paytek: Where Agentic AI Meets Enterprise Reality

paytek delivers every layer of the unified stack in a container — no gaps, no stub implementations. It is designed around explicit principles for workflow, decision grounding, context, persistence, and orchestration. Can be forked as a foundation.

paytek grounds agent decisions in structured domain knowledge, not probabilistic text retrieval. A dedicated knowledge layer keeps merchant relationships explicit and enables agents to reason from verified business context. Decisions are backed by facts, not best-guess embeddings.

paytek makes model selection a config change, not a code change. The runtime is designed so models can be swapped, benchmarked, or specialized per agent role — independently of the rest of the system.

A clean protocol boundary gives agents a well-defined contract to the data layer — any framework connects without coupling to storage. The separation of semantic context from core data means the knowledge layer evolves independently of agent logic, with no leakage between what an agent can know and what it can do.

paytek separates workflow logic from code entirely — gate rules, routing conditions, and agent parameters live in configuration, not in the agent. A risk threshold, escalation path, or agent prompt can be updated mid-deployment without a release. Teams managing policy and teams managing code work on independent cycles.

paytek turns the merchant journey into a stateful, recoverable workflow with checkpoints, risk evaluation, and human-in-the-loop controls. Every step is named, observable, and recoverable so the system never drops state silently.

paytek runs agents built across different frameworks — LangGraph, AutoGen, or bespoke — in the same orchestrated workflow without forcing a shared runtime. Each agent exposes a standard interface; the orchestrator routes to it. Adding a new framework is an integration task, not an architectural decision.

paytek eliminates manual hand-offs from the merchant lifecycle entirely. It carries every merchant from conversation through extraction, compliance checks, risk evaluation, and persistence in a recoverable workflow. The workflow either completes or recovers; it never silently drops.

paytek's data layer is built for agents to query, not just humans. Shared domain models give agents a common vocabulary, and specialized storage keeps each concern in the right place. No single datastore is asked to do everything.

paytek gives every risk decision real context by linking current merchant data with historical patterns and graph relationships — so the evaluation reasons from evidence, not heuristics, and can be audited after the fact.

paytek ships production-ready with built-in deployment, monitoring, and recovery. Stateful services surface for human review rather than failing silently, and response quality is evaluated in real time so issues surface during the run — not in the post-mortem.

paytek makes governance a participant in the workflow, not a gatekeeper in front of it. Configurable rules approve, escalate, or flag — never hard-block. When a check fails, the workflow routes to human review rather than rejecting outright, so compliance teams get oversight without slowing every merchant down.

paytek enforces security at runtime, not at the perimeter. The Guardian agent intercepts every write before it reaches the database — validating identifiers, checking intent against allowed patterns, and blocking non-compliant mutations on the spot. Enabled by default; a bypass requires an explicit override, never an omission.