Contract AI R&D

AI Research

Accelerate and de-risk innovation

AI-enhanced contract research that bridges theory and deployment through advanced analytics, simulation, and subject-matter expertise. When the answer is not in the literature and the experiment is too expensive to run blind, simulation comes first.

4PhDs on the team
90+Peer-reviewed publications across AI, neurotech, and materials
100%Client IP ownership on project-specific work

What contract AI research is for

Corporate R&D runs into two walls. The first is capability: the question needs a methodology your team has not built before: a simulation environment, a physical model, a statistically defensible validation design. The second is cost: the experiment that would settle the question is expensive, slow, or destructive.

We work on both. Where a method is missing, we build and validate it. Where the experiment is too costly to run repeatedly, high-fidelity simulation narrows the search space first, so the physical work that remains is the work worth doing.

Research offerings

Three domains where our published work and our delivery experience overlap.

Healthcare & biotech

Drug modelling
In-silico validation to prioritize candidates before wet-lab commitment.
Clinical trials
Scenario simulation for protocol and cohort design.
Medical devices
R&D prototyping, with ISO 14971 risk-management practice applied to device work.

Defence & aerospace

Threat simulation
AI-generated scenarios for evaluating detection and response under conditions you cannot stage.
Sensor fusion
Multi-modal analysis across radar, EO/IR, acoustic, and RF.
Predictive maintenance
Fleet readiness modelling from operational and telemetry data.

Energy & infrastructure

Digital twins
Urban and industrial system models for planning and what-if analysis.
Smart grids
Load simulation and optimization under changing demand profiles.
Retrofit
Energy-recovery modelling for existing plant and building stock.

The research advantage

Scientific rigor

90+ peer-reviewed publications across AI, neurotechnology, and materials, and 5 patents held by the team. Methods get written down and defended, not asserted.

Simulation first

Replace costly trial-and-error with high-fidelity simulation, then commit physical resources to the narrow set of options that survive.

Research that ships

We are an engineering consultancy that publishes, not a lab that occasionally builds. A finding that cannot be deployed is a finding we will tell you about early.

How a research engagement runs

1. Question
We state the research question in falsifiable terms and agree what evidence would settle it.

2. Method
Design the simulation or analysis, including how it will be validated and against what baseline.

3. Findings
Statistically validated results, with the limits stated as plainly as the conclusions.

4. Handover
Code, models, and documentation transfer to you, with knowledge-transfer sessions so your team can extend the work.


Custom engagements: clients own project-specific code, models, and documentation as defined in the applicable agreement. Where a pre-existing Lemay.ai platform is selected, it is licensed separately, see products.

Start a research engagement

Research enquiries go to Parisa Zarkeshian, PhD, our Chief Research Scientist. Tell us the question you are trying to answer, and we will tell you whether simulation, analysis, or neither is the right instrument.

By submitting this form, you agree to be contacted about your enquiry. See our Privacy Policy.

What happens next

  1. Our research team reads it and replies to confirm whether we are the right fit.
  2. A 30-minute call to sharpen the research question and agree what evidence would settle it.
  3. A fixed-fee research scope with method, deliverables, and milestones.

You own the code, models, and documentation we produce. Prefer to write directly? Email [email protected].