PoC Development

A proof of concept (PoC) is a focused validation exercise that tests feasibility and de‑risks the riskiest assumptions before full delivery. It answers “Can this work?” rather than “What will it look like?” (prototype) or “Will people buy it?” (MVP). Choose a PoC when uncertainty is technical or operational: architecture feasibility, integrations, performance, data handling, or compliance. Typical PoC outputs include architecture spikes, mock services, API proof points, and performance baselines in a time‑boxed window. If risk is mostly experiential, a prototype may be enough. If feasibility is proven and you need real usage evidence, move to an MVP. Many teams run a short PoC, validate UX with a prototype, then ship an MVP for market learning. A well‑scoped PoC reduces cost, clarifies the roadmap, and enables an objective go/no-go decision.

We begin with hypotheses, constraints, and success criteria that define what the PoC must prove and what is out of scope. We prioritise a few validation threads – typically one technical (integration feasibility or performance target), one product (user value), and one delivery (dependency risk), each with acceptance criteria, metrics, and a clear test method. To stay time‑boxed, we use stubs and mock services, seed datasets, and the lowest‑effort path that proves feasibility. Daily risk checkpoints, a mid‑point cut, and a fixed end‑date ensure focus. The output includes demoable artefacts, findings, risks, and recommendations with effort estimates for the MVP. Every task must tie to a hypothesis, if it doesn’t prove or disprove a critical assumption, it waits for the MVP. This keeps the PoC small, fast, and conclusive.

Expect decision‑ready outputs: a demoable PoC build that proves key assumptions; technical notes on architecture options, integration feasibility, performance baselines, and security considerations; and a concise risk register with mitigations. Discovery artefacts include hypotheses, success criteria, and acceptance tests; UX scope may include wireframes or clickable prototypes and user feedback notes. You also receive a practical roadmap to MVP with effort estimates, dependency mapping, and phased prioritisation. For compliance‑sensitive contexts, we add data handling approaches, consent flows, and audit needs. Where useful, we provide spike code, mock services, and test datasets so your team can reproduce results. The full pack supports stakeholder validation, a clear go/no‑go decision, and a smoother transition to delivery.

We target the riskiest aspects with minimal effort. For integrations, we validate authentication, payload contracts, idempotency, and error handling using mock services first, then a thin real integration. For performance, we baseline the critical path – key API response times, page loads with realistic data, and queue behaviour under controlled load – to show scalability pathways. For security, we demonstrate sound foundations: secrets management, basic access controls, safe data handling, and document hardening for the MVP (encryption, audit, compliance controls). This yields credible proof points – architecture options that work, performance tracking to targets, and security considerations that won’t derail delivery, while keeping the PoC lean, time‑boxed, and affordable. Findings feed the risk register and MVP roadmap.

Most PoCs complete within four to eight weeks, shaped by uncertainty level, integration access, and the need for user research. Narrow technical spikes (a single integration or performance concern) can finish in two to four weeks. Broader PoCs with discovery, prototyping, and multiple integrations trend towards six to eight weeks. Budget depends on team mix (engineering, UX, QA), environment setup, and third‑party access. The biggest variables are integration readiness (sandboxes, documentation, credentials), sample data availability, and stakeholder decision latency. We control cost and time via strict scoping, time‑boxing, and an evidence‑first plan that prioritises the riskiest assumptions. You’ll know what “done” means, how it’s measured, and what defers to MVP, enabling confident approvals and avoiding rework.