Advanced R&D

Evaluate the frontier without betting the business on it

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

A stage-gated innovation process, not a hype cycle

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.

01

Business case first

Every experiment starts from a named problem with a quantified cost, never from a technology looking for a use.

02

Pre-agreed kill criteria

Success thresholds set before the work starts, so the decision to stop is evidence-based and unemotional.

03

Production-shaped prototypes

Real data, real users, real constraints — so results transfer rather than evaporate at scale.

04

Honest cost-to-scale

Hardware, licensing, integration, operations and change management modelled before you commit.

What we build

Capabilities you get on day one

The components below are engineered patterns we have shipped repeatedly — not concepts we would be exploring for the first time on your project.

Innovation sprints

Time-boxed, gate-reviewed experiments with a written hypothesis, success metric and decision record.

Digital twin platforms

Live asset models fed by IoT, with simulation and scenario tooling for planners and operators.

Immersive training

VR procedure training with performance capture — measurably faster competency for high-risk tasks.

Intelligent automation

RPA combined with document AI and decision models to automate whole processes, not just clicks.

Edge AI deployment

Quantised, pruned models running on constrained hardware with acceptable accuracy and real latency budgets.

Post-quantum readiness

Cryptographic inventory, exposure assessment and a migration roadmap to NIST-selected algorithms.

Capabilities

Everything inside our emerging technologies practice

The full scope of the practice. Engagements typically draw on a focused subset — this is the bench you have access to.

Spatial & Immersive

  • Augmented reality (AR) applications
  • Virtual reality (VR) training & simulation
  • Mixed reality (MR) & spatial computing
  • Apple Vision Pro & Meta Quest development
  • WebXR & browser-based immersive
  • Remote assist & see-what-I-see support
  • 3D product configurators
  • Metaverse & virtual space experiences

Digital Twin & Simulation

  • Digital twin architecture
  • Asset & process twin modelling
  • Physics & discrete-event simulation
  • Real-time synchronisation with IoT
  • Scenario planning & what-if analysis
  • Predictive simulation for maintenance
  • 3D visualisation & Unity / Unreal
  • Twin-driven operator training

Robotics & Automation

  • Robotic process automation (RPA)
  • Intelligent automation & orchestration
  • Autonomous mobile robot integration
  • ROS 2 development
  • Machine vision for robotics
  • Cobot workcell integration
  • Warehouse automation systems
  • Drone & inspection automation

Frontier Computing

  • Edge AI & TinyML
  • On-device inference optimisation
  • Neuromorphic & accelerator evaluation
  • Quantum computing readiness advisory
  • Quantum algorithm feasibility studies
  • Post-quantum cryptography migration
  • High-performance computing (HPC)
  • Confidential & privacy-preserving computing

Business impact

The outcomes clients measure

Figures are medians across delivered engagements in this practice. We will baseline your own numbers during discovery rather than promise these.

↓ 40%

Training time to competency

VR procedure training for hazardous or high-consequence tasks versus classroom and shadowing.

↑ 26%

First-time fix rate

AR remote assist connecting field technicians to expert support with shared visual context.

6 wks

To a defensible decision

Evidence-based go or no-go instead of a multi-quarter exploratory programme.

↓ 85%

Wasted innovation spend

Stage gates stopping weak concepts at week two instead of month eighteen.

Technology stack

Emerging Technologies technology stack

Selected per engagement against your existing estate, your team's skills and total cost of ownership — never by partnership tier.

Immersive

  • Unity
  • Unreal Engine
  • ARKit
  • ARCore
  • visionOS
  • WebXR
  • Three.js

Simulation & Twin

  • Azure Digital Twins
  • NVIDIA Omniverse
  • AnyLogic
  • MATLAB Simulink
  • Blender

Robotics & RPA

  • ROS 2
  • UiPath
  • Power Automate Desktop
  • OpenCV
  • MoveIt

Edge AI

  • TensorFlow Lite
  • ONNX Runtime
  • NVIDIA Jetson
  • OpenVINO
  • Edge Impulse

Quantum & Crypto

  • Qiskit
  • Azure Quantum
  • Cirq
  • liboqs
  • CRYSTALS-Kyber

Visualisation

  • WebGL
  • Babylon.js
  • deck.gl
  • Cesium

How we deliver

How a emerging technologies engagement runs

Six stages, each with a defined output. You can stop after any one of them and still hold something useful.

  1. Opportunity framing

    Identify the business problem, quantify its cost today and define what a good outcome would measurably look like.

  2. Gate 1 — desk assessment

    Two weeks: technology maturity, vendor landscape, cost envelope, risks and a go / no-go recommendation.

  3. Gate 2 — prototype

    Six weeks: production-shaped prototype with real data, evaluated against the pre-agreed success criteria.

  4. Gate 3 — pilot

    Limited production deployment with real users, operational measurement and a costed scale plan.

  5. Scale or stop

    A written decision record either way. Stopping with evidence is a successful outcome of the process.

  6. Industrialise

    Move survivors into mainstream delivery with support model, training and lifecycle ownership defined.

Engagement models

How to start with Emerging Technologies

Three commercial shapes. Most clients begin with an assessment and move into delivery once the plan is agreed.

Fixed-price assessment

From $12,000

Two to four weeks. Produces a prioritised backlog, target architecture, risk register and a costed delivery plan you own outright.

  • Named architect
  • Executive readout
  • No obligation to proceed
Start here

Dedicated pod

Monthly retainer

An embedded team — lead, engineers, QA — working in your sprints and tooling with US-hours overlap from our India centre.

  • Scale up or down monthly
  • Your definition of done
  • Direct team access
Start here

Indicative ranges for planning purposes. Final pricing follows scope confirmation — we do not quote before we understand the problem.

FAQs

Emerging Technologies — frequently asked

How do we avoid wasting money on hype?

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.

Is enterprise VR training worth the hardware cost?

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.

Should we be doing anything about quantum computing now?

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.

What is a digital twin actually useful for?

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.

Can you work with our internal innovation team?

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.

Advanced R&D

Ready to talk about emerging technologies?

Send the context — current systems, constraints, what you have already tried. An architect from this practice will reply, usually within one business day.

Book a discovery call Email the team

Princeton, NJ · Tiruchirappalli, India · +1 (609) 681-2414