Make AI an advantage, not an exposure
Your people are already using AI, whether or not it has been approved. The question for leadership is no longer whether to adopt it, but how to adopt it deliberately: with clear ownership, defensible controls and a path from pilot to production. Cloudify helps mid-market and enterprise organizations turn scattered experiments into a governed AI program that delivers measurable value.
We bring strategy, governance and architecture together in one engagement, and we stay vendor-neutral. You get recommendations shaped by your data, your regulators and your risk tolerance, not by a quota.
Clarity before spend
A prioritized roadmap tied to business outcomes, so budget goes to the use cases most likely to pay off.
Governance that enables
Policies and controls your teams can actually follow, designed to speed approvals rather than stall them.
Your data stays yours
Private architectures with contractual and technical controls that keep sensitive data out of public model training.
What we deliver
AI Readiness & Strategy
An assessment of your data, infrastructure, skills and risk posture, followed by a use-case inventory scored for value, feasibility and risk, and a phased roadmap leadership can fund.
AI Governance & Compliance
Acceptable-use policy, a model and data inventory, AI risk assessments and an operating model aligned with the NIST AI RMF, ISO/IEC 42001 and, where it applies, the EU AI Act.
Private LLMs & RAG
Retrieval-augmented generation on your own content, deployed in your private cloud tenant, on dedicated GPU infrastructure or on-premises, behind private endpoints with role-based access.
Secure Copilot & Gen-AI Rollout
Readiness for Microsoft 365 Copilot and similar assistants: permission and oversharing cleanup, sensitivity labels, pilot design, adoption and usage reporting.
Data Readiness & Security
Data discovery and classification, data loss prevention, identity and access hardening, and retention policies, so AI only reaches what each user is entitled to see.
AI Agents & Automation
Agents and workflow automation for IT, finance, operations and service teams, with human approval steps, scoped permissions and full action logging.
Contact Center & CX AI
Agent assist, conversation summaries, intelligent routing, self-service and quality analytics, integrated with your contact center platform and CRM.
Managed AI Operations
Ongoing monitoring for model drift, output quality, guardrail effectiveness and cost, with periodic red-team testing and governance reviews.
Shadow-AI Discovery
Visibility into which AI tools are in use across the business, what data is flowing into them, and a practical plan to sanction, replace or block each one.
Governance built for regulated business
AI does not get its own rulebook. It inherits every obligation you already carry. We map your AI program to the frameworks your auditors and customers expect, and build the evidence trail to prove it.
- NIST AI Risk Management Framework
- ISO/IEC 42001 AI management system
- EU AI Act risk classification
- HIPAA and protected health information
- SOC 2 control mapping
- PCI DSS cardholder data scope
- GDPR and CCPA privacy obligations
- Data residency and sovereignty
- Audit trails for prompts and outputs
- Model and data inventory
- Vendor and third-party AI risk review
- Acceptable-use policy and training
Private AI on your terms
For many organizations the right answer is not a public chatbot but a private one. We design architectures where models run inside boundaries you control: a private tenant in your cloud, managed services such as Azure OpenAI or Amazon Bedrock behind private endpoints, or self-hosted open models on dedicated or on-premises GPUs.
No training on your data
We select services and contract terms where your prompts, files and outputs are not used to train shared models, and we verify those settings during deployment.
Permission-aware retrieval
Answers are grounded in your documents and respect the access rights already in place, with encryption, logging and retention policies set to match your requirements.
How we work
Assess
Interviews, discovery and technical review to understand your data, systems, risks and the opportunities worth pursuing first.
Govern
Policy, ownership, risk tiers and controls established up front, so every use case has a clear path to approval.
Build
Architecture, vendor selection and delivery of prioritized use cases, piloted with real users and measured against agreed outcomes.
Operate
Monitoring, cost management, guardrail tuning and regular governance reviews as models, regulations and your business change.
Industries we support
Healthcare
Clinical documentation support, patient communications and revenue-cycle automation designed around HIPAA safeguards.
Financial Services
Research assistance, document review and service automation with model risk management and audit-ready records.
Legal & Professional Services
Private knowledge search, drafting support and matter intake that protect privilege and client confidentiality.
Manufacturing
Maintenance knowledge, quality insights and supply-chain assistance that keep operational and design data protected.
Public Sector
Constituent services and internal productivity with attention to transparency, records requirements and data residency.
Multifamily & Real Estate
Leasing and resident communications, maintenance triage and portfolio reporting across properties and systems.
Frequently asked questions
Where should we start with AI?
Most organizations start with a readiness assessment and a short list of high-value use cases. That gives leadership a funded roadmap and gives security and compliance teams the policies they need before anything reaches production.
Will our data be used to train public AI models?
It should not be, and we design for that. We recommend services and contract terms that exclude your prompts and content from model training, deploy behind private endpoints where possible, and confirm the relevant settings during rollout.
Which frameworks do you align AI governance with?
We typically use the NIST AI Risk Management Framework as the backbone, align the management system with ISO/IEC 42001, assess EU AI Act obligations where they apply, and map controls to the regulations you already follow, such as HIPAA, SOC 2, PCI DSS, GDPR and CCPA.
Can AI run privately or on-premises?
Yes. Options include a private tenant in your cloud provider, managed model services behind private networking, and self-hosted open models on dedicated or on-premises GPU infrastructure. We help you weigh performance, cost and control for each.
Are we ready for Microsoft 365 Copilot?
Copilot can surface anything a user already has access to, so readiness is mostly about permissions and data hygiene. We review oversharing, apply sensitivity labels and data loss prevention, and run a measured pilot before broad rollout.
How do you find shadow AI?
We combine network, identity and SaaS discovery data with short staff surveys to identify the AI tools in use and the data reaching them, then recommend which to sanction, replace or block.
Do you support AI after launch?
Yes. Managed AI operations cover monitoring for drift and output quality, guardrail tuning, usage and cost reporting, periodic red-team testing and governance reviews.
Ready to build an AI program your board, auditors and employees can trust? Talk to a Cloudify advisor or call 888.660.6190.