Klu Documentation

Welcome to the Klu documentation. This site includes resources for using the API and SDK, guides to common Klu platform use cases, and best practices for deploying LLM Apps.

Last updated: February 25, 2024

Klu is an LLM App Platform Klu.ai LLM App Platform


Key Klu Concepts

Learn key concepts in Klu, from Actions and Context to Workspaces.

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Your First App

Build your first app in Klu Studio and deploy it to production.

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Integrate Existing App

Connect an existing OpenAI app to Klu in 5 minutes.

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LLM Primer

Key LLM concepts when just getting started with GenAI.

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What is Klu

Klu.ai is an LLM App Platform that streamlines prototyping, deploying multiple models, evaluating performance, and optimizing LLM-powered applications and features. Klu integrates with your preferred Model Providers and connects data from varied sources, giving your applications unique context.

How Klu Works

Klu helps engineering teams rapidly build and iterate on LLM-powered applications. It provides a unified API access to LLMs like Anthropic Claude 2 and OpenAI GPT-4, allowing developers to quickly test prompt engineering and performance.

LLM Providers

Klu supports all leading LLM providers. Klu comes with a global deployment of OpenAI models built on Azure, enabling all platform functionality to work immediately. Usage of the Klu models is included in the subscription, all other usage is handled by the connected platform. Leading AI Teams connect to additional models using their private API tokens. This ensures data privacy and enables fine-tuned models to live in your account or infrastructure.

Klu (Azure GPT-4 Turbo, GPT-4, and GPT-3.5)All Plans
Klu (Azure GPT-4 32k)Enterprise
OpenAIAll PlansPro+
Azure OpenAIAll PlansPro+
PerplexityAll Plans
AnthropicAll PlansPro+
Google VertexAll PlansEnterprise
AWS BedrockAll PlansEnterprise
Together AIAll PlansPro+
Cloudflare AIAll Plans
ReplicateAll Plans
HuggingFaceAll Plans
CohereAll Plans
AI21All Plans
Self-hosted modelsEnterpriseEnterprise

Build & Evaluate

AI Engineers use Klu's SDKs to build LLM Apps directly into their applications and gather usage data on LLM performance. This allows efficient A/B testing of different prompts and models to optimize the end-user experience. Klu facilitates LLM evaluation through built-in support for logging, monitoring, and analysis. Developers can easily see how different prompts and models perform with real user input. These observations enable data-driven decisions around model selection, prompt engineering, and fine-tuning.


For storage and retrieval of knowledge, Klu has built-in support to index and query embeddings, supporting a range of file types, datagbases, and integrations. This enables retrieval augmented generation, reduction in hallucinations, semantic search, and other vector similarity applications out-of-the-box.

Supported Files

Klu supports a variety of file types across different categories. Below you'll find a table listing all supported file extensions, which you can refer to when uploading content to the platform. If your file type is not listed, please contact the Klu team for assistance. Please note: old versions of Office files and scanned documents in PDFs are known for lower performance.

CategoryFile Type Extensions
Audio / Video.mp3, .mp4
Documents.pdf, .rtf, .txt
Email Files.eml, .msg
Images.png, .jpg
Markup/Structured Text.md, .html, .rst, .org, .xml
Office Documents.doc, .docx, .xlsx, .xls, .ppt, .pptx, .odt
Structured Data.csv, .tsv

Supported Integrations

Klu integrates with an array of platforms for use as Context. Below is a detailed list of all the supported integrations, categorized by their use case. If you require integration with a platform not listed here, please reach out to the Klu team for further assistance.

CategorySupported Platforms
CollaborationGoogle, MS Teams, Slack, Zoom
Customer PlatformsIntercom, Salesforce, Zendesk
ProjectsAirtable, Asana, Atlassian, Github, Notion
Websites (Crawling)HTML, Sitemap
SQL DatabaseMySQL, PostgreSQL, SQLite, Oracle, SQL Server
RedisAll data types (string, list, set, zset, hash)
ElasticAll data types
SnowflakeAll data types
YoutubeAll video formats

AI Moat

Teams using Klu establish a defensive moat by making AI capabilities harder to reproduce. By accelerating the build-measure-learn loop, Klu empowers AI Teams to quickly deliver AI-powered capabilities that users love and trust. Klu provides the tooling for rapid experimentation and evaluation, while engineering teams focus on their domain expertise to delight their users.

The more an AI Team iterates, the more fine-tuned the AI becomes to their use case and users' preferences.



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