Who We Are

We build it, measure it, and publish what we learn.

Fusion Models is a small team of engineers who design, build, and benchmark advanced AI systems end to end. We do not theorize about what might work. We build it, measure it, and publish what we learn.

How We Engage

Senior help, on a selective basis.

If you are leading an engineering or product organization and want senior help architecting multi-model systems, evaluation pipelines, or AI workflows that hold up in production, we consult on a selective basis.

Team & Background

Building custom AI systems with fusion modeling and adversarial engineering.

Brian Galvan

Brian Galvan

Research & Development

Brian leads Fusion Models’ custom system development. He specializes in ensemble architecture, model orchestration, and building the evaluation tooling needed to verify performance under real-world conditions.

  • Ensemble Architecture
  • Model Orchestration
  • Evaluation Tooling
Miladin Malic

Miladin Malic

Research & Development

Miladin focuses on adversarial robustness and fusion model research, developing methods that stress-test models, resolve disagreement, and improve the resilience of multi-model AI systems.

  • Adversarial Robustness
  • Fusion Research
  • Disagreement Resolution

We are developing AI systems that do more than predict. We build multi-model fusion systems that harness diverse strengths, expose disagreement as signal, and route answers through higher-tier evaluators. Our work centers on robustness, quality measurement, and adversarial model testing so the systems you run in production are durable and defensible.

  • Custom AI systems designed around real product goals and risk-managed deployment.
  • Fusion model engineering that orchestrates multiple models into one coherent answer.
  • Adversarial model development to surface failure modes before they become customer issues.
  • Evaluation and benchmark pipelines that measure accuracy, cost, and reliability side by side.
Engagements Include

Where we plug in.

01

AI systems architecture

AI systems architecture and ensemble design — from first principles to a system that ships.

02

Evaluation infrastructure

Evaluation and benchmarking infrastructure so you can measure quality objectively, not guess at it.

03

Orchestration pipelines

Model orchestration and synthesis pipelines that coordinate a panel of models into one reliable answer.

04

Cost & quality optimization

Cost and quality optimization across model providers, so you pay for performance — not branding.

Work With Us

Serious about building AI systems that perform?

We take a limited number of consulting engagements. If that is you, let's talk.

Start a Conversation → How It Works