Bring peace of mind
to your AI solutions
Ensure reliable performance, catch errors, control costs.
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Transform LLM uncertainty into stability.
Turret provides a suite of tools to help you manage your AI agents.
Simply implement our SDK & give yourself omniscience over your AI solutions.
Live Monitoring
Never miss something your agent does; monitor LLM responses & actions live.
Cost Transparency
Track your language model usage. Never get a surprise bill from model providers.
Error Detection
Catch AI agent errors when they happen, trace hallucinations, and view missed context.
Stay Alert
Get alerts on usage, errors, and custom thresholds with higher plans.
Generate Reports
Generate and download reports on AI agent performance and cost metrics.
Budget Management
Monitor your monthly spend and project budgets to manage expenses.
Pricing
Choose the plan that's right for you
Starter
$95 $66.50/month
Best for teams testing a simple AI app
- ✓
Track AI agent performance
- ✓
Monitor actions taken by agent
- ✓
Manage costs with each agent
- ✓
Error logging with in-app alerts
- ✓
Watch monthly spend w/ budget projection
- ✓
Download reports on AI performance and cost metrics
Core
$288 $201.60/month
Best for launching one or more AI app(s)
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Advanced error analysis
- ✓
Customizable alert thresholds
- ✓
Customizable error types
- ✓
Integration with third-party reporting tools
- ✓
Email, Slack, SMS error alerts
- ✓
Visual breakdown of monthly spend by agent
Business
$480 $336.00/month
Best for scaling AI apps with advanced features
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AI-driven error resolution suggestions
- ✓
Root cause analysis for errors
- ✓
Deep dive into token usage trends & patterns
- ✓
Predictive analytics for token usage & cost forecasting
- ✓
Priority support
- ✓
Custom integrations on request
About Us
Our Mission
Turret’s mission is to mitigate the risks in adopting AI into your business or product. Whether that’s a customer-facing feature with AI, or an internal tool to streamline productivity, you’ll be prepared for anything.
Every week, thousands of AI products are launched, making their founders money on autopilot, or built internally, promoting the 10x developers who built them.
But LLMs make mistakes. In some use-cases, it’s reliable, but needs a human-in-the-loop. In others, the models need more work to be reliable. Regardless, as these models get better, you no longer need to manually manage AI activity, errors, and costs for the AI app you’re building.