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What is Proof of Concept (PoC)?

Software Engineering, explained by the engineers who build it. Definition, how it works, use cases and common questions.

PoC definition

A proof of concept (PoC) is a small, focused experiment that tests whether a technical idea is feasible before a team commits to building it fully. It answers a specific question, such as whether an AI model can reach the required accuracy on real data or two systems can integrate, using minimal code that is usually thrown away.

What does a proof of concept test?

A PoC targets the riskiest technical unknown in a project. Can our document AI extract fields from these scanned invoices accurately enough? Can the legacy ERP expose the data we need in near real time? Will this blockchain network handle our transaction volume? If the answer is no, the team learns it in weeks instead of discovering it after months of development and a large budget commitment. The cost of a PoC is small compared with the cost of a failed full project.

A PoC deliberately ignores everything that is not part of the question. It may have no user interface, no authentication and hard-coded configuration. That is acceptable because the output is evidence and a recommendation, not a product. A short written report with measurements is the real deliverable.

How to run a proof of concept

Good PoCs are short, bounded and judged against criteria agreed before any code is written. Without those criteria, the result becomes a matter of opinion and the PoC tends to grow into an unplanned prototype. Agree on them with the people who will make the final decision.

  • State the question and the decision the answer will inform.
  • Define measurable success criteria, such as accuracy or latency targets.
  • Use real or realistic data rather than idealized samples.
  • Fix a timebox, typically a few weeks.
  • Document results, limitations and estimated effort for production.
  • Decide: proceed, change approach, or stop.

Proof of concept examples

An insurer might run a PoC to test whether a language model can summarize claim files accurately, measuring results against summaries written by adjusters. A retailer might test whether its point-of-sale system can stream sales events to a cloud data platform with acceptable delay. A logistics company might check whether low-cost GPS trackers report locations reliably in rural areas before ordering thousands of devices.

In each case, the PoC produces numbers and observed limitations that turn a guess into an informed decision, plus a much better estimate for the full project. It also exposes practical constraints, such as data quality issues or vendor API limits, that no planning document would have revealed.

PoC vs prototype vs MVP

These terms are often mixed up. A PoC proves technical feasibility and is usually internal and disposable. A prototype shows how the product will look and behave so users and stakeholders can react to the experience. An MVP is a working product released to real users to test demand. Many projects move through all three, though not always in that order. Skipping the PoC is reasonable when the technology is proven and the main uncertainty is whether customers want the product.

Why proofs of concept fail

PoCs fail to help when success criteria are vague, data is unrealistically clean, or the scope grows until the PoC becomes an underfunded product. Another trap is treating PoC code as production-ready. Nexzem runs scoped AI and integration PoCs with written success criteria, then gives clients a clear go or no-go recommendation and an estimate for production.

PoC: common questions

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How long should a proof of concept take?

Most software PoCs take a few weeks. If a PoC needs many months, it is probably answering too many questions or turning into a product. Keep it focused on one or two critical unknowns, with a fixed timebox and agreed success criteria, so the result informs a decision quickly.

Is PoC code used in production?

Usually not. PoC code skips error handling, security, tests and scalability to answer a question quickly. Some components, such as a tuned model, data mappings or integration findings, carry forward, but the production system should be designed and built properly using what the PoC revealed.

Who needs a proof of concept?

Any team facing significant technical uncertainty benefits from one, for example when adopting AI, integrating with an unfamiliar legacy system, choosing between platforms or using emerging technology like blockchain or IoT hardware. If the technology is well understood and the main risk is market demand, an MVP is the better next step.

Keep exploring the software engineering glossary

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