EDITOR
- Full VS Code in the browser or the 8080 desktop extension
- Syntax highlighting
- IntelliSense
- Live preview
- Integrated terminal
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
What the factory does
This page inventories the platform’s accepted capabilities — the agentic AI factory, the multi-agent system, the browser-based editor, and the Kubernetes delivery path.
PlatformLive readout
- 328,260SCREENS GENERATED
- 1.310TTOKENS PROCESSED
- 183COUNTRIES SERVED
- Kubernetes-Native
- 100M Token Context
- Production architecture from day one
- 24+ hours continuous
- 0 babysitting needed
- ∞ Scalability
Feature index
Features
The capabilities the factory applies during a build — from the architecture that precedes the first line of code to the PR that merges it.
14 capabilities indexedAgentic AI factory build types
Website, SaaS App, Chat, Loop.
Full VS Code, in the browser or on desktop
A full browser-based VS Code editor, or the 8080 desktop extension.
3 agents, 3 branches
Parallel agent work merged by pull request.
Branch-per-task with PR merging
Every task gets its own branch, merged into the project through a pull request.
Security scan per task
Each task is scanned for security issues before it proceeds.
Managed backend on Kubernetes
A managed backend that runs on Kubernetes.
Flat-cost models
Model usage priced as flat cost.
Dedicated AI Engineer agent
Wires model endpoints, APIs and data stores.
Own Kubernetes namespace per project
Each project runs in its own Kubernetes namespace.
Multi-model gateway
One gateway in front of multiple models.
Isolated workspaces
Projects work inside isolated workspaces.
Auto-scaling infrastructure
Infrastructure scales with the work.
Architecture-first artifacts
System requirements document, microservice design, database schemas, API contracts, evolving component diagrams.
Persistent project memory
Project context persists across sessions.
Architecture first
Architecture before code
The System Architect Agent designs a scalable architecture automatically before a single line of code is written.
Production architecture is established from day one. Artifact generation failures are surfaced loudly, with retry.
Artifact failure — the run halts and reports the failing artifact; retry re-runs the System Architect Agent.
- Draft
- Approval gate
- Build
Multi-agent execution
Three agents, three branches — merged by pull request
The multi-agent system executes in parallel across three branches, from architecture to code to deployment — each agent working its own task while the rest of the system keeps moving.
- Tech Lead
- Architect
- QA
- Pull request
Branch schematic · parallel execution3 agents → 1 merge
Pull requestThree branches · approval gate · one merge
Agent roster
- Tech Lead
- System Architect
- Project Manager
- Frontend
- Backend
- DevOps
- Designer
- QA
- AI Engineer
Each task runs on its own branch. Agent failures are surfaced loudly and retried — nothing merges silently through a failing gate.
Capability · Editor & integration
Edit, wire, and preview
A full browser-based VS Code editor sits alongside a dedicated AI Engineer agent that wires model endpoints, APIs, and data stores through the multi-model gateway.
AI ENGINEER
A dedicated AI Engineer agent wires the model endpoints, APIs, and data stores your app talks to.
- A dedicated agent for wiring model endpoints
- A dedicated agent for wiring APIs
- A dedicated agent for wiring data stores
- Model calls routed through the multi-model gateway
# illustrative example · not a project file model: gateway # multi-model gateway endpoints: chat: "<model-endpoint>" embeddings: "<model-endpoint>" api: upstream: "<your-api>" data: store: "<your-data-store>" owner: "ai-engineer" # wired by the dedicated agent
Compare flat-cost pricing
Model calls routed through the multi-model gateway
Quality & deployment
Test, scan, and ship
Visual testing, continuous QA, security scans, and Kubernetes deployment run against the project itself, so each change is exercised against the application it belongs to.
Test
01 / 04Prove it before it moves
Visual testing, continuous QA, and unit and integration tests run against the project.
Unit + integration · 80%+ coverageScan
02 / 04Check every change
A security scan runs per task and again before anything reaches staging.
Per task · before stagingStage
03 / 04Deploy and verify
The build deploys to Kubernetes staging and is checked in the running environment.
Kubernetes stagingShip
04 / 04Release to production
The verified build deploys to production on Kubernetes when it is ready.
Production
Delivery facts
- Managed backend on Kubernetes, auto-scaling
- Own Kubernetes namespace per project
- Isolated workspaces
- Dockerfiles · docker-compose · Helm charts · health checks
- GitHub Actions: build, test, lint, deploy
Fail loudlyScan or deployment failures are surfaced loudly with retry — nothing is reported as shipped until it has actually passed.
Compliance posture
Trust posture
These certifications and readiness postures are maintained by the platform.
- ISO 9001
- ISO 27001
- SOC 2
- GDPR-ready
- HIPAA-ready
F(x) Data Labs, Inc
F(X) DATA LABS · AGENTIC AI FACTORY
Start building with a free account
Create a free account to reach the factory and put the agents to work on your project.
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
FRONTEND · BACKEND · DB · AUTH
Complete Codebase
Frontend, backend, database layer, API routes, auth — all wired together and working
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!