SAILLENTBook a DemoHow organizations place an independent authorization boundary between autonomous AI agents and the systems they control. Each case study follows the same editorial template: existing posture, architectural gap, attack scenario, runtime decision record, policy model, and results.
0101 · Fintech · MENA · Production
How Lean Technologies Established Runtime Control Over Autonomous Payment AgentsAction-level security policies across Pay by Bank, Payouts, and open-banking data flows for MENA's leading fintech-infrastructure platform. Unauthorized high-impact actions prevented before execution.
Read the case study →0202 · Enterprise SaaS · Illustrative scenarioFrom fragmented, team-specific MCP configurations to a defined inventory, centralized policy, and auditable allow/deny decisions at the tool-action boundary.
Read the case study →0303 · Fortune 500 · Illustrative scenarioBounded autonomy for AI coding agents: full development authority, with hard enforcement boundaries around production secrets, branch protection, and deployment.
Read the case study →Case study 01 references Lean Technologies under the applicable publication agreement; company scale figures are drawn from Lean's public disclosures. Case studies 02 and 03 are illustrative scenarios: fictional customers with hypothetical metrics, published to demonstrate the SAILLENT control model and methodology. They will be replaced with verified engagement data as real deployments are published. Production case study customer identities are anonymized in accordance with publication agreements.
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