What AMPL Optimization Inc. does

AMPL Optimization Inc. is a privately held software company that develops AMPL, an algebraic modeling language (AML) and platform for formulating and solving large-scale optimization problems in business and engineering. The company's core product, the AMPL Modeling System, separates model formulation from solver execution and connects to more than 30 commercial and open-source optimization solvers — including Gurobi, CPLEX, Xpress, MOSEK, BARON, HiGHS, and NVIDIA cuOpt — through the AMPL MP solver interface. Supporting products include the amplpy Python API for integration with data science workflows, the amplbot AI assistant on ChatGPT, and the AMPL Model Colaboratory notebook environment running on Google Colab, Kaggle, and AWS SageMaker. AMPL also offers deployment tooling for AWS, Azure, Google Cloud, and Docker environments.

The company serves enterprise customers across energy and utilities, logistics and supply chain, finance and investment, and manufacturing — with named users including ArcelorMittal, UPS, LinkedIn, Hitachi Energy, Rio Tinto, US Army, Newport News Shipbuilding, Dropbox, Zara, Siemens, O'Shaughnessy Asset Management, and Eviden. Customers deploy AMPL models for production-scale optimization problems involving millions of variables and complex discrete and nonlinear constraints; AMPL claims its models have influenced over $200 billion in customer revenue and reduced over $500 million in operational costs across deployments in more than 50 countries.

Revenue is generated primarily through software licensing — perpetual and subscription — for the AMPL Modeling System, bundled and standalone commercial solver licenses, and professional services including consulting, model development, and energy-specific optimization engagements. The company operates a multi-tier pricing structure spanning a free Community Edition, free academic licenses, and quote-based Enterprise contracts, distributed through both direct enterprise sales and self-serve download channels. AMPL has been operating for over 40 years, is headquartered in Mountain View, California, and is led by CEO William M. Wells with co-founder Bob Fourer serving as founder and president.

Name

AMPL Optimization Inc.

Legal name

AMPL Optimization, Inc.

Website

https://ampl.com

Company type

Private

Founded year

2002

Operating status

Operating

Headcount range

11–50 employees

Short description

AMPL Optimization Inc. provides an algebraic modeling language platform for formulating and solving large-scale optimization problems. It serves enterprise customers in energy, logistics, finance, and manufacturing with optimization software, solver integrations, Python APIs, and AI-assisted modeling tools.

Ownership category

akta.pro rank

Product category

Mathematical Optimization Software

NAICS

Software Publishers (5132), Custom Computer Programming Services (541511), Computer Systems Design and Related Services (54151)

SIC

Services-Computer Integrated Systems Design (7373), Services-Computer Programming Services (7371)

akta.pro primary industry

Workflow-Oriented Integration & Orchestration (HDAEAIAG)

akta.pro secondary industries

NLP Developer Tools & Evaluation (prompting, testing, benchmarks) (HDAAADAK), Semantic Layer, Metrics Store & Headless BI (HDAEAMAE)

Keywords

• Optimization modeling software
• Algebraic modeling language
• Operations research tools
• Mathematical programming solvers
• Decision optimization platform

Headquarters

HQ city

Albuquerque

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure

Revenue model

1. Software Licensing: AMPL generates revenue through software licenses for its modeling language and solver interfaces. Licensing options include perpetual one-time licenses and annual subscriptions. Pricing varies by license type (Demo, Community Edition, Academic, Enterprise) and solver vendor requirements.
2. Solver Licenses: Revenue is generated through bundled and standalone solver licenses. AMPL interfaces with commercial solvers (CPLEX, Gurobi) that require separate licensing from their respective vendors, creating a layered revenue structure.

Pricing tiers

Go-to-market motion3 records

Distribution channels3 records

Marketing channels8 records

Core offering

AMPL is an algebraic modeling language and optimization platform for formulating and solving large-scale mathematical optimization problems used in business and engineering. Its core product, the AMPL Modeling System, separates model formulation from solver technology and connects to more than 30 commercial and open-source solvers (Gurobi, CPLEX, Xpress, MOSEK, Knitro, BARON, HiGHS, SCIP, etc.) through the AMPL/MP interface, with native Python integration via amplpy and AI-assisted modeling through the amplbot ChatGPT companion.

Product overview

AMPL Optimization Inc. offers AMPL as a modern optimization platform and end-to-end system of products and services for building and operating large-scale optimization systems. The core product is the AMPL Modeling System, a purpose-built modeling language that enables organizations to define complex optimization models clearly and maintainably. AMPL connects to an ecosystem of commercial solvers (Gurobi, CPLEX, Xpress, COPT, MOSEK, Knitro, BARON, CONOPT, LOQO, SNOPT, MINOS, LGO, LINDO Global) and open-source solvers (HiGHS, CBC, SCIP, GCG, IPOPT, Bonmin, Couenne, NVIDIA cuOpt) through the AMPL MP solver interface framework. The platform integrates with Python data science workflows via the amplpy Python API and supports deployment across cloud environments (AWS, Azure, Google Cloud) and Docker containers. AMPL also offers professional services including optimization consulting, technical training, and specialized energy optimization services. Free academic licenses and Community Edition are available for educational and non-commercial use.

Differentiator

Problem solved

Functional benefit

Products and services

• AMPL Modeling System A purpose-built algebraic modeling language and interactive environment for defining complex optimization models. Separates model logic from data and solver configuration, allowing models to scale from early experimentation to production deployment. Supports millions of variables, complex discrete and nonlinear constraints, and evolving business rules.
• AMPL MP (Solver Interface Framework) Multi-platform solver interface framework that connects AMPL models to a wide range of optimization solvers, ensuring compatibility, high performance, and continuous support as solver technologies evolve. Enables users to evaluate and switch solvers without modifying model code.
• amplpy (AMPL Python API) Python interface allowing developers to access AMPL features from within Python, enabling optimization models to be embedded within data science workflows and engineering systems. Integrates with Google Colab, Pandas, Databricks, Jupyter notebooks, and AWS SageMaker.
• amplbot AI companion for optimization available through ChatGPT. Helps users learn AMPL, formulate models from natural language descriptions, and generate ready-to-run AMPL/amplpy code.
• AMPL Model Colaboratory Collection of AMPL models in Jupyter Notebooks that run on platforms such as Google Colab, Deepnote, Kaggle, Gradient, and AWS SageMaker. Provides Colab notebooks, Streamlit demos, and example models covering real industry problems.
• Commercial Optimization Solvers Leading commercial optimization solvers distributed and supported through AMPL MP, including Gurobi, CPLEX, Xpress, COPT, MOSEK, Artelys Knitro, BARON, CONOPT, LOQO, SNOPT, MINOS, LGO, and LINDO Global. Enables users to evaluate and switch solvers without modifying model code.
• Open Source Optimization Solvers Open-source optimization solvers integrated with AMPL MP, including HiGHS, CBC, SCIP, GCG, IPOPT, Bonmin, Couenne, and NVIDIA cuOpt, providing cost-effective options for linear, nonlinear, and global optimization problems.
• Optimization Services Consulting services delivered by in-house AMPL consultants, including model development, model rewriting and documentation, technical training, and deployment and integration support.
• Energy Optimization Services Specialized consulting and product development for the energy sector, delivered by energy experts. Includes energy-specific modeling, end-to-end energy solutions, and production deployment.
• Academic Licenses and Resources Free academic licenses for students and researchers, including teaching licenses, academic licenses, and career starter licenses, providing free access to AMPL and leading commercial solvers for teaching, coursework, and research projects, supported by an Academic-Industry Advisory Council.

Quantifiable outcome

• Over $200 billion in revenue influenced by AMPL-built optimization models
• +2 more outcomes

Named customers13 records

Segments5 records

Ideal customer profiles6 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration30 records

AI capability6 records

Feature5 records

Partnerships

Two partnerships are on record, tiered core.

• CPLEX (IBM)coreTechnology or Integration · 1 January 2024CPLEX optimization solver is fully supported by AMPL. Users can formulate models in AMPL and solve them with CPLEX through the AMPL/MP solver interface. This integration provides access to IBM's commercial optimization solver for complex linear, mixed-integer, and quadratic programming problems.
• GurobicoreTechnology or Integration · 1 January 2024Gurobi Optimizer is supported as a solver backend for AMPL models. This partnership enables users to leverage Gurobi's high-performance optimization algorithms through the AMPL modeling interface for linear, mixed-integer, and constraint programming.

Scale indicators4 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• GAMS (General Algebraic Modeling System): GAMS is the closest direct competitor to AMPL: an algebraic modeling language for mathematical optimization with a similarly long history, comparable solver-agnostic architecture, and overlapping customer base in energy, logistics, and academia. It competes head-to-head for the same operations-research practitioner audience.
• AIMMS: AIMMS is an algebraic modeling platform with an integrated GUI and app-deployment layer for supply chain, planning, and operations optimization. It competes with AMPL for enterprise modeling use cases and overlaps on solver-agnostic formulation and verticalized optimization apps.
• LINDO Systems (LINGO): LINDO's LINGO product is an algebraic modeling language for linear, nonlinear, and integer optimization, with both a modeling layer and bundled solvers. It targets the same OR practitioner buyer as AMPL and offers an integrated alternative to AMPL's solver-agnostic model.
• Frontline Systems (Solver Platform / Analytic Solver): Frontline offers a modeling-and-solver platform (Solver SDK, Analytic Solver) for optimization and simulation. It targets a similar audience of analysts and OR practitioners, with Excel-friendly entry points that overlap with AMPL's PLG funnel.

Broad incumbents

• FICO Xpress: FICO Xpress combines the Xpress solver with the Mosel modeling language and a broader decision-optimization suite. It is both a solver partner of AMPL (via AMPL MP) and a broader incumbent competitor that sells optimization as part of an enterprise analytics portfolio.
• Gurobi Optimization: Gurobi is AMPL's deepest solver partner but also a broad incumbent: its own modeling APIs (Gurobi Python, Rapid) increasingly compete with AMPL's modeling layer. Comparable as a high-performance optimization vendor serving the same enterprise buyers.
• IBM CPLEX (ILOG): IBM CPLEX Optimization Studio combines the CPLEX solver with the OPL modeling language and broader Decision Optimization tooling. It is both a solver partner and a broad incumbent competitor with deeper enterprise sales reach than AMPL.

Emerging players

• Google OR-Tools: Google's open-source OR-Tools provides routing, LP/MIP, and constraint programming solvers with Python and C++ APIs. It is an emerging, free alternative that increasingly competes with AMPL on Python-native data-science workflows.
• Pyomo: Pyomo is an open-source Python-based modeling language for optimization, originally developed at Sandia National Labs. It targets the same Python data-science audience AMPL is courting via amplpy, with no licensing cost, and is a credible open-source substitute for AMPL's modeling layer.
• Artelys Knitro: Artelys Knitro is a nonlinear optimization solver accessible from AMPL via AMPL MP. As an AMPL partner, it shares customer overlap; as an independent product with its own modeling interfaces, it is an emerging alternative in the nonlinear optimization niche.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat4 records

Key risks6 records

Key highlights6 records

Customer concentration

• Xx.com/AMPLopt
• GitHubgithub.com/ampl
• YouTubeyoutube.com/channel/UC6Yt3duW9a2IFj3nO2ZL6Ew
• Facebookfacebook.com/AMPLopt
• LinkedInlinkedin.com/company/amploptimization

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about AMPL Optimization Inc.