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KLabs

KLabs provides DML, a platform that lets product and engineering teams embed AI-driven data applications into existing workflows. It offers tools like a Model Hub, low‑code Prompt Studio, and multi‑agent orchestration to build, deploy, and monitor generative AI components that automate services and personalize customer interactions.

Tel Aviv, IsraelFounded 2025100+ followers
Updated 3 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Many organizations rely on static dashboards that present data without enabling interactive, AI‑driven experiences, limiting their ability to automate processes, personalize customer interactions, and extract actionable insights from complex datasets.

Solution

KLabs offers DML, an end‑to‑end platform for building data‑rich applications that go beyond traditional reporting. The platform provides AI engineering tools such as a Model Hub and Prompt Studio to streamline the creation and deployment of large language model (LLM) components. Integrated generative AI capabilities enable automation of service workflows and personalized customer engagements, helping businesses increase revenue and operational efficiency. Multi‑agent orchestration allows coordinated, context‑aware AI agents to deliver sophisticated, real‑time data solutions that embed directly into existing tools and processes.

Target Audience

Primary customers are product and engineering teams in enterprises that need to embed advanced AI functionality into data‑intensive applications, such as SaaS providers, fintech firms, and customer‑experience platforms.

Features

  • Model Hub for centralized storage, versioning, and deployment of pre‑trained and fine‑tuned LLMs
  • Prompt Studio for low‑code prompt design, testing, and optimization across data‑rich applications
  • Multi‑agent orchestration framework that coordinates multiple AI agents to handle complex, context‑aware tasks
  • Built‑in generative AI modules for automating customer service interactions and personalizing user experiences
  • Seamless integration layer that connects AI components to existing business tools, APIs, and data pipelines
  • Real‑time analytics and monitoring dashboards to track AI performance and business impact
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