LLMac is the secure access layer between enterprise databases and AI apps or agents. We enable enterprises to connect data, design enforceable policies, and empower their teams to adopt AI safely, with full audit and compliance.
Before AI can be trusted, it has to connect safely. This is where LLMac makes its mark. We connect directly to your databases — no duplication, no shadow copies. Because the safest AI is always the one working on your complete, real-time data under strict access controls.
LLMac integrates with SQL, NoSQL, data warehouses, and vector databases. Whether BigQuery, Snowflake, MongoDB, or Qdrant — we connect natively.
We don’t import partial snapshots or create unsecured caches. LLMac connects directly to your full data sources, ensuring fidelity, traceability, and compliance. Every AI app or agent sees only what they’re allowed to, and nothing more.
Deploy on-premise, in your VPC, or in the cloud — the entire platform is lightweight, containerized, and enterprise-ready. You can be up and running in days, not months.
LLMac adapts to your organization. From mapping your HR structure into access groups, to enforcing region-specific compliance rules, we tailor the deployment so your policies match your enterprise reality.
We’re committed to your success beyond the software. Every LLMac purchase comes with access to an AI security consultant — not just for technical setup, but to help you design policies, align stakeholders, and move your AI adoption forward with confidence.
LLMac makes access policies as clear as your business logic. Instead of writing brittle SQL filters or relying on static RBAC roles, LLMac gives you a flexible policy framework that mirrors how your enterprise actually works. Rules are human-readable, reusable, and apply consistently across every AI app, agent, and database.
Turns messy permissions into a single source of truth. With LLMac, Finance sees only what Finance should, HR sees only what HR should, and AI agents inherit the same rules automatically. Policies are written once, stored centrally, and enforced everywhere — turning scattered permissions into one governance layer.
Every rule you describe in LLMac is explicit, auditable, and version-controlled. You can fine-tune or extend policies at any time without altering your underlying databases. The system was built for modern governance: change management, compliance review, and collaborative iteration are first-class features.
Not a black box — always transparent. Rules are auditable, version-controlled, and change-managed. Extend policies anytime without altering databases.
group_id: treasury_ops
matching_mode: hybrid
filters:
department:
match: strict
value: ["Treasury"]
region:
match: contains
value: ["Canada", "UK"]SELECT *
FROM finance_ledger
WHERE department = 'Treasury'
AND region IN ('Canada','UK')One is governance-ready and portable across every enterprise system. The other is just SQL.
As your AI use cases grow, policies evolve with them — without needing to rebuild data pipelines or duplicate rules. Every change is logged, every version is recoverable, and auditors can trace exactly who defined what, and when.
LLMac isn’t just about controlling access — it’s about enabling safe exploration. Your teams and AI agents can query, test, and collaborate with enterprise data knowing every result is compliant, filtered, and auditable. Exploration becomes fearless when governance is built-in.
Exploring with LLMac When you experiment with AI, you rarely know where the next question will lead. LLMac ensures that wherever your exploration takes you, sensitive data is never exposed.
Queries run live against your databases, but policies filter results at runtime.
Use the Playground to test policies and simulate queries before deploying them.
Audit & Observability — every access fully traceable. Export logs to Splunk, Datadog, or SIEMs. Full visibility for engineers, governance, and auditors.
LLMac works with your enterprise AI stack of choice — copilots, custom AI apps, or third-party LLMs. No matter the interface (web, desktop, or mobile), access controls remain consistent and enforceable.
Simulate AI queries in a safe sandbox before giving agents production access.Run policy tests on Finance, HR, or R&D datasets to validate outcomes.
Share queries and results directly across teams with full audit context.
Built-in protections: Prompt injection and RAG poisoning defenses. Row, column, and field-level filters at query time.Cross-database and multi-cloud enforcement so you always work with the full, trusted picture.
LLMac makes AI exploration a team sport. Policy files and access models are reusable across departments, and results can be validated and shared with colleagues or auditors — no hidden black box, just transparent governance.
Developers can integrate LLMac directly into apps via the SDK, APIs, or policy JSON. Extend protections into any custom workflow or product, while maintaining consistency with enterprise access rules.
Book a demo or deploy a sandbox to see LLMac in action for your enterprise.
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