risk without impairing usefulness for non-personal data insights.
7. Documentation, Policies & Training
Develop and maintain comprehensive documentation: data handling policies, access control policies, data retention/disposal policies, breach-response protocols, audit logs, consent logs, and data-sharing agreements.
Train staff, clinicians, IT teams, admin staff, on data privacy, security hygiene, consent handling, and compliance obligations. Privacy must be part of organizational culture, not just a compliance checkbox. Best practices for healthcare data privacy and security should be embedded in every workflow.
8.Use of Compliance-Oriented Tools & Automation
Given complexity of HIPAA and GDPR requirements, especially in organizations operating across geographies , compliance tools offer critical support. Key features to look for: data mapping, automated compliance reporting, real-time risk detection, secure storage, identity & access management, audit logs, and integration with existing IT/cloud infrastructure.
Automation not only reduces manual workload, but ensures consistency, reduces risk of human error, and helps prepare for audits or regulatory scrutiny.
Common Challenges — and How to Overcome Them
Complexity of overlapping regulations: Organizations operating globally may need to satisfy both HIPAA (U.S.) and GDPR (EU) standards. Without a unified governance strategy, compliance efforts can become fragmented or contradictory.
Scattered data across multiple systems: EHR systems, lab systems, billing, cloud storage, third-party vendors, patient data often resides in multiple silos, increasing risk and complicating management.
Evolving regulatory and technological landscape: As healthcare delivery becomes more digital and global, regulations may evolve; security threats grow more sophisticated. Compliance must therefore be proactive and adaptive, not static.
Balancing data utility and privacy: Healthcare organizations want to leverage data for analytics, research, and patient care improvements, but must do so without compromising privacy. That balance requires thoughtful governance, anonymization/pseudonymization, and proper consent management.
How Prolifics Helps – Our Approach
At Prolifics, we combine deep domain expertise in healthcare, strong data governance frameworks, and state-of-the-art security practices to deliver end-to-end data privacy solutions tailored to each organization’s needs. Here’s how we partner with you:
1. Comprehensive Privacy & Governance Assessment
We begin with a full audit of your data estate: where PHI resides, who accesses it, current security posture, compliance gaps (HIPAA, GDPR, cross-border requirements), and governance maturity.
2.Policy & Process Design
Based on audit findings, we help you define and implement robust privacy policies, data classification, access control, consent workflows, data retention/disposal, breach response, auditing and logging, and staff training programs.
3. Technology & Compliance Automation
Leveraging best-in-class compliance frameworks and tools, we implement identity & access management (RBAC, MFA), encryption, pseudonymization/anonymization strategies, and integrate compliance automation, making audit readiness continuous, not periodic.
4.Hybrid & Multi-Cloud Compliance Enablement
For organizations operating across geographies and cloud platforms, we build governance frameworks that span hybrid setups, cloud infrastructure, and on-premise systems, ensuring consistent compliance, no matter where data lives.
5. Data Governance for Analytics, AI & Innovation
We support proper anonymization/pseudonymization and consent-based data usage, enabling analytics, AI, and research to proceed without compromising compliance or privacy.
With ongoing security monitoring, user-behavior analytics, access logging, and incident response plans, we help you stay ahead of threats and meet regulatory requirements.
7.Training, Awareness & Culture Building
We run training programs for clinical, administrative, and IT teams, making privacy an integral part of your organizational culture, not just a checklist.
Partner with Prolifics for Data Privacy Excellence
At Prolifics, we don’t just help you meet regulatory requirements , we help you build a privacy-first culture that supports operational excellence, patient trust, and innovation.
Whether you are a healthcare provider, insurer, technology vendor, or a global enterprise offering digital health services, our tailored privacy and compliance solutions will:
assess and map your data estate,
design governance frameworks,
implement robust security controls,
enable compliance automation,
and support ongoing monitoring, auditing, and compliance readiness.
Digital excellence isn’t optional in today’s financial landscape, it’s the standard. When one of the largest U.S. financial institutions needed to modernize more than 110 mission-critical internal applications, they partnered with Prolifics to turn years of tech debt, fragmented workflows, and compliance challenges into a scalable, secure, and future-ready ecosystem.
The Client: A Top U.S. Financial Institution Ready for Change
This institution serves millions of customers through extensive retail, commercial, and investment banking operations. But behind the scenes, over 110 internal applications were built on outdated platforms, including:
Microsoft Access
Visual Basic (VB)
Excel VBA
ASP
Lotus Notes
These legacy systems had become: ❌ Costly to maintain ❌ Difficult to update ❌ Misaligned with IT & security standards ❌ Bottlenecks to compliance and release management ❌ Barriers to innovation and business agility
The Challenge: Outdated Applications, Growing Operational Risk
The bank’s critical systems were creating:
Release management delays
Compliance inconsistencies
Integration issues with modern platforms
Rising maintenance costs
Increased operational risk
Limited scalability
Our Proven Approach to Modernization
1. Comprehensive Assessment
We evaluated 110+ applications across functionality, compliance, cost, and integration readiness.
2. Strategic Modernization Roadmap
Leveraged the DMAIC framework to define the right modernization path, modernize, consolidate, or retire.
3. Prioritization & Rationalization
Identified redundancies, consolidated applications, and optimized maintenance overhead.
4. Agile Execution at Scale
A 25+ member cross-functional Dev+QA team delivered iterative modernization with continuous compliance checks.
The Prolifics Solution: Modern, Secure, Scalable
✔ Migration Roadmap for 90+ Applications
A phased, efficient, and risk-controlled modernization plan.
✔ .NET Modernization Framework
Selected for scalability, maintainability, and enterprise alignment.
✔ Security & Compliance-Driven Development
Every application validated against internal SOA, audit, and security standards.
✔ DevOps Automation
Modern pipelines enabled faster, error-free, and repeatable releases.
✔ High-Quality Engineering & Testing
Dedicated QA ensured performance, data integrity, and seamless user adoption.
✔ Governance & Knowledge Transfer
Ensuring long-term independence, sustainability, and operational excellence.
The Results: A Modern Banking Backbone
The bank’s leadership reported measurable, business-driven outcomes:
⬆ Improved Compliance
All applications aligned with enterprise IT, security, and SOA standards.
⬆ Faster Release Cycles
Automated pipelines and standardized releases accelerated time-to-market.
⬇ Reduced Risk & Costs
Legacy systems were consolidated and modernized, cutting maintenance overhead.
⬆ Enhanced Agility
A future-ready platform capable of supporting innovation, automation, and evolving regulatory needs.
See how we helped them streamline operations, reduce risk, and accelerate innovation.
Get the complete story, including the challenges, strategy, execution model, and transformational results
In 2026, as enterprises accelerate deployments of generative AI (GenAI) models and large language models (LLMs), managing security, compliance, cost, and reliability becomes a paramount challenge. That is where Databricks AI Gateway stakes its claim, offering a unified, enterprise-grade control plane to govern, observe, and scale AI usage across the organization.
What is Databricks AI Gateway?
Databricks AI Gateway, also known as Mosaic AI Gateway, provides a central API-based entry point for all AI model interactions, whether they involve foundation models, open-source LLMs, custom models, or AI agents. With a single unified API for AI models, development teams no longer need to manage multiple endpoints or build bespoke integrations for each provider.
This unified access simplifies the adoption of new LLMs such as GPT-5 or the migration across providers. It enables model switchovers, experimentation, or fallback strategies without refactoring application logic.
Core Capabilities That Matter
1. Unified model access across providers: Whether the AI model is from OpenAI, Meta, an open-source ecosystem, or a custom internal build, AI Gateway routes all calls through a consistent interface, reducing integration complexity.
2. Governance, security, and compliance: Built-in guardrails allow organizations to enforce policies such as filtering PII, blocking unsafe content, applying role-based access, defining permissions, and setting rate limits, supporting enterprise AI governance at scale.
3. Observability and monitoring: Every request and response, along with metadata such as token usage, model version, and identity information, is logged into the lakehouse via inference tables. Teams can audit, debug, evaluate model quality, analyze cost, and produce compliance reports using native platform tools, strengthening GenAI observability and monitoring across applications.
4. Production-grade reliability and traffic management: AI Gateway supports load balancing, provider fallback logic, and dynamic AI model traffic management across multiple LLMs. Applications stay online even if a provider experiences downtime or rate limiting.
5. Cost and usage control: Centralized tracking of AI usage across all models, teams, and applications enables better financial discipline and simplifies budgeting and chargeback models.
Why It Matters for Partners and Customers
For enterprises and service providers aiming to embed GenAI at scale, AI Gateway addresses critical challenges such as fragmentation, risk management, governance, scalability, and cost unpredictability.
• Faster time to value: With a unified API, partners can integrate GenAI features into applications faster, without building custom connectors for each model.
• Safe and compliant AI adoption: Guardrails and audit trails support regulatory, privacy, and internal compliance needs especially important for industries that require strong enterprise AI governance.
• Scalable operations: Central monitoring and governance ensure policy consistency as AI usage expands across teams and geographies.
• Flexibility and future readiness: The ability to switch between proprietary models, open-source models, and custom-trained models ensures organizations avoid vendor lock-in.
Use Cases: Where AI Gateway Excels
• Enterprise-wide GenAI rollouts across marketing, analytics, R&D, operations, and customer support. • Embedding GenAI into commercial products such as chatbots, code assistants, and summarization tools. • Regulated industries that require strict governance, audit logs, and PII controls. • A/B testing and model optimization across multiple LLMs using dynamic routing and AI model traffic management.
Conclusion: AI Gateway as a Strategic Enabler
With Databricks AI Gateway, organizations finally have a secure, scalable, and resilient foundation for rolling out GenAI without integration challenges, compliance risks, or cost overruns.
For partners such as system integrators and consulting firms, including Prolifics, AI Gateway creates an opportunity to build enterprise-grade GenAI solutions backed by governance, observability, and operational excellence.
As GenAI adoption accelerates, integrating Databricks AI Gateway into your architecture becomes a strategic decision that ensures reliability, compliance, and scalability.
Partner with Prolifics to Maximize Your AI ROI
If you are considering GenAI at enterprise scale but are concerned about compliance, cost, governance, or operational overhead, the combination of Databricks AI Gateway and Prolifics provides the ideal foundation.
Partner with Prolifics and let our data and AI experts help you design, deploy, and manage a secure and scalable AI architecture on Databricks. From data strategy to Lakehouse modernization to end to end GenAI applications and agents, we deliver measurable results.
Let us help you build the next generation of AI powered enterprise solutions with governance, performance, and impact.
