Run with confidence. Governance built into every step.
Every Leah agent action is policy-governed, encrypted, and auditable. Trust by design, not by promise.
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Generic AI cannot run a commercial function. Governance is the difference.
For Leah to execute legal, contracting, procurement, and finance work autonomously, the controls have to be intrinsic. These are the failures we engineered out from the start.
Black-box decisions you cannot defend
Generic LLMs make consequential decisions without explanation. When regulators, auditors, or your own board ask why an agent took an action, the answer cannot be a shrug. Every decision needs a traceable rationale.
Data leaking into models you do not own
Public LLMs train on what they ingest. Sending privileged contracts, supplier terms, or financial records into a shared model surface is a privacy and compliance event waiting to happen. Zero retention is the only acceptable answer.
One-size-fits-all models that ignore your policy
A general-purpose model does not know your playbooks, your fallback positions, your jurisdictional rules. When the model and the policy disagree, the policy must win. Generic AI gets this backwards.
No visibility into what agents actually did
If an agent reviews a thousand contracts overnight, you need to know which ones it approved, which it escalated, what it changed, and why. Without per-action audit trails, scale becomes unaccountable.
Compliance frameworks bolted on after the fact
Trying to retrofit GDPR, SOC 2, or HIPAA controls onto a system not built for them creates audit gaps. Governance has to be in the architecture from the first commit, not a paragraph in a vendor questionnaire.
Trust by promise instead of by design
Vendors promise their AI is safe. That is not enough for a CFO running invoicing or a CLO running M&A diligence. Trust has to be built into the system: encrypted, isolated, governed, and auditable from day one.
Three pillars. Built into the architecture, not bolted on.
Data Models You Control
Leah dynamically selects across multiple advanced LLMs to match each task with the right model. You can extend or customize models without writing code. New and adjusted models deploy instantly across your organization, governed by your rules.
Security First by Design
TLS for data in transit. AES-256 for data at rest. Keys managed in Azure Key Vault, rotated regularly. Multi-factor authentication, secure API gateways, network segmentation, real-time monitoring, and a fully documented incident response plan.
Ethics in Action
Leah operates against your policies, your playbooks, and established legal precedents. Every action is measured against benchmarks for accuracy, bias, and outcome. Accountability is structural, not aspirational.
Policy in. Execution governed. Audit out.
Every agent action runs the same loop. Configurable, observable, defensible.
Policy In
You define the guardrails: which agents can act, on which data, within which thresholds, and where escalation is required. Policies live as configuration, not code.
Execution Governed
Every agent action runs through your policies in real time. Approvals, escalations, and rejections happen automatically based on the rules you set. The orchestrator enforces guardrails at every step.
Audit Out
Every decision is logged with full rationale: what the agent did, why, against which policy, with what data, and what the outcome was. Tamper-resistant, immutable, and ready for any audit.
Independently audited. Continuously verified.
Audited annually by an independent MSSP. Penetration tested regularly. Aligned to the frameworks your security and compliance teams already require.
Security and governance, answered.
Leah uses TLS (HTTPS) for all data in transit and AES-256 encryption for all data at rest. Comprehensive audit logs are tamper-resistant and immutable.
Encryption keys are managed through Azure Key Vault KMS, rotated regularly, and accessible only through strictly controlled service accounts.
No. Leah enforces zero data retention policies with OpenAI and Anthropic. Your data is processed but never stored by the underlying LLM providers.
Multi-factor authentication, secure API gateways, network segmentation, real-time monitoring, and a fully documented incident response plan are in place at every layer.
Yes. Leah is GDPR and CCPA compliant, undergoes regular penetration testing, and is audited by an independent Managed Security Service Provider.
Yes. Leah offers a dedicated zero-trust private environment within Azure OpenAI Studio, ensuring complete data isolation from all other customers.
Leah holds SOC 1 and SOC 2 (Type I and Type II) certifications, is HIPAA-ready, GDPR-compliant, supports CCPA principles, and is aligned to ISO 27001 frameworks.
