Lepton Search

Lepton search is an open-source, cloud-native platform designed to empower developers and Enterprises to build, deploy, and customize Conversational AI search experiences. Developed by Lepton AI — a team led by fORMer Alibaba VP Yangqing Jia — it bridges the gap between traditional information retrieval and modern Generative AI. Unlike static search bars or closed commercial tools, Lepton Search provIDEs a flexible foundation where users can orchestrate LLM reasoning, external search API calls (e.g., Bing), result caching, UI Customization, and multi-step dialogue flows — all from a single, extensible architecture.

What it does

Lepton Search functions as a programmable AI Search layer: it accepts natural language questions, routes them Intelligently across retrieval systems and language models, synthesizes answers contextually, and presents results through customizable interfaces. It supports both real-time query answering and peRSIstent APPlication deployment — meaning users can spin up dedicated search bots, internal knowledge assistants, or domain-specific Q&A services without rebuilding infrastructure from scratch.

Key capabilities

• Conversational search interface: Enables natural-language interACTion instead of keyword-based queries, supporting follow-up questions and contextual memory within sessions.
• LLM + search hybrid pipeline: Integrates large language models for understanding and generation while delegating factual grounding to live search engine APIs.
• UI customization: Developers can tailor front-end appearance, layout, and behavior using built-in configuration or Embedded web components.
• Result sharing and caching: Supports saving, sharing, and reusing search outcomes — improving consistency and reducing redundant computation.
• Cloud-native deployment: Runs natively on Lepton AI’s infrastructure, offering auto-scaling, versioned deployments, and API-first access for integration into larger Workflows.

Who it is for

Lepton Search targets technical users — especially developers, AI engineers, and product teams — who need full control over how search and AI interact. It’s ideal for organizations building internal knowledge bases, customer-facing support bots, research assistants, or vertical search tools where transparency, customization, and open governance matter more than turnkey simplicity.

How to get started

Getting started requires bASIc familiarity with command-line tools and Python. Users can clone the open-source repository, configure search backends and LLM endpoints, then deploy locally or to Lepton AI’s cloud platform via CLI commands. documentation includes Sample configurations, UI theme guides, and integration patterns for common use cases like RAG pipelines or multi-turn chat Agents.

Pricing and access caveat

The core platform is free and Open Source under permissive licensing. Hosting on Lepton AI’s cloud may involve usage-based compute fees, though self-hosting options exist. The official web interface at search.lepton.run offers a public dEMO, but production deployments require setup and configuration. Version numbers, exact pricing tiers, and enterprise SLAs are not publicly specified and may vary based on deployment mode and scale.