Modern AI agents are built on probabilistic models, yet they are increasingly being deployed in workflows where decisions must be reproducible. A candidate should not qualify on one run and fail on the next. An invoice should not be approved by one model and rejected by another.
The same input should always produce the same outcome.
Most agent frameworks today are model-centric: the outcome depends on how the model interprets a task and decides to act. TCP/AP was built to ensure runtime decisions remain conformant to the system owner's intent. The model remains free to interpret, reason, and extract information, but the resulting decision must conform to an explicit protocol before any action can occur.
The result is deterministic decision-making on top of probabilistic systems.
Toggle between an Autonomous Agent and a TCP/AP-governed Agent. Upload poisoned documents, embed prompt injections, switch models, and compare the outcomes in real time. The goal is simple: see for yourself what determinism looks like in an LLM-native agent.
Screen candidates against hiring requirements. Upload qualified, unqualified and poisoned CV's and see how Socrates rejects manipulation in real time.
Stress test Socrates →Request a travel itinerary and see how the agent satisfies every constraint and refuses or escalates rather than guess. Hand it deliberately ambiguous preferences and conflicting plans and see how the system cannot suggest out-of-policy bookings.
Coming soon →Approve invoices against declared payment requirements. Submit clean bills, duplicates, missing fields, or mismatched amounts and see how the agent refuses anything outside policy instead of letting money move on guesswork.
Coming soon →Evaluate loan applications against fixed lending criteria. Change income, doctor documents, or introduce conflicting claims and see how the decision stays stable instead of drifting with the story.
Coming soon →The Bottom Line: Four different domains, four distinct decisions, governed by the exact same protocol. TCP/AP exists to preserve absolute coherence when reproducibility and auditability matter most.