Product Information
What is Klu?
Design, deploy, and optimize generative AI applications with Klu
How to use Klu?
Use your preferred LLMs (such as Claude, GPT-4, Llama 2, etc.) to seamlessly integrate with data from databases, files, or websites, building AI applications. Develop optimal prompts, evaluate usage, and enhance performance with one-click model fine-tuning.
Core Functions of Klu
Building, evaluating, and optimizing GPT-4 applications
Prototyping with Klu Studio in minutes
Connecting CRM, databases, knowledge bases, and ticketing systems
Dynamic prompt generation
Generative AI chat with context, memory, and conversation
Connecting multiple actions
Retrieval-based generation
Interactive design environment
Connecting SQL, Snowflake, Elasticache, Redis
CRM, knowledge base, and ticketing integration
One-click deployment for publishing
Advanced data engine for scaling generative AI
Monitoring usage, costs, and performance insights
Adding contextual documents via API or UI
Filtering with contextual metadata
Real user behavior and feedback
Advanced filters, import/export
Collecting real-world learning
Fine-tuning GPT-4 and others with your data
Building with Klu Python, TypeScript, and React SDK
Collaborative editing with context
Generating dynamic content with document references
Creating chat experiences with brand voice
Creating on-demand coaching
Summarizing large documents
Quickly qualifying leads
Creating content with dynamic prompts
Analyzing user feedback and sentiment
Extracting, cleaning, and transforming data
Usage Scenarios of Klu
- Generative or analytical operations
- Prototyping new ML policies
- Building conversational chat and coaching experiences
- Better understanding customer feedback
Common Questions about Klu
Which LLM providers can I use with Klu?
What are the core features of Klu?
What are Klu’s pricing plans?
What use cases does Klu support?
Which SDKs does Klu offer?
