Built on Operations Research and AI
Solvoyo is AI-native supply chain decision automation. Optimization and machine learning have been inside the engine since 2005. One mixed-integer solve weighs cost, service, capacity and lead time together, so the plan can execute. Solvi and specialized agents then act on the result and push approved actions to ERP.
Recognized in Gartner’s Magic Quadrant for Supply Chain Planning Solutions and in 25+ Gartner market guides.
Trusted by
The gap
From Recommendation to Execution, Automatically
Solvoyo decides itself, with little to no human intervention. Analytics show what is happening and why, the optimization engine makes the decision, and generative AI explains it in plain language.
Analytics
Recommendations With Reasons
Solvoyo’s supply chain analytics and visibility layer shows charts, alerts and recommendations from the same optimization engine that makes the decision. Reason codes explain each recommendation in plain language, so planners can see why the system chose an action.
Solvoyo
Domain Depth That Acts
Years of machine intelligence depth, combined with a three-layer AI architecture.
- Understands MOQs, lead times, shelf life, and finite capacity
- Reasons across your entire network the way your best planner would
- Then executes the decision itself
Generative AI
Answers Grounded in the Engine
Ask Solvoyo about lead times or shelf life and the answer is grounded in the optimization engine underneath. That engine allocates inventory across 50 distribution centers against real constraints, and the conversational layer explains the result in plain language.
User Acceptance Rate
The Metric That Shows Whether the System Decided.
User Acceptance Rate (UAR) is the share of recommendations executed without manual change. If a human edits the answer, the system did not decide, so UAR is the honest test of automation. Recommendation quality is the cause of a high rate: Solvoyo’s recommendations are good enough that editing them adds nothing. Solvoyo sustains the rate below across enterprise clients.
Manual
Planners build and adjust every decision by hand. The tool reports; the human carries the load. UAR is undefined because there is no system recommendation to accept.
The engine
One Mixed-Integer Solve, Every Constraint at Once.
Solvoyo reconciles cost, service, capacity, lead time, inventory, production, and transportation concurrently in a single Mixed-Integer Linear Programming solve. A plan built one module at a time can look optimized in every module and still be infeasible in aggregate. One solve weighs all the constraints together, so the plan can execute. Solvoyo applies the same multi-constraint optimization to strategic network design, where it balances total cost to serve against service.
Inventory
Production
Transportation
Service / Cost
Infeasible in Aggregate
Every module reports green on its own. Stitched together, the lead times, capacity, and service targets contradict each other. The plan cannot execute. This is phantom feasibility.
Three AI layers, one data model
Forecast. Explain. Act.
Three layers share one data model and the same decision engines. Each layer reads and writes the same ground truth, and all three are built into the engine.
Algorithmic
The math that finds the answer. Forecasting and optimization grounded in operations research, not pattern-matching.
Best-Fit Forecasting
30+ statistical and deep learning models, selected per series for the best fit.
MILP Optimization
Mixed-Integer Linear Programming across the full network, solved concurrently with NVIDIA cuOpt for GPU-accelerated performance at scale.
Price and Markdown
Price-elasticity and markdown ladder modeling that protects gross margin.
Generative
The layer that makes the system legible. It explains decisions in plain language and lowers the cost of getting clean data in.
Conversational Analytics
Ask why a KPI shifted and get a real answer traced to the underlying drivers.
Reason Codes in Language
Exposes system logic and reason codes in natural language for any recommendation.
Import and Validation
Assists with data import and validation so onboarding is faster and cleaner.
Agentic
The layer that acts. Specialized autonomous agents take the optimized plan and execute against it.
Master Data Maintenance Agent
Detects lead-time deviations and updates parameters before they break a plan.
Safety Stock Agent
Retunes service levels when demand or supplier OTIF variance spikes.
Execution Agents
Replenishment, allocation, transportation, and production agents that commit decisions.
The orchestrator
Solvi Runs It Across Your Business.
Solvi sits on top of the three layers and routes work across supply chain functions and across sales (order prioritization, customer commits), marketing (promotion impact, campaign assortment), finance (cost-to-serve, working capital), and procurement (supplier OTIF, lead-time deviations).
One agent, one context, one audit trail. Solvi calls the optimizer directly: agents invoke the solver, evaluate scenarios, and push approved actions to ERP. Model-agnostic across OpenAI, AWS Bedrock, and local models with identical agent definitions and no code changes. Built on the Microsoft Agent Framework, single codebase, native .NET and Python. Read more about AI-native decision automation and Solvi.
Open protocols
MCP and A2A Let New Systems Plug in Without Custom Integrations.
Open protocols mean new systems and partners plug in through a standardized interface, with no integration project sitting in the middle.
MCP Model Context Protocol
Agents reach decision engines, data sources, and external systems through one standardized interface.
- New connectors plug in without bespoke integration
- Decision engines exposed as callable tools
- One interface across data, models, and systems
A2A Agent-to-Agent
Cross-vendor interoperability over standardized HTTP contracts, so agents from different vendors work together.
- Streaming via Server-Sent Events
- Agent Cards publish each agent’s capabilities
- ContextID carries thread continuity across the handoff
Agent-to-agent handoff, no integration project
Built for regulated enterprise
Autonomy You Can Govern.
Every action is inspectable, contained, and reversible by policy. Answers on data security, hosting and compliance are in the Solvoyo FAQ.
Self-Healing Master Data
Diagnostics flag, isolate, and auto-correct broken data in real time, before it reaches a decision.
Private AI Execution
AI runs inside your security perimeter. Local models for zero third-party exposure, AWS Bedrock for private isolation with no training on your data.
100% Audit Trail and Token Governance
Every agent action, tool call, and model invocation is logged. Token governance keeps cost under control.
Configurable Engine
A configurable UI and workflow engine fits your operating model, so your existing processes stay in place.
Fast Business Logic
New business logic ships in 3 to 6 week sprints. NVIDIA cuOpt speeds up solve times so the system keeps pace with how you run.
Complement or Replace
Deploy modularly. Sit alongside your existing stack or replace it function by function. The integration and API options cover how Solvoyo connects to your ERP and other systems.
Proof
Autonomous Decisions in Production.
Speed to value
Live in 12 Weeks.
To Deploy
Industry-specific templates and a dedicated Customer Success team get you running fast.
To Measurable Results
Outcomes you can put a number on, in the same fiscal cycle you started. Follow each phase in the customer journey.
Per New Logic
New business logic ships in short sprints, so the system keeps pace with your operation.
See It Run on Your Own Data
See how Solvoyo turns your supply chain plans into decisions that run on their own.
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