Orchestrate Autonomous Agents. Ship Complex Software in Real-Time.
The developer-first AI workspace uniting configurable multi-agent swarms, instant reactive code artifacts, deep web & document RAG with Jina Reader, and visual architecture graphs.
User Intent:
"Construct a real-time portfolio risk computation engine with interactive VaR metrics, live WebSockets stream, and full TypeScript typings."
Task decomposed into 3 concurrent sub-agents:
`GET https://r.jina.ai/https://finmath.net/risk-metrics/parametric-var`
Extracted: 99% confidence horizon formula, Cholesky covariance matrix decomposition routines.
Generated RiskMatrixWidget.tsx. Interactive React component rendered on live artifact canvas with hot reload.
Quantum Risk Matrix
Live portfolio volatility simulation
Powered by Frontier Foundation Models & Modern Enterprise Infrastructure
Engineered for Deep Autonomy. Built for Modern Builders.
Say goodbye to copy-pasting chat messages. Thinking Machine provides a reactive studio where autonomous agents cooperate to deliver working, verified software.
Autonomous Multi-Agent Swarms
Orchestrate specialized sub-agents working concurrently. An Orchestrator plans the trajectory, a Researcher browses real-time APIs via Jina, a Coder synthesizes code, and a Critic verifies syntax and edge cases.
Live Reactive Artifacts
Code isn't just text in a box. Thinking Machine compiles and renders React components, interactive HTML widgets, Mermaid schemas, and code side-by-side in a sandboxed side panel.
Deep Web & Document RAG
Powered by Jina Reader integration. Feed any URL, PDF, or documentation site into the swarm to extract clean markdown, compute embeddings, and search with semantic precision.
Visual Flow Canvas (xyflow)
Inspect complex agent pipelines, database entity relationships, and tool routing visually. Drag, zoom, and inspect data flows in an interactive node-graph canvas.
Model Agnostic Routing
Switch seamlessly between Anthropic Claude 3.5, OpenAI GPT-4o, DeepSeek, Google Gemini, or local Ollama endpoints with zero codebase modification.
Test the Swarm in Real-Time. Pick a Mission.
Experience how the autonomous agents break down goals, pull external documentation with Jina, and generate tested code artifacts.
"Build a production-grade Stripe webhook handler with signature verification, Clerk user metadata sync, and idempotent Redis caching."
Decomposed webhook validation pipeline into 3 concurrent verification tasks.
Scraped Stripe API docs: verified signature construction & header formatting.
Synthesizing app/api/webhooks/stripe/route.ts with raw request body verification.
Audited for replay attacks and timing leaks. Passed with 0 vulnerabilities.
import { headers } from 'next/headers';
import { stripe } from '@/lib/stripe';
import { clerkClient } from '@clerk/nextjs/server';
export async function POST(req: Request) {
const body = await req.text();
const signature = (await headers()).get('stripe-signature')!;
// 1. Cryptographic Signature Validation
const event = stripe.webhooks.constructEvent(
body,
signature,
process.env.STRIPE_WEBHOOK_SECRET!
);
// 2. Synchronize Customer State with Clerk
if (event.type === 'checkout.session.completed') {
const session = event.data.object;
await clerkClient().users.updateUserMetadata(session.client_reference_id!, {
publicMetadata: { tier: 'pro', active: true }
});
}
return new Response(JSON.stringify({ received: true }), { status: 200 });
}How Autonomous Swarms Deliver Production Software
Instead of single-prompt guessing, Thinking Machine breaks down engineering missions into a rigorous, verifiable 4-stage pipeline.
Intent Parsing & Graph Decomposition
Your prompt is deconstructed into a directed acyclic graph (DAG) of specialized tasks with explicit input/output boundaries.
Deep Web & Vector Retrieval (Jina Reader)
The swarm queries documentation sites, API endpoints, and internal project PDF vaults using Jina Reader and semantic embeddings.
Parallel Swarm Synthesis & Verification
Coder agents generate code while Critic agents validate syntax, security vulnerabilities, and typing invariants simultaneously.
Interactive Live Artifact Execution
Code is immediately mounted into a sandboxed React 19 / HTML canvas with hot-reload and visual inspection tools.
Why Builders Choose Thinking Machine
Standard chat interfaces were designed for answering casual questions. Thinking Machine was designed to build software.
| Capability | Legacy AI Chatbots | Thinking Machine |
|---|---|---|
| Execution Model | Single model sequential prompt-response | Concurrent multi-agent swarm with specialized roles |
| Code Output & Artifacts | Static markdown code blocks to copy-paste | Live interactive sandboxed canvas with hot reload |
| Web & Document RAG | Basic web search snippets or file attachment caps | Deep Jina Reader extraction & vector database pipeline |
| Visual Workflow Canvas | No visual architecture or node visualization | Interactive drag-and-drop ReactFlow node graphs |
| Model Choice & Fallback | Locked to a single proprietary vendor | Claude 3.5, GPT-4o, DeepSeek, Gemini & local Ollama |
| Knowledge Organization | Linear unorganized chat list | Dedicated Project vaults with isolated memory & docs |
| Autonomous Verification | User must manually test and debug errors | Built-in Critic agents audit security & syntax first |
Join engineering teams moving from prompt copy-pasting to autonomous agent swarms.
Loved by Builders. Trusted by Engineering Teams.
Discover why forward-thinking software engineers and AI developers build on Thinking Machine.
"The ability to orchestrate Claude 3.5 for high-level planning while DeepSeek generates and verifies the live React artifact cuts our internal prototyping cycle from weeks to minutes."
Dr. Elena Rostova
Staff AI Engineer • Aether Capital
"Integrating Jina Reader directly into the agent reasoning loop is a superpower. Our agents read full Stripe and AWS docs in real-time, completely eliminating outdated hallucinations."
Marcus Vance
Founder & CTO • Synthetix Data
"The live artifact canvas is what chat should have been from day one. Seeing the component render hot in the sandboxed preview while the swarm streams code is pure magic."
Sophia Chen
Head of Developer Experience • ScaleStack Cloud
"We migrated our internal knowledge base to Thinking Machine project vaults. The pgvector ingestion with real-time job progress indicators gave us full visibility into our RAG pipelines."
Kareem Al-Mansoor
Lead Systems Architect • Fintech Core
Simple, Transparent Plans. Scale as You Build.
Deploy multi-agent swarms with predictable, builder-friendly pricing.
Explorer
Free ForeverIdeal for individual developers exploring multi-agent swarms and live artifacts.
- 5 active Project vaults
- Standard multi-agent swarms (up to 3 agents)
- Live interactive sandboxed artifact canvas
- Jina Reader basic web extraction (100 URLs/mo)
- Stream latency: ~0.3s
- Standard community discord support
Pro Builder
Most PopularFor engineers and startups shipping real software with autonomous AI agents.
- Unlimited Project vaults & full chat history
- Priority multi-agent swarms (Claude 3.5 + GPT-4o + DeepSeek)
- Unlimited Jina Reader web RAG & PDF vectorization
- Interactive ReactFlow visual node graph studio
- Hot-reloading code sandbox with 1-click export
- Ultra-low 0.15s stream latency
- Priority developer support & early access features
Autonomous Scale
EnterpriseFor engineering teams requiring dedicated clusters, custom endpoints, and SSO.
- Everything in Pro Builder
- Dedicated isolated agent runner clusters
- Bring Your Own Key (BYOK) & local Ollama routing
- Clerk Enterprise SSO / SAML integration
- Custom agent role definitions & internal tool bindings
- Audit logs, RBAC & SOC2 compliant security
- 99.9% Uptime SLA & dedicated engineer Slack channel
Frequently Asked Questions
Answers to common questions about multi-agent swarms, security, and live artifacts.
Ready to Build at the Speed of Autonomous Intelligence?
Join thousands of developers, researchers, and startups orchestrating multi-agent swarms with live interactive code artifacts.