Prompt-to-app generation
A plain-language brief produces a structured, running project, because time-to-first-preview is what retains creators.
AI-Built Bolt New Clone
Build a Bolt New Clone Platform
An AI-first build of every Bolt New mechanic, which is fitting: streaming prompt-to-app generation, sandboxed live previews, error-aware recovery, and a model router that protects your margins per tier. Three synced panels ship white-label with 100% source code, owned by you from day one. The almost-ready AI build goes live in 6 working days; a custom build takes 3 to 4 weeks.
Launch-ready from
$3,699
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- Live in 6 working days
- 60 days support
- Complete source codes
- Complete rebranding
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Trusted by the brands we build for
Moxace AI platforms by the numbers
Canonical facts behind every build.
- /012010Operating Since15+ years shipping apps
- /029,000+Projects Deliveredacross 35+ industries
- /033,900+Apps Publishedin 25+ countries
- /04120+AI Products in Production98% model accuracy
overview
What is a bolt new clone?
A Bolt New clone is a prompt-to-app platform: users describe software in plain language, a model generates a running project with live preview, and iteration continues by conversation until the app deploys.
Its purpose is to sell software creation as a subscription. The buyer market is enormous, everyone who wants an app but cannot code, and the operator's economics hinge on token metering and model routing rather than headcount.
The platform includes the creator workspace with streaming generation and sandboxed previews, a team panel for agencies and client handover, and an admin console covering quotas, model routing, cost controls, and sandbox monitoring.
AI app generation moved from novelty to product category within a very short span, and demand is visible in how quickly usage-based plans have been adopted across the space. A clone positions you inside that demand with your own token pricing, your own brand, and no dependency on a foreign platform's quotas.
Main features of our bolt New-style platform
The summary layer above the role panels.
Streaming code with live preview
Generated code streams as diffs into a sandboxed container while the model is still working.
Conversational refinement
Follow-up prompts apply targeted edits to the existing project instead of regenerating it from scratch.
Error-aware recovery
Preview failures feed back into the loop with one-click fix suggestions, so a broken build is a checkpoint away.
Sandboxed isolation
Every preview session runs in an isolated container with lifecycle limits and no cross-tenant access.
Token-based billing
Generation and refinement meter against plan quotas, with per-tenant cost visible in the admin console.
Model routing with failover
Provider-agnostic routing balances cost and quality per tier, so provider price changes never break your unit economics.
Code export and handover
Users own and can export their generated code, the trust signal that separates serious platforms from lock-in traps.
Who should launch a bolt New-style platform?
What these buyers share: an audience that wants software without hiring engineers, and a reason to own the generation pipeline.
AI-native SaaS founders
Building the category's next consumer brand, with token economics and routing under their own control instead of a foreign platform's quotas.
Developer-tool companies
Extending up-market from infrastructure into creation, where prompt-to-app is the natural top of the funnel.
Agencies productizing delivery
Letting non-technical clients brief and iterate on apps inside your sandboxed workspace, then handing over real code.
Education and incubator networks
Teaching software creation in exactly the sandboxed, checkpointed environment the platform provides.
Enterprise innovation teams
Running internal builders under their own brand with data boundaries the public tools cannot promise.
Feature panels of your bolt New-style platform
Three panels, one AI builder. Every build ships all of them.
Creator workspace
From prompt to running app in one canvas.
- ✓Prompt-to-app project generation
- ✓Streaming code generation with diffs
- ✓Live sandboxed preview on every change
- ✓Error-aware fix suggestions
- ✓Chat-based iterative refinement
- ✓Project file tree and editor
- ✓Version history and checkpoints
- ✓One-click deploy to hosting
- ✓Custom domain attachment
- ✓Project templates by app type
Team panel
For agencies and teams building for clients.
- ✓Shared workspaces and projects
- ✓Role-based member access
- ✓Client handover with code export
- ✓Project usage dashboards
- ✓Comment and review threads
- ✓Deploy previews per branch
Admin panel
Run the AI economics, not just the servers.
- ✓Plan and token quota management
- ✓Model routing and cost controls
- ✓AI quality and success-rate monitoring
- ✓Sandbox resource monitoring
- ✓Abuse and prompt-policy enforcement
- ✓Tenant usage metering reports
- ✓Billing and invoicing
- ✓Model provider failover config
- ✓Audit logs and exports
The admin control plane: running the AI builder as an operator
Four consoles, one view of creators, models, and money.
Token and plans console
Plan and token quota management with rollover rules, tenant usage metering reports, and per-tier model selection shaping the margin lever.
Models and quality console
Model routing and cost controls with provider failover configuration, AI quality and success-rate monitoring, and generation telemetry per tenant.
Sandbox console
Sandbox resource monitoring with per-session lifecycles, resource-envelope alerts, and recycling policy administration keeping the fleet healthy.
Trust and billing console
Abuse and prompt-policy enforcement, rate-limited endpoints with audit logs, and billing and invoicing across tokens, seats, and hosting.
How the AI builder works: prompt to deployed app
The loop every creator runs, from first sentence to live URL.
01
Describe the app
The creator writes a plain-language brief and the platform scaffolds a structured project rather than a blank editor.
02
Watch the first preview
Generated code streams as diffs into a sandboxed container, and a live preview appears while the model is still finishing.
03
Refine by conversation
Follow-up prompts produce targeted diffs against the existing project, so the app grows instead of being regenerated from scratch.
04
Recover from errors
When a preview breaks, the error feeds back into the generation loop with one-click fix suggestions instead of a dead end.
05
Deploy to hosting
A working build publishes to per-tenant hosting with automated SSL, and a custom domain attaches without leaving the workspace.
06
Track tokens and export
Generation and refinement tokens meter against the plan in real time, and the creator can export the codebase at any point because they own it.
AI inside the platform
Five model-driven systems working the same generation stream. Each ships pre-tuned for prompt-to-app workloads and sharpens as your data compounds.
Prompt-to-app generation
Turns a plain-language brief into a structured, running project by orchestrating prompts, diffs, and scaffolding templates.
Reads
User brief, project context, successful build patterns
Changes
Time-to-first-preview measured in seconds, the retention metric
Error-aware recovery
Reads preview failures and produces targeted fixes inside the generation loop instead of leaving creators stuck.
Reads
Build errors, runtime logs, fix history
Changes
Broken builds that become one-click checkpoints
Model router
Chooses providers per request by cost and quality with automatic failover and per-tier model selection.
Reads
Request type, provider pricing, latency and quality signals
Changes
Margins that survive provider price moves
Usage intelligence
Projects token consumption per tenant from behavior so quota tiers and pricing track real economics.
Reads
Token history, plan limits, project complexity
Changes
Pricing decisions made on evidence, not averages
Sandbox anomaly detection
Watches sandbox behavior for abuse patterns and resource escapes across thousands of concurrent sessions.
Reads
Resource envelopes, network patterns, session telemetry
Changes
Multi-tenant generation that stays safe at scale
platform concepts
Concepts behind a Prompt-to-app platform
The first concept is the project as a persistent artifact. The orchestrator treats every request as an edit against the current codebase, applying streamed diffs idempotently, so a retried prompt never duplicates a file and a refined app stays coherent as it grows. Checkpoints let creators roll back to any prior state.
The second is sandboxing as a trust boundary. Each preview session runs in an isolated container with a lifecycle limit and no cross-tenant network access, which is what lets thousands of strangers execute generated code next to each other. Sandboxes recycle automatically, and the admin panel watches their resource envelopes continuously.
The third is token economics. Generation and refinement requests meter against plan quotas at the request level, while the model router chooses providers by cost and quality per tier with automatic failover. That routing decision, not server count, is the margin lever, and it stays admin-configurable as provider prices move.
Feature groups that decide whether prompts become apps
Four groups, each mapped to the part of the prompt-to-app promise it protects.
Generation orchestrator
Every request treated as an edit against the current codebase with streamed diffs applied idempotently, so a retried prompt never duplicates a file and a refined app stays coherent as it grows, with checkpoints rolling back to any prior state.
Sandboxed previews
Every preview session runs in an isolated container with a lifecycle limit and no cross-tenant network access, which is what lets thousands of strangers execute generated code next to each other safely.
Deploy pipeline
Generated projects build and publish to per-tenant hosting with automated SSL, so the path from prompt to a live URL runs inside the platform rather than out to a terminal.
Token economics
Generation and refinement requests meter against plan quotas at the request level, with the model router choosing providers by cost and quality per tier and failing over automatically, the routing decision that is the category's margin lever.
insight
The market numbers behind the Prompt-to-app opportunity
AI app builders and low-code platforms keep compounding past the hundred-billion-dollar mark globally by 2030 on widely published forecasts, with prompt-to-app the fastest-moving edge: non-developers now generate working software, and the tools that keep generated code coherent win the category.
The wedge is orchestration quality and token economics: idempotent diff application and sandboxed previews are what make generated code trustworthy, and model routing per tier is the margin lever that decides profitability as provider prices move. The revenue table below quantifies the lines.
Revenue lines, typical ranges, and what sets each ceiling
Six monetization lines across the platform, quantified against published industry benchmarks. Every rate is admin-configurable; the figures here are modelling inputs, not projections of your platform's earnings.
| Criteria | Revenue line | How it is charged | Typical range | What sets the ceiling |
|---|---|---|---|---|
| Token subscriptions | Monthly token tiers with rollover rules | Plans commonly $20 to $200+ per month | Generation quality. Tiers hold while outputs stay usable | |
| Usage metering | Tokens, sandbox runtime, project hosting | Metering commonly $0.01 to $0.10+ per unit | Builder intensity. Usage scales while quotas stay fair | |
| Team and agency seats | Seats with client handover and code export | Seats commonly $30 to $150+ per user per month | Agency adoption. Seats hold while handovers stay clean | |
| Hosting subscriptions | Per-project hosting with SSL and domains | Hosting commonly $5 to $50+ per project per month | Deploy quality. Hosting sticks while apps stay live | |
| Model cost margin | Margin between token price and provider cost | Margins commonly 30% to 70% of token spend | Routing discipline. Margin holds while the router balances cost and quality | |
| White-label deployments | Branded instances for agencies and verticals | Deployments commonly $10,000 to $100,000+ | Vertical demand. Deals close while per-tenant config stays cheap |
How your AI builder platform earns
Token-based subscription tiers: free monthly tokens, paid tiers with higher ceilings, and rollover rules you control.
Usage metering on generation tokens, sandbox runtime, and deployed project hosting, enforced automatically at plan limits.
Team and agency seats billed separately from individual creators, with client-handover and code-export gated to business plans.
Every rate and quota is admin-configurable, and model routing lets you balance quality against provider cost per tier, which is the margin lever in this category.
Every build ships with
Standard inclusions on every engagement, almost-ready or custom. Nine things you never have to ask for.
100% source code, full IP
The complete unencrypted codebase transfers to you, with documentation and deployment scripts.
White-label branding
Your logo, colors, and store accounts across all three panels, plus branded workspace UI.
Store submission and launch
App store and Play Console submissions for the companion apps, with production monitoring switched on.
Payment integrations
Stripe, PayPal, and regional gateways configured for token-tier and seat billing across your creator base.
AI models Pre-tuned
Generation, recovery, and routing arrive configured for prompt-to-app workloads, not as raw APIs.
Multi-language and Multi-currency
Languages, currencies, and tax display configured for your markets during the launch window.
Scalable cloud infrastructure
Firecracker-class sandbox clusters and per-tenant hosting on AWS or GCP with autoscaling.
Admin analytics and reports
Token cost dashboards, sandbox monitoring, and CSV exports so your team starts informed on day one.
Post-launch support and updates
Included support window plus product updates covering bug fixes, model upgrade assistance, and version upgrades.
Engineering behind the platform
Prompt-to-app is an orchestration problem. We build the plumbing seriously.
Generation orchestrator
Structured prompts, streamed diffs, and retry logic that keep the model editing a coherent project instead of regenerating files from scratch.
Sandboxed previews
Firecracker-class container isolation with per-session lifecycles, so every user gets a live preview that cannot touch neighbors.
Payments and metering
Token tiers and usage enforced at the request level, billed through Stripe, PayPal, and regional gateways with per-tenant cost visibility.
Model router
Provider-agnostic routing with cost and quality weighting, automatic failover, and per-tier model selection, so provider price changes never break your unit economics.
Deploy pipeline
Generated projects build and publish to per-tenant hosting with automated SSL. For AI depth beyond the clone, see AI agent development.
Security and compliance
Sandbox isolation, prompt-policy enforcement, rate-limited endpoints, and audit logging come standard, so abuse questions have answers before they are asked.
Your launch timeline: first generated app in 6 working days
The almost-ready AI build, day by day. Store review times can add a short buffer outside our control.
- 01
Days 1-2: scoping and branding
Token tiers, model mix, and sandbox capacity locked with a written scope, and your identity applied across workspace and admin.
✓ step 01 complete - 02
Days 3-4: configuration and integration
Model providers, quotas, billing, and failover configured and tested against your live accounts.
✓ step 02 complete - 03
Days 5-6: orchestration hardening and pilot
Prompt templates, diff application, and sandbox recycling tested under load, then a pilot generating, refining, and deploying real apps including a failing-state recovery path.
✓ step 03 complete - 04
Days 7-9: store review and go live
App store submissions with review buffers accounted for, production monitoring on, and full launch with post-launch support and product updates included.
✓ step 04 complete
Almost-ready AI launch or custom build: the honest comparison
Both tracks ship the same generation core. The difference is time, price structure, and how much you want to change.
| Criteria | Almost-Ready AI Launch | Custom Build |
|---|---|---|
| Time to live | 6 working days from branding handoff | 3 to 4 weeks, scoped before work starts |
| Pricing | Fixed written quote after a short scoping call, no hourly meter | Estimated per module after the discovery call |
| Source code and IP | 100% ownership on delivery | 100% ownership on delivery |
| AI layer | Generation, recovery, and routing pre-tuned for prompt-to-app | AI services designed around your workflows and data |
| Token economics | Metering, quotas, and model routing engineered in | Plus custom pricing models and private routing |
| Best for | Operators who want to launch this quarter | Teams with bespoke workflows or a unique model |
| After launch | Post-launch support and product updates included | Post-launch support and product updates included |
$ moxace launch --nowWatch it build an app before you commit.
Book a walkthrough and we will generate, refine, and deploy a real app live on the call, then send the written scope.
- 01
Share your idea
a quick call, no deck required
- 02
See the live demo
every screen, admin to user
- 03
Launch with source
full code, your brand, your servers
What moves your quote
No two launches price the same. These are the factors that shape the written quote you receive after scoping.
Scope of customization
The almost-ready AI build covers the proven feature set. Enterprise SSO, private model routing, or bespoke templates add scoped estimate work.
Creators, teams, and markets
Token tiers, language packs, and currency setups are configured per market. Adding regions means more configuration, never a rebuild.
Integrations
Model providers, hosting targets, and SSO are wired during the build, and each integration is estimated individually.
AI tuning depth
Out of the box, generation and routing are pre-tuned for prompt-to-app workloads. Custom prompt libraries and fine-tuning are optional, separately scoped workstreams.
Add-on modules that deepen the platform
Extend the Bolt New-style build once the core generation loop is running.
GitHub and CI pack
Two-way repository sync and CI pipelines over generated projects, meeting professional teams where their code already lives.
Figma-to-app bridge
Design file import feeding the generation orchestrator, converting mockups into coherent starter codebases.
Database and auth templates
Pre-wired database schemas and authentication flows as generation targets, so prompt-to-app covers the boring parts too.
Team workspaces
Multi-user projects with roles and shared token pools, the collaboration layer agencies bill against.
Custom model Fine-tuning
Tenant-specific model tuning on their project corpus as a scoped service, the premium tier of generation quality.
White-label builder reseller
Deploy the platform for agencies and vertical operators under their own identity, with per-tenant token quotas and routing configuration.
/21
Why founders pick our bolt New-style build
Ready-made speed with AI-orchestration discipline.
Orchestration done properly
Streamed diffs, idempotent edits, and checkpoints are core system logic, so projects stay coherent as they grow.
Margin-aware AI
Model routing and token metering are first-class product surfaces, because unit economics decide this category.
Launch economics
A ready-made launch costs a fraction of a ground-up AI stack, with a fixed written quote before work starts.
Full ownership
One hundred percent of the source code transfers to you, refined across 120+ AI products in production. No per-token royalties, no black-box dependencies.
Proof from platforms we have shipped
Canonical deployments from our own portfolio. Metrics are reported from live platforms, not projections.
PragPlay
A gaming platform from the same engineering system, proving infrastructure reliability under sustained consumer load.
500K+
Players
99.9%
Uptime
Etihad Airways
A high-traffic consumer platform our team ships and operates at national-carrier scale, the same bar every build is held to.
1M+
Monthly Users
40%
Engagement Lift
Marvel Studios
A media platform delivered by the same engineering system, holding quality under global launch traffic.
10M+
Streams
65%
Completion Rate
Frequently asked questions
Security and integrity
Tap a card to see how the platform defends its generated code.
Prompts Edit, Never Duplicate
Every request applies streamed diffs idempotently against the current codebase, so a retried prompt never duplicates a file and a refined app stays coherent as it grows.
Checkpoints Roll Back Everything
Creators roll back to any prior project state from checkpoints, so a bad generation direction costs minutes instead of the project.
Sandboxes Are Trust Boundaries
Each preview runs in an isolated container with a lifecycle limit and no cross-tenant network access, so thousands of strangers execute generated code next to each other safely.
Quotas Enforce at the Request
Token tiers and usage meter enforce at the request level automatically, so plan boundaries hold no matter how hard a creator leans on generation.
The Router Protects the Margin
Model routing balances quality against provider cost per tier with automatic failover, so provider price changes never break your unit economics.
Abuse Meets Prompt Policy
Prompt-policy enforcement, rate-limited endpoints, and audit logging gate what the platform will generate, so abuse questions have answers before they are asked.
Frequently asked questions
the process
What to expect from your AI builder build
Discovery covers token tiers, model mix, and sandbox capacity, and returns a written scope and fixed quote. Once you approve, you hand over your brand assets and we configure the platform: your identity across workspace and admin, your model providers with failover, and your billing tiers. The almost-ready AI build goes live in 6 working days; a custom build takes 3 to 4 weeks, planned with you up front.
Launch is not the finish line. You get an included support window, product updates, and model upgrade assistance, and the first 90 days are margin management: watching token cost per tenant, adjusting model routing as provider prices move, and tuning plan ceilings while your creator base compounds.
Live in action
See It Live Before You Talk to Us
Open the web app, sign in with the printed demo credentials, or install the Android build — no signup, no sales call. What you see is what you launch.
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Pro: [email protected] | pro1234
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$ moxace launch --nowLaunch your AI app builder this month.
Book a free consultation and get a written scope and price.
- 01
Share your idea
a quick call, no deck required
- 02
See the live demo
every screen, admin to user
- 03
Launch with source
full code, your brand, your servers
Independent Build
Moxace is an independent software development company. We are not affiliated with, sponsored by, or endorsed by Bolt.
Why This Name
The phrase “Bolt clone” is used descriptively. It is how the software industry refers to building a platform with similar functionality, and how buyers search for one.
Who Built This
The design and codebase are built entirely by our in-house team. Nothing is taken from the Bolt website, applications, or brand assets.
Trademarks
Bolt and all third-party names and marks remain the property of their respective owners, referenced here only to describe the category of software we build.
Read the full legal notice on our disclaimer page.