AI agents that know when to ask for help. Seamless escalation to humans with SLA enforcement, zero context loss, and automatic resume.
In EnGenAI, human agents and AI agents share the same interface. A human is
registered with execution_mode='human' and
appears in the agent roster alongside AI agents. The system routes tasks based
on capability, not species.
When an AI agent reaches its autonomy limit or encounters a task that requires human judgement, it escalates automatically. The routing engine matches the task to the right human by role — business analyst, architect, legal, compliance.
Every human task has a configurable SLA window. The system sends automatic reminders when time is running out, escalates on breach, and tracks response metrics for accountability.
When an AI task is escalated, the agent suspends cleanly. All conversation context, working memory, and partial results are preserved in a Redis breadcrumb. When the human responds, the agent resumes from the exact point of suspension — zero information loss.
Human agent task scheduling runs on a background task scheduler with Redis as the message broker. A dedicated periodic scheduler checks SLA windows every 5 minutes, sends reminders, and triggers breach escalations — all without any manual intervention.
Every agent (AI or human) exposes an A2A-compatible Agent Card endpoint. This enables standardised agent discovery and inter-agent communication across organisational boundaries.
Task worker and scheduler run as separate Kubernetes deployments alongside the API and frontend. Each pod is non-root (UID 1001), resource-limited, and monitored via ArgoCD GitOps.
Human agents are first-class citizens in EnGenAI — same API, same routing, same observability. We're onboarding select B2B teams for early access.
Register for Early Access →