10+ agents working in parallel

Not an assistant.
An engineering team.

CrewCode deploys specialized AI agents that architect, build, test, and ship production-grade software. One prompt. Full team. Real infrastructure.

Try Demo →
crewcode session
$ crewcode build "SaaS billing platform with Stripe"
 
[Architect] Generating System Requirements Document...
[Architect] Designed 4-service microservice architecture
[PM] Decomposed into 23 tasks across 3 sprints
[Backend] Building payment-service with Stripe webhooks
[Frontend] Scaffolding dashboard with billing components
[DevOps] Provisioning K8s cluster with staging + prod
[QA] Running visual tests with browser automation
 
6 agents active | 147 files changed | 12,847 tokens/sec
The Crew

Every agent has a specialty.
Together, they ship.

No single AI can do everything well. CrewCode assigns the right agent to the right job, with supervisor-based routing and parallel execution.

SA

System Architect

Designs multi-tier microservice architectures from natural language. Generates SRDs, database schemas, API contracts, and component diagrams before a line of code is written.

architecture-first
PM

Project Manager

Breaks high-level descriptions into granular tasks. Tracks sprints on a Kanban board. Parallelizes independent work across agents for maximum throughput.

task-decomposition
FE

Frontend Engineer

Builds responsive, accessible UIs with modern frameworks. Integrates with design systems, handles state management, and delivers pixel-perfect implementations.

ui-components
BE

Backend Engineer

Implements APIs, business logic, database models, and integrations. Writes production-grade code that passes review, not just demos.

api-services
DO

DevOps Engineer

Deploys to Kubernetes with staging and production clusters. Handles Docker containerization, persistent volumes, and auto-scaling out of the box.

k8s-native
QA

Visual QA

AI-driven testing that sees your app like a real user. Browser automation, session replay, screenshot comparison, and full test generation across unit, integration, and E2E.

visual-verify
Why CrewCode

Everyone else builds tools.
We built the team.

10+

Parallel Agents

Multiple specialized agents stream simultaneously with supervisor-based routing and automatic retry.

100M

Token Context

Agents run for hours on massive codebases. No context window limitations. Your entire project, held in mind.

K8s

Production Infrastructure

Stage and production Kubernetes clusters deployed automatically. Not localhost demos. Real infrastructure.

SRD

Architecture First

System Requirements Documents, API contracts, and database schemas are designed before implementation begins.

Comparison

Single agents can't build systems.

Here's how CrewCode compares to tools that rely on one AI doing everything.

Capability IDE Tools Single Agents CrewCode
Multi-agent orchestration ✗ ✗ ✓ 10+ agents
Architecture design (SRD) ✗ ✗ ✓ Auto-generated
Kubernetes deployment ✗ ✗ ✓ Stage + Prod
Parallel streaming ✗ ● Limited ✓ Full parallel
Visual testing / replay ✗ ✗ ✓ AI-driven
Integrated cloud IDE ✓ ✗ ✓ Full VSCode
100M+ token projects ✗ ● Some ✓ Built for scale

The future of software isn't one AI writing code.
It's a crew shipping products.

Architecture designed before the first line. Agents that specialize, not generalize. Infrastructure that deploys itself. CrewCode is what happens when you stop asking AI to autocomplete and start letting it engineer.

Watch the Crew Build →