Secure Private AI for Companies That Can’t Afford a Data Breach
The productivity gains of AI are real.
So is the risk of putting your clients, your contracts, and your competitive edge into a tool that trains on every word you type.
Renevar has spent years securing business data, networks, and endpoints for regulated companies. When AI arrived, we didn’t pivot — we applied what we already knew. We help growing companies adopt AI the right way: with your infrastructure, your data, your control.
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Most Companies Are One Court Order Away From Watching Their AI History Become Evidence
In February 2026, a federal judge in the Southern District of New York ruled in United States v. Heppner that documents a defendant created using a public AI tool were not protected by attorney-client privilege. The FBI had seized the device. The prompts and outputs became discoverable — used as evidence against the very person who typed them.
It was the first ruling of its kind. It will not be the last.
That decision should change how every CEO, CFO, CIO, and General Counsel thinks about AI. Because here’s the uncomfortable reality:
Your Team is already using AI.
They’re using multiple AI apps and LLM’s whether you’ve approved it or not.
Once your data is in their model, it doesn't come out.
There is no “delete my data from your training run” button.
Most public AI platforms train on what you type.
A judge has now ruled that data is not privileged or confidential.
Opposing counsel can subpoena it, leaving your company and clients exposed.
If your business handles client information, financial records, legal strategy, M&A activity, employee data, healthcare records, or any kind of regulated information — and you haven’t put a real AI policy in place — you don’t have an AI strategy. You have a slow-moving compliance event.
“Public AI platforms are designed for public consumption. Your business data is not.”
You Need to Read This If You’re a Leader At:
A Law Firm or Legal Organization
that handles privileged client matters.
A Financial Services Firm
governed by FINRA, SEC, or state regulations
A Healthcare or Life Sciences Organization
subject to HIPAA
A PE-backed Company
scaling fast and building infrastructure
A Multi-Location Business
with sensitive operational data
Any company
with a compliance framework — SOC 2, ISO 27001, PCI, GDPR — that hasn’t been updated for AI yet
If your team is asking “Can we use AI?” and the honest answer is “We don’t know what’s safe yet,” you’re exactly who we built this service for.
Your Infrastructure. Your Data. Your Control.
Renevar’s AI Systems Integration service helps you adopt AI without surrendering what makes your business defensible.
Security, governance, and compliance are the foundation of everything we build — ensuring you never have to choose between protecting what matters most and unlocking the full power of AI.
We don’t sell AI. We help you deploy it correctly.
Here’s something most AI vendors won’t tell you: the hardest part of AI adoption isn’t the model. It’s the security architecture around it. The access controls. The data policies. The compliance alignment. The question of who can see what — and how you prove it to an auditor.
That’s exactly what we’ve been doing for regulated businesses for years. Not with AI — with cybersecurity, managed infrastructure, and endpoint security. When AI entered the picture, we didn’t have to reinvent ourselves. We just had to apply what we already knew to a new set of problems that everyone else was ignoring.
That means looking at your business the way a strategic security partner should — understanding your compliance obligations, your data flows, your team’s actual workflows, and your existing tech stack — before recommending a single tool.
For some clients, that means properly configuring Microsoft 365 Copilot so it actually respects your tenant boundaries. For others, it means deploying enterprise OpenAI or private Gemini instances. For the most regulated, it means standing up a fully private, air-gapped AI environment that runs locally and never touches the public internet.
And for every client, it starts with the same question the rest of the industry skips: What does your data need to be safe?
You shouldn’t have to pick a model and hope. You should have a partner who knows what’s possible and what’s safe — and can build the right combination for your business.
AI Systems Integration, Built on a Foundation of Security
Tier 1: Secure Private AI Deployments
For companies that need their data to never leave their environment.
Azure Agent Foundry Services We design, deploy, and manage enterprise-grade AI agents within your private Azure environment — building secure, multi-agent workflows connected to your business systems, including SharePoint, SAP, Salesforce, and Dynamics 365. Every deployment enforces strict identity controls, network isolation, and compliance standards including GDPR and HIPAA. We manage the full agent lifecycle from prototype to production, with built-in monitoring, content safety, and governance.
Private Gemini Deployments and Integrations We deploy Google Gemini models in fully private, air-gapped, or on-premises environments through Google Distributed Cloud — purpose-built for regulated industries where data sovereignty is non-negotiable. Our integrations include custom agent development, RAG-powered knowledge retrieval, Google Workspace connectivity, and enterprise governance through Agent Gateway and Model Armor. Frontier AI capability — without your data ever leaving your controlled environment.
Coming soon: The Renevar Secure Private AI Platform — a turnkey, multi-model, role-based AI environment built for regulated businesses.
Tier 2: Enterprise Cloud Deployments & Integrations
For companies already invested in the major platforms — done right.
Microsoft 365 Copilot
We prepare, deploy, and optimize Microsoft 365 Copilot across your organization — from tenant readiness and licensing strategy to custom agent development in Copilot Studio. Our engagements include workflow automation via Power Automate, enterprise data source integration through Microsoft Graph, and governance via the Copilot Control System. Every deployment is paired with adoption programs and ROI measurement to ensure your investment translates to real productivity gains.
OpenAI & API Enterprise Models
We deploy OpenAI’s most advanced models within your secure cloud environment, with private networking, identity-based access controls, and version-governed model management. We build custom AI agents, fine-tune models on your proprietary data, and integrate OpenAI capabilities into your existing enterprise applications — deployed across Azure, AWS, or Google Cloud, wherever your workloads already live.
Chat GPT for Business
We integrate ChatGPT into your enterprise workflows and customer-facing applications — configuring secure access, custom system prompts, and usage governance policies that align with your organization’s standards. Our deployments connect ChatGPT to your internal knowledge bases and business tools, enabling teams to leverage conversational AI at scale while maintaining compliance, data protection, and cost visibility.
Claude
We deploy Anthropic’s Claude models into your enterprise environment — known for their strong reasoning, nuanced instruction-following, and built-in safety design. Our integrations connect Claude to your existing systems and workflows, making it an ideal fit for document analysis, complex decision support, customer engagement, and high-stakes use cases where accuracy, reliability, and responsible AI behavior are paramount.
Gemini
We integrate Google’s Gemini models into your cloud environment and productivity stack — including deep connectivity with Google Workspace, BigQuery, and Vertex AI. Our deployments take advantage of Gemini’s multimodal capabilities — text, code, image, and data — to power intelligent agents, analytics workflows, and enterprise applications. We handle the architecture, security configuration, and ongoing optimization so your team can focus on outcomes.
Tier 3: Corporate AI Strategy
For leadership teams who need a roadmap before they need a tool.
Most organizations don’t have an AI problem. They have a clarity problem. They know AI matters — they just don’t know where to start, what’s safe, or how to make it defensible to a board, a regulator, or an auditor.
That’s what Corporate AI Strategy is for.
Our engagements deliver a board-ready AI roadmap covering:
- Current-state readiness assessment — where you are today, where the risk lives, where the highest-ROI opportunities are
- AI governance frameworks — aligned to the EU AI Act, GDPR, and your industry’s specific regulatory requirements
- Data architecture strategy — ensuring your data infrastructure can support reliable AI at scale
- Operating model design — including AI Center of Excellence structure and cross-functional accountability so AI doesn’t die in a committee
- Workforce change management — upskilling programs and adoption planning so your team actually uses what you deploy
- Investment modeling — TCO analysis and measurable ROI frameworks so leadership can defend the budget
- AI security strategy — covering prompt injection defense, Zero Trust architecture, and ongoing risk management so your AI program is built to last
The output isn’t a slide deck. It’s a working plan your team can execute — with the security architecture to make it defensible from day one.
We’ve Been Securing Sensitive Business Data Since Long Before AI Was a Buzzword
Most companies choosing an AI partner are choosing someone who got into AI when AI got hot. We didn’t. Renevar’s founders spent years engineering secure data centers, building cybersecurity programs for regulated businesses, and helping growing companies meet SOC 2, HIPAA, and FINRA obligations before anyone was calling it “AI strategy.”
That history matters. Because when you strip away the hype, AI security is just security. The same principles — access control, data segmentation, audit trails, role-based permissions, zero trust architecture — apply whether the threat is a bad actor on the outside or your own team sending sensitive prompts to a public model.
We know this space because we built our business here. AI just gave us a new surface to secure.
What sets us apart:
Security-first DNA
Every recommendation we make starts with a question about your data, your compliance, and your risk posture — not with a product pitch.
Multi-Platform Expertise
We’re not locked into one vendor. We deploy and integrate Microsoft, Google, OpenAI, Anthropic, and open-source models — and we’ll tell you which fits your business.
Compliance-native
SOC 2, ISO 27001, HIPAA, FINRA, GDPR, EU AI Act — we design AI deployments that map cleanly to the frameworks your auditors care about.
Real human accountability
You’ll work with senior engineers and strategists, not a ticket queue. We answer the phone. We show up.
24/7 support model
Our existing managed services include around-the-clock coverage — built for companies that don’t stop running at 5 PM.
We build what we deploy
We’re actively developing our own Secure Private AI platform — which means we understand the full stack, not just how to point at vendor documentation.
Five Questions Every Executive Should Be Able to Answer About Their Company’s AI Use
1.
Do you have any compliance or regulatory requirements that govern your data?
If you’re SOC 2, HIPAA, FINRA, PCI, GDPR, or subject to the EU AI Act — your AI strategy is a compliance question, not a productivity question.
2.
Is this a company-wide deployment, or specific departments?
The blast radius determines the risk. Marketing using AI to draft copy is different from finance using AI to analyze deals.
3.
What kind of data is going into the model?
Public information? Fine. Your own internal data? Maybe. Your clients’ information, your contracts, your IP? You need a different kind of tool.
4.
Who has access — and can you prove it?
Role-based access control. Audit logs. Session recording. The basics of security still apply when the user is an AI agent.
5.
If there were a breach or a subpoena tomorrow, could you tell a regulator exactly what data went where?
If the answer is no, you’re not ready to scale AI in your business yet.
If you can’t answer these confidently, that’s not a failure — it’s just a starting point. It’s also exactly the conversation we have on a Discovery Call.
Here’s How a Discovery Call Actually Goes
Step 1: 30-minute conversation.
We’ll ask about your business, your industry, your current tech stack, and what’s prompting the AI question right now. No slide deck. No sales pitch.
Step 2: A short readiness summary.
We’ll send you a written summary of where the real risks and opportunities are — based on what we heard. You can use it whether you work with us or not.
Step 3: A scoped recommendation.
If it makes sense to go further, we’ll propose a specific engagement — usually starting with a focused AI Readiness Assessment or a targeted deployment.
Step 4: You decide.
We don’t pressure. Companies that aren’t ready usually come back six months later — and we’d rather have you when you’re ready than now when you’re not. Readiness Assessment or a targeted deployment.
The Industry Is Telling You Local AI Can’t Compete With the Big Models. They’re Wrong — and We Can Prove It.
You’ll read constantly that small, private AI models can’t keep up with the giant frontier models from OpenAI, Google, and Anthropic. That you have to send your data to the public cloud to get real performance.
That was true two years ago. It is no longer true.
We know this because we test it. We run private AI environments on dedicated hardware as part of how we develop and validate our own platform. The latest open-weight models — properly tuned and deployed on the right hardware — match the performance of frontier models from just a few months ago. On your own data, a private fine-tuned model will outperform any public model, because the public models don’t have access to your data in the first place. (And you don’t want them to.)
The future of AI in business isn’t a single all-knowing model in someone else’s data center. It’s a thoughtful combination — public models for public knowledge, private models for private data, and a security architecture that lets you decide what goes where.
That’s the architecture we build. And we build it because we’ve run it ourselves.
Frequently Asked Questions
Q: Do we have to rip out the AI tools we're already using?
Q: We have an internal IT team. Will you replace them?
No. We work alongside internal IT leaders all the time — co-managed engagements are one of our most common models. We make your team better, not redundant.
Q: How private is "private"?
Depends on the configuration. We deploy options that range from “private endpoint inside a public cloud” to “fully air-gapped, on-premises hardware with no internet connection at all.” The right answer depends on your data and your regulatory posture. We’ll walk you through it.
Q: Can you help us with Microsoft Copilot specifically?
Yes. Copilot deployments are one of our most-requested services right now — and one of the most commonly misconfigured. If your company is rolling it out, we should talk.
Q: What about agentic AI?
Same principles apply, with even more rigor. An AI agent is a non-deterministic system being given credentials to act on your behalf. You wouldn’t hand a new contractor admin access to your accounts on day one. The same logic applies to agents — and we help you build the guardrails.
Q: What's the engagement model?
Most engagements start with a fixed-scope AI Readiness Assessment. From there, deployments can be project-based, ongoing managed services, or co-managed with your internal team. We tailor it.
Q: How quickly can you get started?
A discovery call within the week. A scoped engagement typically within 2–3 weeks of that, depending on complexity.
The Companies Getting AI Right Are the Ones Who Started With Security.
The companies that get AI right in the next 12 months will pull ahead of the ones that don’t. Not because they found the best model. Because they built the right foundation.
The ones that get it wrong will end up explaining their prompts to a regulator, an auditor, or opposing counsel.
You don’t have to be either. You just need a partner who treats AI the way it should be treated: as a powerful capability that requires real security thinking — not a plug-and-play tool you figure out as you go.
That’s what we do. And we’re ready when you are.
Renevar is a managed technology and cybersecurity firm helping growth-stage businesses adopt AI securely. Headquartered in Atlanta. Serving clients across the Southeast and beyond.