About Dedalus Labs

Dedalus Labs offers a unified platform for building and deploying AI agents, enabling seamless integration of any LLM with custom or marketplace tools via a single API. This allows developers to create adaptable, multi-model agents with hybrid tooling capabilities and evolve them in real-time without downtime.

<problem> Developing and deploying AI agents often requires complex integration of various Large Language Models (LLMs) and external tools, leading to vendor lock-in and fragmented development workflows. This complexity hinders the ability to create flexible, multi-model agents capable of leveraging diverse functionalities efficiently. </problem> <solution> Dedalus Labs provides a unified platform for building and deploying AI agents, enabling seamless integration of any LLM with custom or marketplace tools through a single API. This facilitates the creation of adaptable, multi-model agents with hybrid tooling capabilities, allowing developers to orchestrate diverse AI functionalities. The platform supports live agent evolution, enabling real-time updates to tools and logic without downtime. Developers can leverage a rich ecosystem of Model Context Protocol (MCP) servers from a marketplace or deploy their own, creating specialized agents for tasks ranging from legal analysis to financial trading and code architecture. </solution> <features> - Universal Model Access: Integrates with any LLM (e.g., OpenAI, Claude, Gemini, Llama) via a single API, allowing for dynamic model switching and optimization. - Hybrid Tooling: Supports the combination of custom Python functions with a marketplace of pre-built MCP tools for extended agent capabilities. - Live Agent Evolution: Enables hot-reloading of custom functions and instant access to new marketplace tools for real-time agent adaptation with zero downtime. - MCP Marketplace: Provides access to a catalog of pre-built tools for tasks such as web search, document processing, code execution, and image generation. - Managed Runners: Offers a pay-as-you-go compute environment for hosting MCP server logic. - Serverless Deployment: Facilitates instant deployment and infinite scaling of agents without requiring manual DevOps management. - Unified Observability: Provides integrated telemetry for monitoring all models and tools within an agent. - Python and JavaScript/TypeScript SDKs: Simplifies agent creation and integration for developers. </features> <target_audience> The primary target audience includes AI developers, startups, and organizations building and deploying AI agents that require flexibility in model selection and tool integration. </target_audience> <revenue_model> Revenue is generated through a tiered subscription model (Hobby, Pro, Enterprise) with additional pay-as-you-go charges for gateway tokens, managed runners, and a platform rake on paid tools sold in the MCP Marketplace. The Pro tier is priced at $20 per developer per month, with token usage billed at Vendor Cost + $0.0025 per 1K tokens. </revenue_model>

What does Dedalus Labs do?

Where is Dedalus Labs located?

Dedalus Labs is based in San Francisco, United States.

When was Dedalus Labs founded?

Dedalus Labs was founded in 2025.

Location

San Francisco, United States

Founded

2025

Employees

2 employees

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Dedalus Labs

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Executive Summary

dedaluslabs.ai 100+

Founded 2025 – San Francisco, United States

Funding

No funding information available.

Team (<5)

No team information available.

Company Description

Problem

Developing and deploying AI agents often requires complex integration of various Large Language Models (LLMs) and external tools, leading to vendor lock-in and fragmented development workflows. This complexity hinders the ability to create flexible, multi-model agents capable of leveraging diverse functionalities efficiently.

Solution

Dedalus Labs provides a unified platform for building and deploying AI agents, enabling seamless integration of any LLM with custom or marketplace tools through a single API. This facilitates the creation of adaptable, multi-model agents with hybrid tooling capabilities, allowing developers to orchestrate diverse AI functionalities. The platform supports live agent evolution, enabling real-time updates to tools and logic without downtime. Developers can leverage a rich ecosystem of Model Context Protocol (MCP) servers from a marketplace or deploy their own, creating specialized agents for tasks ranging from legal analysis to financial trading and code architecture.

Features

Universal Model Access: Integrates with any LLM (e.g., OpenAI, Claude, Gemini, Llama) via a single API, allowing for dynamic model switching and optimization.

Hybrid Tooling: Supports the combination of custom Python functions with a marketplace of pre-built MCP tools for extended agent capabilities.

Live Agent Evolution: Enables hot-reloading of custom functions and instant access to new marketplace tools for real-time agent adaptation with zero downtime.

MCP Marketplace: Provides access to a catalog of pre-built tools for tasks such as web search, document processing, code execution, and image generation.

Managed Runners: Offers a pay-as-you-go compute environment for hosting MCP server logic.

Serverless Deployment: Facilitates instant deployment and infinite scaling of agents without requiring manual DevOps management.

Unified Observability: Provides integrated telemetry for monitoring all models and tools within an agent.

Python and JavaScript/TypeScript SDKs: Simplifies agent creation and integration for developers.

Target Audience

The primary target audience includes AI developers, startups, and organizations building and deploying AI agents that require flexibility in model selection and tool integration.

Revenue Model

Revenue is generated through a tiered subscription model (Hobby, Pro, Enterprise) with additional pay-as-you-go charges for gateway tokens, managed runners, and a platform rake on paid tools sold in the MCP Marketplace. The Pro tier is priced at $20 per developer per month, with token usage billed at Vendor Cost + $0.0025 per 1K tokens.