Corporate AI R&D

An AI R&D partner

For questions your team does not have the method to answer yet

We take on contract research where the methodology has to be built before the question can be answered, and where the physical experiment is too slow or too expensive to run blind. Simulation narrows the search space; your team gets the method, not just the finding.

What a good R&D partner is for

Corporate R&D groups rarely lack domain expertise. What they lack, at a specific moment, is a method: a simulation environment that does not exist, a validation design that will hold up to scrutiny, or the machine-learning engineering to make a physical model tractable. Hiring for that permanently is expensive when the need is bounded.

We work as the bounded, methodological half of that pairing. 4 PhDs, 90+ peer-reviewed publications across AI, neurotechnology, and materials, and 5 patents held by the team, but attached to an engineering consultancy that ships production systems, so a finding gets assessed for whether it can actually be deployed.

Where we do research

Healthcare & biotech

Drug modelling and in-silico validation to prioritize candidates before wet-lab commitment; clinical trial scenario simulation; medical-device R&D prototyping with ISO 14971 risk-management practice.

Defense & aerospace

Threat simulation for evaluating detection and response, multi-modal sensor fusion research, and fleet-readiness modelling.

Energy & infrastructure

Digital twins for urban and industrial systems, smart-grid load simulation, and energy-recovery modelling for retrofit programs.

Method development

Where the technique does not exist, we build and validate it, and write it down well enough that your team can extend it.

Statistical validation

Results validated against agreed performance and fairness standards, with limits stated as plainly as conclusions.

Knowledge transfer

Code, models, and documentation transfer to you at handover, with sessions so the capability stays after we leave.

How research engagements work

Who owns the research output?

You do. Clients own project-specific code, models, and documentation as defined in the applicable agreement: 100% IP ownership on the work we do for you. Where a pre-existing Lemay.ai platform is selected, it is licensed separately.

Can you publish, or do you work quietly?

Either. We publish extensively in our own right, and we routinely do work that will never be published. Publication rights are a contracting question, settled before we start.

How do you scope research when the answer is unknown?

By scoping the method rather than the outcome. The engagement commits to a defined body of work (this simulation, this validation, these benchmarks) with stage gates where we reassess. Fixed fee, so an inconclusive result is not a budget problem.

Do you work with our existing research team?

Usually, yes. The most productive shape is your domain experts plus our methodology, rather than us working in isolation and delivering a report.

Registered to contract in the United States

U.S. and NATO registration is already in place, so teaming does not wait on paperwork. Every identifier is verifiable in a public registry.

Unique Entity IDJJADR6LWJ743
NCAGE codeL0QB4
U.S. consortiumSOSSEC member
CybersecurityCMMC, scope on request
Controlled goodsCGP registered
PersonnelTop Secret cleared staff

Registry entries establish procurement eligibility. They do not imply endorsement by any government. Full detail is in our capability statement.

Start a research engagement

Tell us the question you are trying to answer and what evidence would settle it. Research enquiries can go direct to [email protected].

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What happens next

  1. An engineer reads it and replies to confirm fit.
  2. A 30-minute discovery call to frame the problem, constraints, and success measures.
  3. A fixed-fee scope with deliverables, milestones, and price, typically within two weeks.

You own the code, models, and documentation we produce. Defense and government enquiries can go direct to [email protected].