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.

We plan the handover from day one. Validated architecture patterns form the baseline. Integration contracts and stubs turn into production adapters. Performance baselines guide non-functional requirements. UX prototypes help create the MVP backlog. Handover includes a structured transition pack with: Prioritised user storiesAcceptance criteriaTechnical recommendationsKnown risksDependency mappingEffort estimates by phaseWe propose a delivery cadence with decision gates and measurable outcomes; where appropriate, a limited pilot validates adoption and support needs. This continuity - from feasibility to product value, minimises rework and shortens the runway to MVP. Stakeholders receive demoable artefacts and documentation that support a clear go/no‑go decision and a de‑risked plan to scale.

A no-go is a legitimate and useful result, and the engagement is structured so it can surface honestly. The decision pack documents what was tested, what the evidence showed and why the recommendation is to stop or change course, so the conclusion can be defended internally without re-running the work. In practice the outcome is often a pivot rather than a flat stop: the business goal survives while a specific architecture, vendor or data source is ruled out, and a short follow-up spike tests the alternative. Either way, the time-box has done its job - the cost of the PoC bought the avoidance of a far larger build that the evidence says would have struggled.

Come with the business case as it currently stands, including the numbers it relies on - the workshop's job is to find the assumptions doing the most load-bearing work, and those usually hide in the financial model rather than the technical design. Bring the colleagues most doubtful about the idea - the architect who questions the integration, the operations lead who has watched a similar project fail - because their objections convert directly into the hypotheses most worth testing. Records of prior attempts are valuable too, whether an abandoned prototype or a vendor evaluation, since they tell us what has already been disproven. Finally, any hard constraints - regulatory obligations, vendor contracts, fixed launch dates - so the test is designed inside the world the project will actually live in.

Yes, and it usually strengthens the result. We regularly run PoCs alongside client engineering teams: your engineers bring system context and institutional knowledge, ours bring the validation discipline and an outside view that is not invested in any particular answer. The framing workshop is run jointly, so the hypotheses reflect what your team already suspects but has not had the space to test properly. During the build we work as one team, with shared standups and a shared board. The benefit shows at the end: because the evidence was produced together, the verdict carries weight internally and the knowledge needed to act on it already lives in-house.