Business case first
Every experiment starts from a named problem with a quantified cost, never from a technology looking for a use.
Advanced R&D
Our innovation practice runs disciplined experiments on technologies that are nearly ready. Spatial computing, digital twins, robotics, edge AI and post-quantum cryptography — each assessed against a real business case, with a clear kill criterion if the evidence does not hold up.
0+
Innovation experiments run
0 wks
Typical evaluation sprint
0 gates
Stage gates before production commitment
Overview
We run emerging technology as a portfolio with explicit gates. Gate one is a two-week desk assessment against a named business problem. Gate two is a six-week prototype with success criteria agreed in advance. Gate three is a production pilot with real users and a costed scale plan.
Most concepts should die at gate one or two — that is the process working, and it is far cheaper than discovering the same thing eighteen months into a programme.
What survives arrives with evidence: measured outcomes, honest cost-to-scale, integration requirements, and the operational capability you would need to build.
Every experiment starts from a named problem with a quantified cost, never from a technology looking for a use.
Success thresholds set before the work starts, so the decision to stop is evidence-based and unemotional.
Real data, real users, real constraints — so results transfer rather than evaporate at scale.
Hardware, licensing, integration, operations and change management modelled before you commit.
What we build
The components below are engineered patterns we have shipped repeatedly — not concepts we would be exploring for the first time on your project.
Time-boxed, gate-reviewed experiments with a written hypothesis, success metric and decision record.
Live asset models fed by IoT, with simulation and scenario tooling for planners and operators.
VR procedure training with performance capture — measurably faster competency for high-risk tasks.
RPA combined with document AI and decision models to automate whole processes, not just clicks.
Quantised, pruned models running on constrained hardware with acceptable accuracy and real latency budgets.
Cryptographic inventory, exposure assessment and a migration roadmap to NIST-selected algorithms.
Capabilities
The full scope of the practice. Engagements typically draw on a focused subset — this is the bench you have access to.
Business impact
Figures are medians across delivered engagements in this practice. We will baseline your own numbers during discovery rather than promise these.
↓ 40%
VR procedure training for hazardous or high-consequence tasks versus classroom and shadowing.
↑ 26%
AR remote assist connecting field technicians to expert support with shared visual context.
6 wks
Evidence-based go or no-go instead of a multi-quarter exploratory programme.
↓ 85%
Stage gates stopping weak concepts at week two instead of month eighteen.
Technology stack
Selected per engagement against your existing estate, your team's skills and total cost of ownership — never by partnership tier.
Immersive
Simulation & Twin
Robotics & RPA
Edge AI
Quantum & Crypto
Visualisation
How we deliver
Six stages, each with a defined output. You can stop after any one of them and still hold something useful.
Identify the business problem, quantify its cost today and define what a good outcome would measurably look like.
Two weeks: technology maturity, vendor landscape, cost envelope, risks and a go / no-go recommendation.
Six weeks: production-shaped prototype with real data, evaluated against the pre-agreed success criteria.
Limited production deployment with real users, operational measurement and a costed scale plan.
A written decision record either way. Stopping with evidence is a successful outcome of the process.
Move survivors into mainstream delivery with support model, training and lifecycle ownership defined.
Engagement models
Three commercial shapes. Most clients begin with an assessment and move into delivery once the plan is agreed.
From $12,000
Two to four weeks. Produces a prioritised backlog, target architecture, risk register and a costed delivery plan you own outright.
Most common
Scoped per phase
Well-bounded phases priced against agreed acceptance criteria. Suited to migrations, integrations and defined product increments.
Monthly retainer
An embedded team — lead, engineers, QA — working in your sprints and tooling with US-hours overlap from our India centre.
Indicative ranges for planning purposes. Final pricing follows scope confirmation — we do not quote before we understand the problem.
FAQs
Stage gates with pre-agreed kill criteria. The hypothesis, success metric and cost ceiling are written down before work starts, and the gate review is a genuine decision point rather than a status update. Roughly two thirds of concepts we assess do not pass gate two, which is exactly what a functioning innovation portfolio looks like.
For high-consequence, high-repetition, hard-to-simulate tasks — electrical isolation, confined-space entry, surgical procedure, emergency response — yes, and the payback is usually under a year. For routine software or process training, conventional e-learning is more cost-effective. We model the specific case rather than generalising.
Two things, both practical. First, post-quantum cryptography migration is a real near-term concern because data captured today can be decrypted later — build a cryptographic inventory and a migration roadmap now. Second, keep a watching brief on algorithm feasibility for your specific optimisation or simulation problems. Building quantum applications for production use is premature for almost every enterprise.
Three things reliably: operational visibility across a complex asset hierarchy, scenario simulation before acting in the physical world, and predictive maintenance grounded in real duty cycles. A twin that is only a 3D visualisation with live labels is an expensive dashboard — the value comes from simulation and prediction.
Yes, and that is our preferred model. We typically provide the engineering capability and stage-gate discipline while your team owns the business case, stakeholder access and the eventual scale decision. Capability transfer is an explicit deliverable.
Production-grade generative AI, applied ML and autonomous agents — governed, evaluated and observable.
Industrial IoT, smart devices, edge computing and embedded systems from sensor to dashboard.
Smart contracts, tokenisation, supply-chain provenance and decentralised identity — with audits built in.
Migration, cloud-native engineering, Kubernetes, FinOps and resilience across AWS, Azure, Google Cloud, Oracle and IBM.
Advanced R&D
Send the context — current systems, constraints, what you have already tried. An architect from this practice will reply, usually within one business day.