Owned Operational Intelligence

Decision systems you can own.

SolverForge AI builds operational intelligence for constrained, changing operations: software that combines machine learning, optimization, and agentic workflows to predict problems, repair plans, explain tradeoffs, and put better decisions into production.

Discuss Your System Inspect SolverForge In Practice

Optimization Agentic Workflows Predictive Operations

You Are Here When

Operational decisions need more than another black box.

Manual Judgment Is Under Pressure People are making high-stakes calls from spreadsheets, stale dashboards, or scattered tools.

Predictions And Constraints Need One System Forecasts, rules, capacity, live events, and tradeoffs all affect the same decision.

Plans Change Faster Than Rules Can Keep Up Disruptions need repair workflows, not another full reset or manual cleanup loop.

Recommendations Need Explanation Operators need to inspect why a decision changed before they approve or act.

Inspect Logic And Outputs Stay Legible

Control Deployment Fits Your Stack

Operate Built For Daily Decisions

Where Ownership Matters

Across operations where predictions, constraints, and action meet.

The domains vary, but the pattern is the same: operational decisions depend on live data, hard constraints, human approval, and software that has to keep working after conditions change.

Scheduling And Workforce Planning

Assignments, rosters, coverage, fairness, and qualification logic your team can inspect and adjust.

Routing And Allocation

Routes, dispatch decisions, capacity allocation, and tradeoffs that need to fit real operating systems.

Predictive Maintenance And Asset Readiness

Risk signals, maintenance windows, parts, technicians, and readiness targets in one decision loop.

Agentic Operations Workflows

Background workflows that monitor events, propose repairs, surface explanations, and keep humans in control.

Product-Embedded Decision Systems

Operational intelligence inside SaaS products, APIs, internal tools, and customer-facing workflows.

SolverForge In Practice

Proof across six operating shapes.

SolverForge is tested against machine scheduling, route ownership, warehouse picking, field service routing, workforce coverage, and readiness planning. Each case exposes real model structure, constraint surfaces, screenshots, and integration paths.

Furnace 155 orders / 11 furnaces / 39 operators Heat-treatment planning where furnace capacity, thermal sequencing, task operators, and shift rosters solve together.

Inspect case

Open source Deliveries 82 deliveries / 10 vehicles / retained routes Route ownership, vehicle capacity, time windows, recommendations, and REST workflows on one inspectable surface.

Inspect case Open Space

Order Picking 8 orders / 94 items / 5 trolleys Warehouse order picking where item assignment, bucket capacity, order splits, product locations, and walking routes solve together.

Inspect case

Open source Field Service 48 visits / 6 technicians / road routes Technician routes, skills, parts, shifts, territories, time windows, and road geometry in one retained workflow.

Inspect case Open Space

Open source Hospital 688 shifts / 50 employees / 28 days Coverage, qualifications, rest, availability, preferences, and fairness across dense workforce schedules.

Inspect case Open Space

Fleet 24 vessels / 56 days / readiness planning Maintenance, inspections, training, docks, parts, technicians, and readiness targets in one operating plan.

Inspect case

SolverForge Output

Models, operating surfaces, and integration paths stay connected.

SolverForge is built for decisions where predictions, rules, capacity, timing, and people affect the same outcome. The output remains usable because the model, explanation, and production boundary are designed together.

Coupled Decision Models

SolverForge solves predictions, constraints, objectives, and approvals together when staged cleanup would create brittle or invalid plans.

Inspectable Operating Output

Schedules, routes, recommendations, scores, and constraint explanations remain visible to the people who review and act.

Production Integration

APIs, retained jobs, events, dashboards, and repair loops fit the systems already running the operation.

Inspectable By Design

Trust comes from behavior you can examine.

SolverForge documentation explains the modeling and solver behavior. Open-source repositories expose implementation choices. Hugging Face Spaces run the public examples, and the use cases show deeper operating shapes with constraints, screenshots, and integration paths.

Use Cases Documentation GitHub Hugging Face Spaces

Behavior-Level Proof

SolverForge exposes model behavior, score pressure, and integration surfaces.

# Modeling and solver behavior solverforge.org/docs # Open-source implementations github.com/solverforge # Runnable public examples huggingface.co/SolverForge Decision logic is explicit. Outputs are inspectable. Production delivery stays controllable.

Start With The Decision

Bring the operational decision, not a polished requirements doc.

If your team is trying to predict issues, schedule work, allocate resources, repair plans, or explain recommendations inside production software, send the rough context and current stack.

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