
Managed cloud app and backend workspace
Run and manage applications and their backend infrastructure in one owned workspace.
- For
- Small software teams and internal IT groups running applications and backend infrastructure in the cloud
- Solves
- Teams rent separate tools for cloud environments, app creation, databases and virtual machines, so setup, access and scaling stay fragmented.
- Delivers
- A working cloud environment with provisioned apps, database and virtual machines
- Built in
- about 5 weeks of creation time, MVP in 6 days
- Investment
- $12,500 for the MVP, $42,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Run and manage applications and their backend infrastructure in one owned workspace.
- Provision a ready-to-use cloud environment.
- Reach the environment from any device.
- Organize content, notes, links, videos and apps on a dashboard.
- Create lightweight apps from natural language commands.
- Let applications interact with each other.
- Integrate front ends through APIs.
- Scale a managed cloud database with demand.
- Deploy applications with minimal configuration.
- Use built-in SDKs and tools.
- Apply authentication and permissions to data.
- Spin up a full Ubuntu virtual machine with admin rights, desktop and SSH access.
- Stop, resume and fork virtual machine state.
- Scale to many concurrent virtual machines.
- Preconfigure virtual machines with project tooling.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
Everything these tools do, in one app
- Cloud environment provisioning Creates a ready-to-use computing environment in the cloud, such as a personal OS, backend service, or virtual machine.Found in Deta Space, Deta Surf, box
- Access from any device Lets users reach their cloud environment from any device with an internet connection.Found in Deta Space
- Customizable dashboard Provides a personal dashboard where users can organize content, notes, links, videos, and apps.Found in Deta Space
- AI-assisted app creation Enables users to create lightweight apps using natural language commands with AI help.Found in Deta Space
- App interoperability Allows different applications to interact seamlessly with each other.Found in Deta Space
- API-first design Makes it easy to integrate with various front-end technologies through APIs.Found in Deta Surf
- Managed cloud database Provides a database that automatically scales with application demand.Found in Deta Surf
- Simple deployment Deploys applications with minimal configuration required.Found in Deta Surf
- Built-in SDKs and tools Accelerates development workflows with included software development kits and tools.Found in Deta Surf
- Secure data handling Supports authentication and permissions to keep data secure.Found in Deta Surf
- Fast VM creation Spins up a full Ubuntu virtual machine with admin rights, desktop, and SSH access in about two seconds via a single terminal command.Found in box
- VM snapshotting Supports stopping, resuming, and forking a virtual machine's state so workflows can pause and resume.Found in box
- High concurrency scaling Allows self-serve scaling up to 1,000 concurrent virtual machines, with support for higher limits.Found in box
- Preconfigured templates Lets users preconfigure virtual machines with project-specific tooling to avoid repeated setup.Found in box
What goes in, what comes out
- Approved project requirements
- Tooling choices
- Access rules
AI drafts, people review. Technical delivery workspace with managed implementation.
- A working cloud environment with provisioned apps
- Database
- Virtual machines
How it works
The workflow
- InStart with
Approved project requirements, tooling choices and access rules
- 1
Confirm the buyer's problem and scope
- 2
Collect approved project requirements
- 3
Tooling choices and access rules
- 4
Then follow this sequence: 1
- OutFinish with
A working cloud environment with provisioned apps, database and virtual machines
AI does the heavy lifting, people stay in charge
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved cloud region and one supported runtime stack; final security, access and production decisions remain with the operator. A model suggestion is never a verified fact, professional decision or authorization to act.
What your team sees
Primary screens: Environment setup and templates, App and backend workspace, Operations and scaling. Use a project list with environment states, a central workspace showing apps, database and virtual machines, and a right-hand panel for access, logs and costs. Let users compare environment versions side by side. Display provisioning, running, paused and failed states. Provide a client preview link with comments anchored to the relevant environment. Make the task-specific outcome a working cloud environment with provisioned apps, database and virtual machines visible beside its evidence, review state and value baseline.
Accounts and administration
Project ownership, environment versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.
Integrations and data access
Customer-owned repositories, authorized cloud accounts and permitted monitoring sources. Cloud asset storage, design-file import/export and deployment destinations. Start with file exchange and validate destination specifications before promising direct deployment. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
6 daysOne buyer segment, one recurring use case; first modules: provision a ready-to-use cloud environment; create lightweight apps from natural language commands. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
7 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
3 weeksSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will small software teams and internal IT groups running applications and backend infrastructure in the cloud use it to solve "teams rent separate tools for cloud environments, app creation, databases and virtual machines, so setup, access and scaling stay fragmented"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Time to first working environment per project and operator hours per running application.
- Measure, then decide. Track time to first working environment per project and operator hours per running application; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Pilot scope: One approved cloud region and one supported runtime stack; final security, access and production decisions remain with the operator. Implement one approved input format, a bounded representative case set and the first two task modules: provision a ready-to-use cloud environment; create lightweight apps from natural language commands. Support the third module with operator review: scale a managed cloud database with demand. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around a working cloud environment with provisioned apps, database and virtual machines. Retain the explicit scope boundary: One approved cloud region and one supported runtime stack; final security, access and production decisions remain with the operator.
What the build depends on. Asset upload and preview, asynchronous provisioning jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist infrastructure QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved cloud region and one supported runtime stack; final security, access and production decisions remain with the operator.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case; first modules: provision a ready-to-use cloud environment; create lightweight apps from natural language commands. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$42,500about 5 weeks of creation time · start with the MVP from $12,500
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $30–$60 | $60–$120 | $90–$180 |
| Full productabout 50 customers | $110–$210 | $530–$1,050 | $640–$1,260 |
Run it or resell it
For your own team
Small software teams and internal IT groups running applications and backend infrastructure in the cloud run it inside the business: approved project requirements, tooling choices and access rules in, a working cloud environment with provisioned apps, database and virtual machines out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#277c91 - accent
#c95a54 - surface
#e4eef1 - ink
#22201e
- Headings
- Archivo
- Text
- Lora
- Voice
- Technical, direct, no hype
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test a USD 300-1,500 fixed pilot for one defined environment package. Offer a monthly production allowance after repeat demand. Quote complex migrations or specialist infrastructure separately. These are test prices, not market benchmarks. Package the initial sale as one bounded working cloud environment with provisioned apps, database and virtual machines. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.
Message to test
Run and manage applications and their backend infrastructure in one owned workspace. Demonstrate a concrete working cloud environment with provisioned apps, database and virtual machines using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Small software teams and internal IT groups running applications and backend infrastructure in the cloud professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample working cloud environment with provisioned apps, database and virtual machines from a small authorized input set, with a transparent calculation of time to first working environment per project and operator hours per running application and no promised savings.
The first 30 days
- Week 1: interview five small software teams and internal IT groups running applications and backend infrastructure in the cloud and inspect a recent example of teams renting separate tools for cloud environments, app creation, databases and virtual machines, so setup, access and scaling stay fragmented.
- Week 2: prepare a consented or synthetic demonstration of the three task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- Week 4: measure time to first working environment per project and operator hours per running application, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.
Paid pilot
Agree quality and outcome thresholds before the pilot using this measure: Time to first working environment per project and operator hours per running application. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.
Success metrics
Time to first working environment per project and operator hours per running application; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs a working cloud environment with provisioned apps, database and virtual machines. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.
Why clients would pick it
A reusable library of approved templates, access rules and review examples, together with reliable delivery for a narrow technical niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for small software teams and internal IT groups running applications and backend infrastructure in the cloud. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Deta Space, Deta Surf, box, freelancers, agencies and generic cloud consoles. Compare this product with the buyer's present method on time to first working environment per project and operator hours per running application. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Compute, storage, network egress, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of a working cloud environment with provisioned apps, database and virtual machines. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Preserve access boundaries, source attribution, configuration accuracy and usage permissions. Operators approve substantive changes and production scope. One approved cloud region and one supported runtime stack; final security, access and production decisions remain with the operator. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.