Agentic engineering, with control in your hands.
Teams of AI agents that design, build and verify software and hardware with NYTT's method. Nothing reaches your product without passing automated tests and an independent review.
AI alone isn't enough; it takes a method. Ours was born in NYTT's own projects and rests on six principles.
No agent approves its own work
Every delivery passes two independent checks: automated tests green, and a reviewer other than the one who did it. Only then is it integrated.
You decide
Agents execute. Scope, priorities and business decisions belong to your team. Anything that needs human judgment is escalated, never guessed.
Everything is on the record
Every task, review and decision lives in the repository and the project board. If it isn't recorded, it didn't happen.
Cost measured and capped
We measure the real spend of each task, not estimates. Every project has a capped budget: as it nears the limit, the system stops on its own.
The right model for each task
We use more powerful models where the task demands it and cheaper ones where they suffice. Cost follows value.
Your code is yours
The code and documentation we produce are yours. Personal data is handled under Argentina's Law 25.326.
Every delivery passes two independent checks before reaching your product. If one fails, it goes back to the agent with the concrete note; if it doesn't converge, a person decides.
A team of agents, NYTT's method, and you in charge. Pick where to start.
Agentic engineering
Your product, built by a team of agents that NYTT directs and supervises.
See serviceAI staff augmentation
NYTT engineers who join your team with their agents.
See serviceAgentic FPGA
FPGA design with agents, without lowering the lab's bar.
See serviceAgentic UVM
Functional verification with UVM, written and extended by agents.
See serviceAgentic IoT
From firmware to the cloud, with agents that also operate what they build.
See serviceAgents for your operation
Agents for concrete tasks, where your customers already are.
See serviceWe start small, measure, and only then scale.
Diagnosis
We understand your problem, your systems and which decisions you want to keep. We define what the agents do and what your team approves.
Scoped pilot
We start with a small, measurable scope. At the end you see what was delivered, what it cost and what a person had to decide.
Scale
With the pilot validated, we add agents, tasks or channels. Each expansion has its own budget and cap.
Operation and improvement
Every error becomes a new test, and improvements ship in versions you choose when to adopt.
Do the agents replace my team?
What if an agent gets it wrong?
Who owns the code?
Do you use my data to train models?
Which AI models do you use?
How is cost controlled?
AI agents that deliver, and account for every delivery.
The method was born in fifteen years of NYTT's mission-critical engineering: aerospace, radar, energy and industry.