Comparison

CueAPI vs Inngest

Inngest is event-driven background functions for web apps. CueAPI is coordination infrastructure for AI agent systems with verified outcomes. Different focus areas, different architectures.

FeatureInngestCueAPI
Primary use case
Event-driven background functions for web applications
Coordination with verified outcomes for AI agent systems
Integration model
SDK-based -import inngest, define functions in your codebase
API-based -any HTTP client, any language, no SDK required
Scheduling
Cron functions as one of many trigger types
Scheduling is the core product: cron, one-time, interval, manual fire
Outcome tracking
Function return values and step results
Six outcome states: reported_success, reported_failure, verified_success, verification_pending, verification_failed, unknown
Delivery model
Event-driven -your functions run on Inngest infrastructure
Webhook push to your server or worker pull from your agent
Agent focus
General purpose -any background job pattern
Purpose-built for AI agents -payload delivery, outcome verification, failure alerting
Execution ownership
Your code runs on Inngest servers
Your code runs on your servers -CueAPI delivers and tracks
Failure handling
Automatic retries with step-level recovery
Automatic retries with exponential backoff + proactive failure alerts
Worker mode
Not applicable -functions are pushed
Built-in worker pull mode for agents behind firewalls
Security
Platform-managed security
HMAC-signed webhooks, SSRF protection, HTTPS-only, hashed API keys
Open source
Yes -Inngest server is open source
Yes -CueAPI Core is open source

Different models of execution

Inngest runs your code on its infrastructure. You define functions using the Inngest SDK, and Inngest manages execution, retries, and step orchestration. This works well for web application background jobs -user onboarding flows, webhook processing, data syncs.

CueAPI takes a different approach: your agent runs on your infrastructure. CueAPI delivers a payload (via webhook or worker pull) and verifies the outcome. Your agent has full control over execution. CueAPI provides the coordination, delivery, and verification layer.

Built for AI agents

CueAPI's outcome verification system is designed specifically for agent workloads. Agents report structured outcomes with six states (reported_success, reported_failure, verified_success, verification_pending, verification_failed, unknown) plus evidence metadata. CueAPI verifies that outcomes are reported and alerts when they're not. This verification pattern (did the agent actually do the thing?) is what makes CueAPI different from a general-purpose job queue.

No SDK required

CueAPI is a REST API. Use curl, fetch, requests, or any HTTP client in any language. There is no SDK to import, no DSL to learn, no vendor lock-in on your function definitions. If you can make an HTTP request, you can use CueAPI.

Coordination built for agents

No SDK. No vendor lock-in. One API to declare, deliver, and verify.

How do I know if my agent ran successfully?
Ctrl+K