01 · Assemble
Agentic AI factory to build:
Public Projects
Explore All →
khushboo-s
Yash Shah
gigo-underwear-dealbyethan-gay
Eric Salo
regal-https
Umar FF 12Platform track record
293,150Screens generated
959.1BTokens processed
175Countries served
Explore what people are building in the public gallery.
Made for you
One platform. Five ways in.
Pick who you are - tap a tile to jump to the feature.
Platform
Everything you need to ship
production-grade software.
02 · Design
System Architect Agent. AI that designs clean, scalable architecture before writing a single line of code.
03 · Plan
Project Manager Agent. Built-in task decomposition, sprint tracking, and intelligent prioritization.
04 · Ship
Managed Backend on Kubernetes. Every app gets a real backend - API, database, auth and storage - running in its own managed Kubernetes namespace.
05 · Verify
Visual Testing & Replay. AI-driven testing that sees your app like a real user does.
06 · Control
Integrated Code Editor. Full VSCode editor in the browser - supports every language and framework.
07 · Scale
Auto-Scaling Infrastructure. Your projects scale horizontally without manual intervention.
The process
Not a black box. A process.
Nine steps from one sentence to a running product - a clickable design in as little as two minutes, a security scan on every task, agents do the work, you hold the gates.
- 01
Share your idea
You describeType what you want to build. A project is created instantly, and a supervisor agent decides which specialists to bring in - requirements, design, user flows, architecture, tasks.
- 02
Requirements, written down
You approveThe System Requirements Agent writes your requirements document - the source of truth everything else derives from. Every later change arrives as a diff you accept or reject.
- 03
User flows, mapped
You approveThe User Flow Planner turns requirements into screen-by-screen journeys for every user persona - and the pipeline pauses until you approve them.
- 04
Designs you can click
You approveYour first clickable design preview lands in as little as two minutes. The home page is designed first and sets the style; approve it, and the remaining pages generate in parallel - planned, coded, screenshotted, and checked by an AI design critic.
- 05
Edit it visually
You editClick any element on a design page and change its text, font, size, colours, gradients and borders in an inspector - direct saves write straight to the code and cost no credits. Ask the Design Agent for anything bigger, and preview every page on desktop, tablet and mobile.
- 06
Blueprint and task plan
You approveThe System Architect draws five architecture diagrams; the Project Manager breaks the build into tasks, sprints and phases. Review it all in a guided walkthrough, then press Start Building.
- 07
AI engineers, in parallel
Agents buildEach task runs in its own isolated cloud workspace through a six-phase pipeline - setup, environment, branch, code, tests, staging - and merges into your repo by pull request.
- 08
Security scanned, every task
Agents verifyBefore a task can reach staging, its workspace is scanned for leaked secrets and API keys, vulnerable dependencies and unprotected API routes. Findings land on the task card with a one-click fix run, and Deploy warns until the latest scan is clean.
- 09
Your app, live on a URL
You open itEvery finished task auto-deploys to your project’s own Kubernetes namespace - a managed backend with your API, database and storage already running. Open the live staging URL on any device, or press Deploy to promote the latest build to production.
The same process runs behind every project in the gallery - open one and read its requirements, designs and task board.
Collaboration
Humans and AI. One team.
Set up your org, add your developers, share the board, and hand work back and forth.
Org management, built in
Create an organization, invite by email, and assign owner, admin or member roles. Owners control billing and project access, admins manage people and settings, members build - and every project the org owns is shared with everyone in it.
Multi-developer collaboration
Several developers work on one project at once: each takes tasks from the same board, works in an isolated cloud workspace or the VS Code extension, and merges by pull request into a shared repo - alongside the AI engineers, never blocked by them.
Kanban handoff, human ↔ AI
Work moves across one board whether an agent or a teammate owns it. Assign any task to a human - a decision, a review, an API key - and agents pick the thread back up the moment it lands. List, sprint, Gantt and phase views included.
Humans steer, agents ship
Review gates keep people in control: approve requirements, designs and plans, then agents carry the approved work through code, tests and deployment.
The moat
AI pays a quadratic tax. We removed it.
Flat-cost intelligence for software engineering - built on the models the world already has.
To produce each new word, today's models re-read everything they have read so far: 2× the reading means 4× the cost, 10× the reading means 100× the cost. Nowhere does that tax bite harder than coding - so today's assistants read fragments, forget the rest, and guess.
1M+ tokenswhat a real enterprise codebase measures - far beyond what quadratic models can afford to read
×100 costthe quadratic penalty for reading 10× more code - before a single line is written
2.15× fasterour flat-cost models on long code - and the gap widens as codebases grow
The breakthrough
8080.AI dynamic dense attention (O(n))
Each new word reads a bounded slice of memory, the output is still the exact attention formula, and every token can still reach every other token. Flat cost at any context length, on the models the world already has, with no retraining. And it ships with something no other attention mechanism has: a zero-knowledge proof of its own cost that you can run yourself.
Run the proofThe fix
Flat cost - on models that already exist.
Routed attention: each new word reads a small, relevant slice of memory instead of everything.
Read what matters, not everything
Our routing layer sends each new word to the few places in memory that matter. Work per word stops growing with document size: O(n²) becomes O(n).
Retrofit, not rebuild
We convert leading open models in days - no from-scratch pretraining, no new chips. Every new model release makes us better the week it ships.
Proven on a real model
A 9B open model, converted: flat generation speed at every context we tested - 2.15× faster at 32k, and the gap widens with length.
The multipliers
Three 10× levers. One platform. They multiply.
Orders-of-magnitude better unit economics for AI that writes software.
Context economics
Routed attention makes reading a whole repository affordable - the cost of context stops growing with the square of its size.
Thinking speed
We train models to run ten independent lines of thought inside a single pass, then merge the best into the answer. Reasoning that took ten passes takes one.
Cost per token
A small, cheap model writes most of the code. We read its confidence word by word; the moment it wavers, a large model steps in, fixes, and hands back.
Incumbents answer exploding context demand with GPU capex. Our answer is math - it ships as software, at software margins, and every new open model upgrades us in days. The ecosystem's R&D compounds into our moat.
Trusted
Trusted by leading brands.
Fortune 500s, governments and startups trust the team behind 8080.AI.
The team
Built by developers from
Experience
10+ years of experience in AI.
One of the first AI labs.
8080.AI is built by fxis.ai - F(x) Data Labs, Inc, founded in 2016 - an AI lab shipping data science and machine learning systems long before the AI wave. Every claim on this page is public and verifiable.
10+Years in AI
2016Incorporated, on public record
4.9/5Clutch rating · 65 reviews
Security & compliance
Certified. Isolated. Compliance-ready.
ISO 9001, ISO 27001 and SOC 2 - on an independent Kubernetes stack.
ISO 9001
Quality management system certified - a documented, audited process behind every release and every support ticket.
ISO 27001
Information security management certified - risk assessment, access control and incident response are audited, not promised.
SOC 2
Independently attested controls for security, availability and confidentiality across the platform and the clusters that run your apps.
Independent Kubernetes stack
Your apps run on our own Kubernetes clusters in a namespace per project - not on a shared third-party app backend. Data, secrets and volumes stay inside your boundary.
GDPR ready
Namespace isolation, encrypted volumes, audit logs and per-project data deletion make both 8080.AI and the software it generates ready for GDPR compliance.
HIPAA ready
The same isolated stack gives generated healthcare software an audited, access-controlled home - ready for a HIPAA compliance program and a signed BAA.
Security scan on every task
Before any task reaches staging it is scanned for leaked secrets, vulnerable dependencies and unprotected routes, and Deploy warns while findings remain open.
Certifications cover the 8080.AI platform and its clusters. GDPR and HIPAA readiness describes the controls your generated software inherits; your own compliance program and agreements still apply.
Reviews
Rated 4.9 out of 5 by clients.
Independently verified on Clutch.
“They are truly an incredible company.”
Improved platform usability and AI model accuracy, with exceptional project management and on-time delivery.
“Ability to execute at a high standard on genuinely complex problems.”
Refactored our LLM architecture and shipped new features with clear progress tracking and patient technical explanations.
“They bridge business needs with technical execution.”
Delivered a 30–40% reduction in manual tasks and a 20–25% improvement in lead engagement.
“They understood both business and technology.”
Built a voice AI system that handles customer calls after hours, cutting missed leads and routine phone time.
“Delivered insights reshaping how we plan campaigns.”
An AI-powered marketing suite that improved campaign response rates by 55% and lead conversion speed by 30%.
“Built AI tools that felt practical, not technical.”
A recruitment chatbot that reduced manual screening workload by over 60% with real-time candidate conversations.