FRONTEND · BACKEND · DB · AUTH
Complete Codebase
Frontend, backend, database layer, API routes, auth — all wired together and working
8080-ai-platform
by
Guneet Bajaj
Guneet BajajCopy and clone 8080.ai platform and provide system design and development and same output.
Comments (0)
Sign in to leave a comment
F(X) DATA LABS · AGENTIC AI FACTORY
Models, routedby the factory
Every project's model calls are routed through a multi-model gateway, so model choice is managed by the platform.
- Kubernetes-Native
- 100M Token Context
- Production architecture from day one
- 24+ hours continuous
- 0 babysitting needed
- ∞ scalability
Models · Gateway
Available models
Every project’s model calls route through the multi-model gateway, so model choice is managed by the platform rather than wired in by hand.
General reasoning
Planning and architecture — turns requirements into the system design the factory builds against.
Planning · ArchitectureLong context
Navigates sprawling codebases across a 100M token context so agents keep the whole system in view.
100M token contextCode-specialized
Generation and editing — writes and revises source across frontend, backend, and infrastructure.
Generation · EditingFast drafting
Chat and document processing — quick turns for interface responses and documentation passes.
Chat · DocumentsVision
Visual testing and replay — reads rendered output during continuous QA and visual regression.
Visual testing · Replay
Routing
Routing is managed by the platform. Flat-cost models keep cost predictable across the gateway.
Multi-model gateway
How routing works
The multi-model gateway manages model choice, so a project does not pin itself to a single provider.
Request
A project’s model call enters the gateway.
Route
The gateway selects the model family for the task.
Return
Results return to the build.
- FLAT-COST MODELSPricing stays predictable as models are swapped.
- AI ENGINEER AGENTWires model endpoints, APIs, and data stores.
- 100M TOKEN CONTEXTLets agents navigate sprawling codebases.
F(X) DATA LABS · AGENTIC AI FACTORY
Start building with the model layer
The factory is reachable through a free account. Create one to open a workspace where the multi-model gateway routes work across your projects.
F(X) DATA LABS · AGENTIC AI FACTORY
A team of AI engineers that build, test, document, and debug production-grade software — so you ship what matters.
Platform scale capabilities
Three agents · three branches
Three agents, three branches — merged by pull request
Each task fans out across parallel agent branches. Every branch lands as a pull request, so the merge point stays a human-readable gate rather than a hidden hand-off.
Agentic flow · approval gates
Human control at every gate
Work moves through five observable stages — from a queued task to a merged pull request — and nothing crosses a gate without a human decision.
To Do
A task is scoped and queued before any agent branch opens.
AI In Progress
An agent works its own branch — architecture, code or QA in parallel.
Human In Progress
You step in at the approval gate to direct, adjust or take over.
Review
The branch is opened as a pull request, scanned, and readied for merge.
Done
Merged to the project and carried forward in persistent project memory.
- To Do
- AI In Progress
- Human In Progress
- Review
- Done
Swipe to trace the flow →
Branch per task · Security scan per task · Merged by pull request
Output · Every task
What ships.
05 deliverables
UNIT + INTEGRATION
Test Suite
Unit and integration tests with 80%+ coverage
CONTAINERS · HELM
Docker & Kubernetes artifacts
Dockerfiles, docker-compose, Helm charts, health checks
API DOCS · README · ARCHITECTURE
Documentation
API docs, README, architecture overview
GITHUB ACTIONS
CI/CD Pipeline
GitHub Actions workflows for build, test, lint, deploy
Trust
Trust posture
Certifications & compliance05
- ISO 9001
- ISO 27001
- SOC 2
- GDPR-ready
- HIPAA-ready
Platform scale · recorded by 8080-ai-platform
Screens generated
Tokens processed
Countries served
Values as published by the platform
Freemium.Flat-cost models.
One price statement. No credit tables, no per-seat arithmetic.
PRICE / MONTHSTART
starting at$4.99 /month(flat-cost models)
Sign up for freeFlat-cost models · Freemium
COMPANY
Built by F(x) Data Labs, Inc, founded in 2016; 10+ years in AI.
Field notes
Reviews
Unavailable in source
Reviews
Reviews are not available yet.
Section · Contact
Contact
This page carries no form, inbox or phone line. Every conversation with 8080-ai-platform begins at one of the two account entry points opposite.
F(X) DATA LABS · AGENTIC AI FACTORY
Signing up is the only step required before your first build.
Audience index
Who it’s for
Built for the people shipping software, not watching a demo — three audiences, one workflow of branches, review and approval.
- Developers
Teams who want the scaffolding, wiring and tests written for them — then review each branch as a pull request and keep control of the codebase.
- Founders
Founders who need production-grade applications without assembling an engineering department first, and who want to watch the work take shape.
- Operations leads
Leads who need the build observable end to end — approving at human checkpoints, reviewing before staging, and seeing what the agents are doing right now.
Agentic AI factory · Capabilities
Features
Agentic AI factory to build a Website, SaaS App, Chat, or Loop.
Full VS Code in the browser, or the 8080 desktop extension.
Three agents, three branches — merged by pull request.
Branch-per-task with PR merging.
Security scan per task.
Managed backend on Kubernetes.
Flat-cost models.
A dedicated AI Engineer agent for wiring model endpoints, APIs and data stores.
Your own Kubernetes namespace per project.
Multi-model gateway.
Isolated workspaces.
Auto-scaling infrastructure.
Architecture-first: system requirements document, microservice design, database schemas, API contracts and evolving component diagrams.
Persistent project memory across sessions.
Workflow · 04 stages
How it works
One continuous line from your idea to running software — architecture first, agents in parallel, human review at the gates.Describe → Plan → Build → Ship
- 01You
Describe
State the idea in plain language — the website, SaaS app, chat or loop you want built.
- 02AI agents
Plan
Agents decompose the idea into architecture, tasks and milestones before any code is written.
- Architecture
- Microservices
- API contracts
- 03AI agents
Build
Parallel multi-agent execution across frontend, backend, infrastructure and tests.
- Frontend
- Backend
- Infra
- Tests
- 04Deployment
Ship
Dockerized, tested and documented — a production-ready deployment.
- Docker
- Kubernetes
Human-in-the-loop
Humans + AI
Approval gates and human review controls preserve human control over agent work. The named AI agents act on behalf of the Platform User and surface their work for human review.
ControlHuman approval gates
Agent roster
- Tech Lead
- System Architect
- Project Manager
- Frontend
- Backend
- DevOps
- Designer
- QA
F(X) DATA LABS · Operating principles
Why 8080
Four rules govern how the agents plan, build and hand over software — in that order, every time.
- 01POSITION
Opinionated, Not Rigid
- 02OBSERVE
Observable by Default
- 03SIGNAL
Fail Loudly
- 04ARCHITECT
Human-First Architecture
No comments yet. Be the first!