Applied research on agents, automation, and private AI.
We study how AI systems behave inside real businesses — and publish what we learn. What survives the lab becomes a NexosAI service.
Programs
Research agenda
Four programs. Publications appear inside their program until there are enough to stand alone.
Agent architectures for real workflows
How multi-agent systems should be structured to run actual business processes — delegation, tool use, and hand-offs that hold up outside a demo.
OutputReference architectures + open benchmarks
Approval & autonomy design
When an agent should act, ask, or defer — and how to make human-in-the-loop feel like one clear decision instead of a growing queue.
OutputDesign patterns + a scored eval set
Private & on-prem AI
Making open-weight models genuinely usable in-house: hardware sizing, tuning, and the honest trade-offs against hosted frontier models.
OutputSizing guides + deployment playbooks
Automation reliability
Treating agent automations like production software — tracing, retries, self-evaluation, and the failure modes that only appear at scale.
OutputTooling + a reliability checklist
People
The team
Agent systems
Program
Architectures, delegation, and tool use for agents that run real processes — the core of what graduates into the platform.
Private AI & infrastructure
Program
On-prem and hosted private models: sizing, tuning, and deployment so a business can own its AI without owning a research team.
Reliability & evaluation
Program
Making automations dependable — tracing, self-evaluation, and the benchmarks that tell us whether the work actually held up.