Frequently Asked Questions
Who owns the IP for the models, code, and playbooks developed during an engagement? Is it a full transfer to the client, or is it a licensed solution?
Our policy is straightforward: the client owns the IP. All bespoke code, trained models, evaluation harnesses, and governance artifacts created specifically for your project are your property upon completion and final payment. The delivery includes complete handover of all code repositories, logs, and documentation. Our goal is to empower your team, not create a dependency. The only exception is our pre-existing, proprietary tooling or general methodologies, which we retain ownership of, but you receive a perpetual, royalty-free license to use them as part of the delivered solution.
Who exactly would be working on my project? What is the ratio of senior practitioners to junior staff or students on a typical enterprise engagement?
This is a key differentiator for us. Your project will be led and executed by the senior practitioners—individuals with direct, hands-on experience shipping AI in high-scale and regulated environments. We do not use a leveraged model typical of large consultancies.
While we are proud of our "AI Research Student Guidance" program, it is a separate initiative. We do not staff client enterprise projects with students. You are paying for deep, hands-on expertise, and that is what we provide. The engagement lead will be your primary point of contact, and the team will consist entirely of seasoned professionals.
How is your pricing structured? Is it a fixed fee per project, a time-and-materials basis, or value-based? What is the typical cost range for an "AI Infrastructure Audit" versus a full "R&D-as-a-Service" engagement?
Our pricing is designed to de-risk the engagement for you. We typically use a phased approach:
Deposit: For well-defined engagements, we usually work on a fixed-fee basis deposit of 30%, as the scope is clear.
Full Payment: For a completed project, the rest 70% of the payment is requested only if the KPIs are reached.
The schema ensures you are not committing to a large, open-ended budget. You invest a smaller amount to get a clear, evidence-based plan before scaling the investment, and you pay for the real results.
Your process mentions "pass/fail gates." What happens if a project fails to meet the agreed-upon KPIs at a gate? Does the engagement end, and what are the financial implications for us as the client?
If a project fails to meet the KPIs at a decision gate, we present the evidence and our analysis of why it failed. At that point, the engagement can conclude. The financial implication is that you have only paid for the work up to that gate, saving you the significant cost of a full-scale but ultimately unsuccessful project. We have successfully de-risked the initiative and provided a valuable, board-ready result: "We investigated this AI approach, and it is not feasible for these specific, measurable reasons."
For an air-gapped engagement, what are the security protocols your team follows when working with our highly sensitive, proprietary data on our premises?
We are "Enterprise-ready by default," and this is a core part of that promise. Our protocol for air-gapped work is strict:
NDA First: All work is preceded by a robust, mutually-agreed-upon Non-Disclosure Agreement.
No Data Exfiltration: We work entirely within your environment, on your hardware. No sensitive data ever leaves your premises.
Clean Room Policy: Our practitioners access your environment through your established security protocols (e.g., client-provided laptops, VPNs, virtual desktops).
Full Audit Trail: All work is logged and documented, creating the audit trail required for regulated industries.
Final Delivery: All code, models, and artifacts are delivered and remain within your infrastructure.
Are you technology-agnostic, or do you have preferred cloud providers, MLOps platforms, and foundational models? Will your solutions lock us into a specific vendor ecosystem?
We are fundamentally problem-first and technology-agnostic. Our loyalty is to the optimal solution, not a specific vendor. As the client testimonial highlights, we run ablations to find what actually moves the metric. Our recommendation is based on a rigorous evaluation of quality, cost, and latency for your specific use case and existing infrastructure. We aim to integrate with your current stack where possible and will never recommend a solution that creates unnecessary vendor lock-in.
What does the "hand over" process truly entail? What level of support or training is provided to our internal team to ensure they can maintain, monitor, and retrain the delivered models?
The handover is a critical phase, not an afterthought. The "Deliver" package includes:
A Working Prototype: The functional code itself.
The Evaluation Harness: The exact tools we used to measure performance, so your team can reproduce our results and test future iterations.
A Detailed Playbook: Comprehensive documentation explaining the "why" behind our decisions, the system architecture, and instructions for operation, monitoring, and retraining.
Knowledge Transfer Sessions: We conduct workshops with your technical team to walk them through the solution so they are fully equipped to own it.
Our goal is to make your team self-sufficient. We can also arrange for ongoing advisory retainers for longer-term support if needed.
How does your hands-on, practitioner-led approach differ in practice from engaging a major consultancy or a specialized AI freelancer from a platform?
We occupy a unique space between those two options.
vs. Major Consultancies: You get the senior expert who sold you the project doing the actual work, not a junior team that learns on your dime. We deliver a working, evaluated prototype with a full audit trail, not a 100-page PowerPoint deck. Our overhead is lower, and our process is faster and more transparent.
vs. A Freelancer: You get the benefit of a structured, battle-tested scientific process (the FEED pipeline) that is reproducible and auditable. You are not dependent on a single individual; you are engaging a firm with enterprise-grade standards for governance, security, and documentation. We de-risk the project by providing a system, not just a person.
In short, we offer the deep, hands-on expertise of a top-tier specialist combined with the rigorous process and enterprise-ready governance of a larger firm.