Per-Asset Predictive APIs
Built for Operations

Operations teams have telemetry, but not reliable prediction their systems can run — so decisions stay manual, reactive, or late.

Assets behave differently and data changes over time, so generic models miss failures and prediction never reaches operations as a dependable service.

SOLVER-AI builds, updates, and runs custom predictive services as APIs — often one model per asset (each asset gets its own model) or per equipment type.

Prediction is embedded directly into your systems, not delivered as model files you must deploy.

Custom APIs are built on the SOLVER-AI platform, so model build, updates, and execution are already handled.

That means multiple models and logic can be combined into one deployable API without rebuilding the stack.

• Connect data (files or live telemetry; validation handled inside the service).
• Models update per asset (new data triggers background updates with no interruption to live predictions).
• Call the API from your product or workflow (stable endpoints, business-ready outputs).

Integration-first: REST / HTTP + client libraries (Python, JavaScript, C++).

• Founded and led full-time by Dr. Paolo Fantini (BSc/MSc from Politecnico di Milano; PhD from Cranfield University, both in Aerospace Engineering).
• 20+ years across aerospace engineering, scientific software, and computational optimisation.
• Highly experienced in developing advanced engineering software used by teams in high-performance industrial environments.

Book a call and we'll define one concrete operational decision and a tight predictive API aligned to your systems and workflows.