Confidently adopt AI for sensitive use cases once considered too risky — with enforceable rules on what AI apps and agents can access in your databases, and a complete audit of every action.
Enterprises can’t let AI apps and agents touch their critical enterprise databases today. Why? Because a single misstep could expose records, break compliance rules, or allow the wrong team to see the wrong data. The result: AI adoption stalls where it matters most — from Finance and Legal to Audit, R&D, and beyond.
LLMac makes it possible for enterprises to safely use their critical enterprise databases inside AI apps and agents. You define exactly what Finance, Legal, Audit, R&D, or any other team member using your enterprise AI apps can access — and apply the same rules to AI agents. Every access is tracked, giving enterprises full confidence and control.
For enterprises moving from AI pilots to production, the challenge isn’t building apps — it’s controlling access.LLMac gives Security and Data Platform leaders a way to enable AI adoption without losing oversight of their most sensitive databases. The result: innovation moves forward, compliance stays intact.
Connect directly to your databases — Because the safest AI is always the one working on your complete, real-time data under strict access controls. Keep all data inside your perimeter, under strict access rules.
Translate business logic into enforceable rules. One governance layer ensures Finance, HR, and AI agents only see what they’re authorized to see.
Let teams and AI agents build safely. Every query is validated at runtime, every action is auditable, and sensitive data never slips through.
Explore how LLMac enables safe AI adoption across your enterprise. Start with AI apps used by your teams, or AI agents working alongside them.
Portfolio managers want AI-powered dashboards to analyze performance, generate client-ready reports, and run “what-if” scenarios.
Compliance officers want AI apps that scan transactions, contracts, or communications for red flags. Without guardrails, an app could reveal sensitive deals or client identities to the wrong user.
Ops leaders want AI apps to surface supply chain risks, inventory forecasts, and production anomalies. But databases contain supplier contracts, cost breakdowns, and PII of logistics partners.
Internal auditors want AI apps to test controls and spot anomalies in ERP or finance systems. But exposing all ledger or payroll data to every auditor risks overreach.
Research teams want AI apps to explore trial data, lab results, and genomic databases. Without ACL, researchers could see trial arms or patient data outside their study.
Agents analyze spend and cash flow — without ever exposing payroll or restricted ledgers.
Copilots handle claims and intake securely, with PHI masked unless explicitly authorized.
Underwriting copilots query policies by region and product line — fraud markers stay hidden.
Predictive AI assistants help spot outages and risks, while SCADA controls remain locked down.
Caseworker copilots access only assigned cases — all queries logged for compliance and FOIA.
Let’s chat about your data, your teams, and the AI apps or agents you want to deploy. We’ll show you how LLMac adapts to your exact needs.