Applied AI Engineering
Test Before You Invest. Then Build It Right.
We’re an AI dev shop. We test your workload against real models, build the system your organization actually needs, and stay responsible for it in production.
Four-time Microsoft Solutions Partner: Security, Data & AI, Azure Infrastructure, and Digital & App Innovation. Founder-led engineering experience since 1999.
The problem
You are expected to accelerate AI adoption and protect the organization at the same time. Most providers recommend a model before they have tested one, hand over an architecture, and leave your team to carry the risk when it does not hold up.
Your workload determines the model. The evidence comes before the investment.
How the engagement works
The four pillars
Model Evaluation
Workload-specific model, runtime, quantization, serving, and hardware recommendations based on measured evidence.
Private AI
AI systems that run inside your control boundary when privileged, regulated, or proprietary data cannot be sent to a public AI service.
Autonomous Operations AI
Continuous monitoring and anomaly detection for operational telemetry, with escalation design, human override, and audit trails treated as first-class requirements.
AI Product Engineering
End-to-end AI product and platform engineering: ingestion, enrichment, retrieval, UI, APIs, cost controls, and operating discipline.
We publish our own homework — including the parts that did not work.
Bonelli Systems built and publishes a benchmark of locally servable open-weight LLMs. The point is not a model leaderboard. The point is the discipline: a controlled roster, eleven evaluation batteries, version-pinned judges where judgment is required, confidence intervals, statistical ties called out as ties, hardware provenance, and a published gap register.
Proof assets
Private AI legal evidence
A fully local evidence-processing pattern for privileged legal material: transcription, speaker diarization, document/image extraction, and search inside the client boundary.
Industrial telemetry monitoring
A public-safe case brief for energy and industrial environments where monitoring, escalation, and auditability matter as much as the model.
AppellateNews.com
A commercial legal research and analytics product built and operated end to end, with deterministic statistics and labeled AI enrichment.
Ownership continuum
Co-managed, fully managed, or build-and-operate: you choose how much Bonelli owns in production. We do not change the engineering standard based on the answer.
Related Bonelli capabilities
Next step
Turn the risk, AI, and Microsoft 365 conversation into a concrete operating plan.
Bonelli Systems helps regulated and growth-minded teams decide what to secure, what to automate, and what evidence to keep before another tool or AI workflow becomes business-critical.