Latitude
Refine LLM prompts using real data to build reliable AI applications
Target Audience
- LLM application developers
- AI product teams
- Technical prompt engineers
- DevOps engineers managing AI systems
Overview
Latitude helps teams develop better AI products by tracking and improving LLM prompts through real-world performance data. It lets you test multiple prompt versions at scale, compare results, and deploy updates confidently. The open-source platform is built for technical teams who need to maintain consistent AI outputs in production environments.
Key Features
Prompt Analytics
Track production logs to monitor prompt performance
Version Testing
Compare multiple prompt versions using batch processing
AI Refinement
Automatically improve prompts using performance data
Open-Source Core
Self-host or modify platform to meet specific needs
SDK Integration
Deploy updated prompts directly to applications
Use Cases
Engineering reliable chatbot responses
Optimizing AI product performance
Testing LLM prompt variations at scale
Collaborating on prompt version control
Pros & Cons
Pros
- Open-source foundation for customization
- Data-driven prompt improvement cycle
- Production-to-testing feedback loop
- Free tier for small-scale usage
Cons
- Requires technical setup for integration
- Self-hosting adds infrastructure complexity
- Primarily targets developers vs end-users
Pricing Plans
Hobby
monthlyFeatures
- 40k prompt runs/month
- Basic analytics
- Community support
Team
monthlyFeatures
- Unlimited prompt runs
- Advanced analytics
- Priority support
- Team collaboration
Enterprise
annualFeatures
- Dedicated infrastructure
- SLA guarantees
- Custom integrations
- Security reviews
Pricing may have changed
For the most up-to-date pricing information, please visit the official website.
Visit websiteFrequently Asked Questions
Can I self-host Latitude?
Yes, Latitude is open-source and can be self-hosted for full control over your infrastructure
What types of evaluations does Latitude support?
Supports both automated LLM-based evaluations and human evaluations for quality checks
How does version control work for prompts?
Allows comparing different prompt versions side-by-side using historical performance data
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