Built by Operations Research Scientists. Run by Machine Intelligence.
Solvoyo replaces passive tools with a system that acts. One decision engine. Every function. Reconciled in a single solve.
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
Two camps dominate this market, and neither one actually decides anything. One shows you the problem and waits. The other talks a good game but has never actually run one. Solvoyo decides itself, near-autonomously, with little to no human intervention.
Legacy suites
Passive dashboards
Charts, recommendations, alerts. Then nothing. Gartner found only about 30% of licensed users actually use these tools, yet vendors still sell every seat. Now they’re bolting AI agents onto the same dashboards and calling it autonomous decision-making. But an agent wrapped around a bad recommendation is still a bad recommendation, just faster. The math underneath never changed.
Solvoyo
Domain depth that acts
Years of machine intelligence depth fused 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, not a suggestion
AI-only startups
Generative, no ground truth
Ask one of these tools about lead times or shelf life and it answers fluently. Ask it to allocate inventory across 50 distribution centers against real constraints, and the fluency stops. There’s no optimization engine underneath the conversation.
The one metric
We optimize for one number.
User Acceptance Rate (UAR) is the percentage of system recommendations executed without manual change. It is the only honest test of automation: if a human edits the answer, the system did not decide. Solvoyo sustains UAR this high 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 solve. Every constraint. No phantom feasibility.
Competitors run heuristics that solve one problem at a time, then re-solve when the answer breaks downstream. Each module looks optimized. The aggregate is infeasible. Solvoyo reconciles cost, service, capacity, lead time, inventory, production, and transportation concurrently in a single Mixed-Integer Linear Programming solve.
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. Nothing is bolted on. Each layer reads and writes the same ground truth.
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.
The moat
MCP and A2A, not bespoke 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.
Autonomous does not mean opaque. Every action is inspectable, contained, and reversible by policy.
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 bends to your operating model instead of forcing a rewrite of it.
Fast business logic
New business logic ships in 3 to 6 week sprints, with NVIDIA cuOpt accelerating solve times so the system keeps pace with how you actually run.
Complement or replace
Deploy modularly. Sit alongside your existing stack or replace it function by function.
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.
Per new logic
New business logic ships in short sprints, so the system keeps pace with your operation.
Start your journey now
Begin the comprehensive digital transformation of your business with Solvoyo's end-to-end intelligent platform.
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