Synty · AI Developer Platform
An AI platform that turns plain-language requirements into fully built, deployed applications.
The Client
Synty is an in-house AI platform that transforms plain-language requirements into fully built, deployed applications. An orchestrator agent coordinates a team of specialized agents, from planning to deployment, that build, preview, and ship production-grade projects in minutes.
Category
AI Developer Tools
Sector
AI App Generation
The Challenge
Turn a sentence into a shipped application.
Building software the traditional way means assembling a team across planning, architecture, design, development, QA, and deployment, which adds up to weeks of coordination before anything ships. Synty set out to collapse that entire lifecycle into a single prompt. The platform had to interpret vague, plain-language requirements, make sound architectural decisions, generate production-quality code across multiple language stacks, validate it, and deploy a running application, all autonomously, reliably, and fast enough to feel interactive.
From a single sentence to a deployed application, built by a pipeline of autonomous agents.
The Solution
A pipeline of autonomous agents, prompt to production.
Synty orchestrates a chain of specialized AI agents, each owning a stage of the lifecycle: planning, architecture, design, development, QA, and deployment, with every stage routed to the best-fit model across Claude, Gemini, and GPT. Under the hood it runs as a microservice architecture of a Next.js front end and Python FastAPI services that communicate over Kafka, with arq distributed background jobs handling generation, builds, and deployments across every service. Generated code is built and previewed inside isolated VMs before shipping, with progress streaming back to the user in real time.
Technology Stack
A microservice architecture of Next.js and Python FastAPI services, connected by Kafka event streaming and arq distributed background jobs across every service, a multi-model agent pipeline across Claude, Gemini, and GPT, isolated VMs where each application is built and previewed, and automated deployment to the cloud.
Claude AI
Each stage of the pipeline is handled by a specialized agent backed by the best-fit large language model. Anthropic Claude (via Vertex AI) anchors planning, architecture, and code generation, with Gemini and GPT available as alternative providers. An orchestrator coordinates the agents and their sub-agents, passing structured context between stages so decisions made upstream inform the code produced downstream.
Results & Impact
Outcomes that hold up under load.
- Microservice architecture of Next.js and Python FastAPI services, connected by Kafka and arq background jobs across every service
- Autonomous multi-agent pipeline taking a plain-language prompt to a deployed application
- Six specialized agents covering planning, architecture, design, development, QA, and deployment
- Multi-model orchestration routing each stage across Claude, Gemini, and GPT
- Real-time build and deployment logs streamed to the user over an SSE event bus
- Generated projects spanning Next.js, React, FastAPI, Node, Java, and Kotlin stacks
- Isolated VMs where each app is built and previewed before one-click deployment to the cloud
6
Autonomous agents orchestrated end-to-end
8
Frameworks generated across stacks
Minutes
From prompt to live deployment
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