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 · AI Infrastructure · China · Production
How Dify Established Runtime Control Over Its MCP EcosystemFrom fragmented, team-specific MCP configurations across Dify's agentic workflow platform to a defined inventory, centralized policy, and auditable allow/deny decisions at the tool-action boundary — across OpenAI, Anthropic, and open-weight model routes.
Read the case study →0202 · AI Infrastructure · United States · Production
How Modal Put Autonomous Software Engineering Under Runtime ControlBounded autonomy for AI coding agents on Modal's serverless GPU cloud: full development authority, with hard enforcement boundaries around production secrets, branch protection, and deployment.
Read the case study →Case studies 01–02 reference real customers (Dify / LangGenius; Modal Labs) under applicable publication agreements, with company scale figures drawn from public disclosures. Production case study customer identities are anonymized in accordance with publication agreements.
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