Founders and product teams evaluating a difficult concept
Test technical feasibility, user interaction, integration, performance, hardware, data, or AI behaviour before full delivery.
Focused technical prototypes that test the highest-risk assumptions before major product investment
Proof of concept development
Rokad builds focused software, hardware, AI, embedded, and connected-product proofs of concept to test feasibility, integration, performance, and user assumptions.
Designed for / 01
A focused delivery model for the organisations that need it.
A proof of concept should reduce a defined uncertainty—not imitate a finished product badly. Rokad identifies the most consequential assumptions, designs measurable experiments, builds the smallest credible system, records evidence, and recommends whether and how to proceed.
Enterprises assessing new technology
Compare architecture, vendor, platform, automation, device, and operating assumptions in a controlled environment.
Engineering programmes facing a high-risk dependency
Resolve one critical unknown before committing schedule, architecture, suppliers, or production investment.
Challenges / 02
The problems this service is built to solve.
The prototype has no explicit learning objective
Features accumulate, but the team cannot state which uncertainty, threshold, or decision the work is meant to resolve.
Demonstration shortcuts are mistaken for production architecture
Temporary data, hardware, security, scaling, workflows, and manual operations are not labelled or planned for replacement.
Success criteria remain subjective
The outcome depends on visual impression rather than measured feasibility, accuracy, latency, cost, reliability, fit, or user evidence.
Capabilities / 03
What Rokad can deliver.
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Assumption mapping, feasibility, experiment, evidence, and decision design
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Software, AI, data, embedded, electronics, IoT, CAD, and physical prototypes
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Third-party API, model, hardware, cloud, vendor, and platform integration tests
04
Performance, latency, throughput, accuracy, power, range, fit, and reliability experiments
05
User workflow, interface, interaction, operator, and field validation
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Prototype instrumentation, logs, measurements, findings, limitations, and risks
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Production-gap assessment, architecture options, budget inputs, and next-stage roadmap
Solution components / 04
The system behind the visible product.
Decision and hypotheses
The decision to inform, assumptions to test, thresholds, evidence, time box, constraints, and stop conditions.
Minimum credible system
Only the components, integrations, interfaces, data, hardware, and workflows required to test the assumptions.
Measurement system
Logs, instrumentation, tests, samples, user observation, benchmarks, failure cases, and repeatable procedure.
Production gap
Security, reliability, scale, quality, certification, manufacturing, operations, support, cost, and maintainability still required.
Use cases / 05
Where this capability creates practical leverage.
AI feasibility prototype
Test task quality, data, model, latency, cost, evaluation, human review, and integration before product development.
Connected-device prototype
Validate sensing, control, power, connectivity, cloud, application, enclosure, and user setup assumptions.
Integration proof
Confirm that systems, protocols, vendors, APIs, data, identity, and workflows can coordinate under real constraints.
Product workflow prototype
Evaluate user journeys, interfaces, operations, permissions, exceptions, and commercial workflow before full engineering.
Architecture and integration / 06
Designed to fit the wider technology environment.
Time-boxed learning
Limit scope by uncertainty and decision value; stop when evidence is sufficient rather than polishing non-critical features.
Explicit shortcuts
Document mocked, manual, insecure, non-scalable, temporary, or vendor-specific choices and their production replacements.
Representative constraints
Test with realistic data, hardware, environment, latency, users, volume, integration, and failure where they affect feasibility.
Quality and control / 07
Production requirements are part of the build.
Requirements before geometry
Fit, function, load, environment, power, interfaces, tolerance, material, production, and service constraints guide design decisions.
Evidence through prototypes
High-risk assumptions are tested with measurable prototypes, inspection, iteration, and documented findings before scale.
Production-aware decisions
Component availability, manufacturing method, assembly, testing, certification, repair, and lifecycle are considered early.
Delivery / 08
A controlled path from requirement to operation.
Discover
Clarify the objective, users, systems, constraints, dependencies, risks, and measurable acceptance criteria.
Architect
Define the target design, interfaces, controls, migration or delivery sequence, and operating model.
Deliver and validate
Implement in controlled increments with testing, review, documentation, observability, and stakeholder validation.
Operate and improve
Establish ownership, service controls, measurement, support, and a prioritised improvement backlog.
Typical deliverables
PoC objective, assumptions, success criteria, risks, and experiment plan
Prototype architecture and minimum credible implementation scope
Working software, hardware, AI, data, or integrated prototype
Instrumentation, tests, demonstrations, measurements, and evidence
Findings, limitations, failures, uncertainty, and production-gap assessment
Recommendation, target options, next-stage scope, and delivery roadmap
Engagement models / 09
Use the delivery structure that matches the work.
Assessment and roadmap
A bounded evidence review, target direction, prioritised risks, and executable next-stage plan.
Fixed-scope delivery
A defined implementation, migration, prototype, procurement, or transformation outcome with acceptance criteria.
Embedded specialists
Specialists working alongside internal product, engineering, data, operations, security, or procurement teams.
Managed lifecycle
Ongoing ownership, maintenance, monitoring, supplier coordination, reliability, security, and improvement.
Related capabilities / 10
Continue through the wider product and technology system.
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Embedded systems
Take validated device behaviour into production firmware engineering.
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IoT development
Develop the complete connected-device and fleet system.
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3D design
Turn validated mechanical assumptions into detailed CAD and production preparation.
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AI development
Governed AI applications, agents, retrieval, models, evaluation, and intelligent automation.
02
Software development
Custom applications, platforms, integrations, APIs, and software modernisation.
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Technology consulting and research
Strategy, architecture, discovery, due diligence, feasibility, and market intelligence.
FAQ
Proof of concept development
Scope, ownership, assumptions, delivery, security, and long-term operation are clarified before work begins.
01How is a proof of concept different from an MVP?
How is a proof of concept different from an MVP?
A PoC primarily tests feasibility or uncertainty. An MVP is a usable product release designed to test customer and market assumptions while operating with real users.
02Can PoC code or hardware be reused in production?
Can PoC code or hardware be reused in production?
Sometimes, but reuse is not assumed. We identify which components meet production standards and which require redesign for security, reliability, scale, quality, manufacturing, or operation.
03What happens if the concept fails?
What happens if the concept fails?
A well-designed negative result is valuable. We document why it failed, which assumptions were disproved, whether alternatives exist, and whether the programme should change or stop.
04Can Rokad continue from PoC into full development?
Can Rokad continue from PoC into full development?
Yes. We can translate the evidence into product discovery, architecture, production engineering, procurement, certification preparation, deployment, and managed operation.
Product engineering and prototyping
Resolve the expensive uncertainty before funding the full build.
Rokad can define the experiment, build the minimum credible system, measure the result, and recommend the next stage.
Contact / 05
Bring us the difficult technology problem.
Tell us what you need to build, improve, procure, deploy, or operate. We will respond with a practical next step.