AiSanity
Monitors AI apps for hallucinations, model drift, and broken JSON schemas.
Product memo
AI app developers and teams face a new set of quality challenges beyond uptime. AiSanity provides a crucial QA layer, focusing on output quality like hallucinations, model drift, and schema validation. It builds production confidence and stakeholder trust through public status pages, offering a specialized monitoring product for B2B AI applications.
- For who
- AI app developers and teams
- Solves what
- AI hallucination, model drift, and broken JSON schema issues
- AI output monitoring
- Model drift detection
- JSON schema validation
Operator & company
Operators
1 person
Company
- Founded
Dec 2025
- HQ
Thailand
Operating model
- Business model
Usage Based
- Platform
Web app
- Audience
Developers
- Payments
Stripe
Product channels
Builder strategy
- Strategy Type
- Niche Specialist
- Stage
- Pre Revenue
- Effort
- Solo Buildable
Source evidence
Evidence sources
About AiSanity Expand
AiSanity provides a specialized quality assurance layer for AI applications, moving beyond basic uptime checks to focus on output integrity. It helps AI app developers and teams catch critical issues like AI hallucination, model drift, and broken JSON schema validation.
By offering features such as LLM-as-a-Judge and public status pages, AiSanity builds confidence in AI deployments. The product's positioning as a missing QA layer addresses the unique challenges of maintaining reliable AI performance in production environments.
In their own words
Uptime isn’t quality. Monitor AI outputs in production.
AiSanity catches hallucinations, model drift, and broken JSON schemas before users notice — with cost-aware checks that don’t spam your token bill. Share a clean status page when stakeholders ask, “is it working?”
Stop trusting '200 OK'. AiSanity monitors your AI for hallucinations, model drift, and broken JSON schemas. The missing QA layer for AI apps.
Competitive context
5 peers · Same primary niche · Radar benchmark · AiSanity #3737.
Commercial cues
- Model
- usage based
- Free tier
- No
- Trial
- No
Pricing strategy
- • Tiered plans scale monitor counts, matching usage to a team's needs.
- • Clear feature differentiation across tiers encourages upgrades for deeper insights.