AI-powered monitoring that auto-fixes unreliable async jobs in JS/Python.
Developers struggle with unreliable and complex async processing leading to bugs and delays.
AsyncGuard watches your queues, detects failures early, and applies smart retries or fixes via AI suggestions. Integrates with existing BullMQ/Celery setups in minutes. Get alerted and resolved before bugs cascade.
Backend and full-stack developers implementing async tasks in languages like Node.js, Python, or JavaScript
AI-driven auto-remediation, not just passive monitoring like competitors.
professional
Connect existing queues (BullMQ, Celery) via agent.
Spot delays/failures instantly with ML thresholds.
Intelligent retries with exponential backoff + context.
AI analyzes logs and proposes code/config changes.
Custom alerts via email/Slack/Discord.
Latency, throughput, error rates charts.
Auto-categorize and bulk-resolve DLQs.
Replay past jobs for testing.
Multi-user views with roles.
Train on your data for anomalies.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| queue_type | text | No |
| config | text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| integration_id | uuid | No |
| type | text | No |
| resolved | bool | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| integration_id | uuid | No |
| latency | int | No |
| timestamp | timestamp | No |
Relationships:
/api/integrationsAdd queue integration
/api/alertsList active alerts
/api/metrics/:integrationIdFetch metrics
/api/fixes/:alertIdApply AI fix
/api/agent/webhookReceive queue events
1k events/mo
50k events/mo
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 80 | 3% | $65 | $780 |
| Month 6 | 700 | 6% | $1,134 | $13,608 |
Monitors BullMQ/Celery, auto-retries failures, suggests code fixes. Reliability without the hassle.
Target BullMQ/Celery GitHub issues with free installs. Email 20 devs from recent StackOverflow async questions. Run targeted Twitter ads to node/python devs.
Simple dashboard
No AI, manual only
Proactive AI fixes
Celery-specific
Passive monitoring
Cross-queue + AI
AI models trained on proprietary failure data.
Explosion of unreliable LLM/agent workflows needs smart oversight.
AI accuracy
Fallback to manual + fine-tune on user data
OSS loyalty
Agent-first, non-intrusive
OpenAI costs
Tiered usage
Success: 80% want AI fixes
Success: 5 integrations
Success: 20% referral conv
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