Cost & risk of rebuilding software with AI tokens

Choose a category, a reference product and the modules you need; the tool estimates the resources and risk of rebuilding software with AI instead of buying it. The figures are budgeting estimates, not an actual invoice.

Cost & risk of rebuilding software with AI tokens

Considering building your own CRM or ERP instead of buying SaaS? Select the modules you need and the tool estimates resources (person-months, cost, timeline with AI assistance) and scores risk across four dimensions: security and sensitive data, legal compliance, legacy integration, and AI code quality plus budget. This is a high-level business case for a build-vs-buy decision.

Rebuild cost by software category

Checklist before you start

Drawn from what we hit in practice — the traps that cost real money or force a rewrite.

  1. Verify the tool still exists AI tooling churns fast: Windsurf was renamed Devin Desktop on 2 June 2026, while Sora, DALL·E and Luma Genie were all discontinued in the first half of 2026. Confirm status on the vendor's own site before a rebuild plan or budget depends on it — not from an old blog post.
  2. Read pricing pages, not marketing Before concluding that KiotViet, Sapo or MISA AMIS lacks a feature and therefore justifies a rebuild, open their pricing pages and technical docs rather than their marketing pages. Stale marketing is real: nhanh.vn still advertises Sendo sync even though the marketplace shut down on 15/4/2025.
  3. Count your coding-assistant quota GitHub Copilot Free gives only 2,000 completions and 50 chat requests per month, and 50 chat requests vanish in a single session refactoring an accounts-receivable module. If you move to paid, multiply by seats and by the full duration of the project: Cursor Pro is 16 USD/month, Devin Desktop Pro is 20 USD/month.
  4. No developer, no cheap path Token-based API pricing usually beats subscriptions at low volume, but it requires a developer to open a dev account, obtain an API key and write the code. A team without one never gets that cheap price, and a self-built system has nobody left to maintain it after handover.
  5. Leave the regulated parts alone POS and accounting touch Decree 70/2025/ND-CP (e-invoices generated from cash registers, mandatory for retail and F&B households and businesses since 01/6/2025) plus Decree 123/2020/ND-CP; card swipes and dynamic QR bring PCI DSS and the State Bank's payment-intermediary rules; payroll, social insurance and personal income tax are sensitive data. Let KiotViet, MISA AMIS or iPOS carry that weight, because building it yourself means tracking every legal change forever.
  6. Fact-check every AI number AI states product names, prices and quotas with total confidence and still gets them wrong: it may still recommend Windsurf, or generate code calling DALL·E, which was removed from the API on 12/05/2026 in favour of gpt-image-2. Verify every figure in your build-versus-buy report against the source page, and check endpoint lifespans before handover, for example the Sora API only runs until 24/09/2026.

Frequently asked questions

How much does rebuilding software with AI cost?

It depends on the modules you select: each carries its own effort (person-months), summed and then reduced by AI assistance, converted into cost and timeline.

What risks are covered?

Four dimensions: security and sensitive data, legal compliance, legacy integration, and AI code quality plus budget overrun. Risk rises with the sensitivity of the modules chosen.

Does this estimate cover security properly?

Only at a directional level. Security, compliance and integration require a dedicated assessment for your specific project.

Who is this tool for?

Executives, CTOs and department heads weighing build against buy who need a directional number before commissioning a detailed business case.

Does the estimate include running costs after launch?

Not in full. Once live, a system still incurs infrastructure, maintenance, user support and further development — often the largest cost over several years.

Is it risky to expose internal data and processes to AI during the build?

It is. Define which data may go into AI tools, prefer options that contractually exclude your data from training, and set internal rules for the development team.

All figures are reference estimates. Built by the TOT team.