Nextmv offers a DecisionOps platform that lets teams write optimization, simulation, or rules‑engine code in any language and then validate, version, and deploy those models through a unified workflow. The platform provides KPI‑driven experimentation, A/B shadow testing, a versioned model repository, and a marketplace of pre‑built decision apps, while integrating via APIs and SDKs into existing CI/CD pipelines and cloud environments.
Funding
$8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Companies that need to automate complex decisions—such as routing, scheduling, packing, or price optimization—often build custom optimization, simulation, or rules‑engine code that is hard to validate, version, and integrate with existing development pipelines. The lack of a unified workflow leads to slow iteration, fragile deployments, and difficulty proving that models meet business KPIs.
Solution
Nextmv provides a DecisionOps platform that acts as a speed, trust, and innovation layer for any decision‑making application. Users write optimization or simulation code in their preferred language, then import it into the platform where they can run experiments that measure KPI impact, simulate alternative scenarios, and shadow production runs. The platform maintains a system of record for models, supports collaborative model management, and offers a marketplace of pre‑built decision apps for common use cases. Integrated APIs and SDKs let teams embed decision services into existing services, CI/CD pipelines, and cloud environments. By automating testing, validation, and deployment, Nextmv enables faster time‑to‑value while reducing risk associated with decision‑model changes.
Target Audience
Primary customers are operations researchers, data scientists, and software engineers building optimization or simulation solutions, as well as product and business teams that need reliable decision services embedded in their applications.
Features
- Unified DecisionOps workflow for model validation, A/B shadow testing, and KPI‑driven experimentation
- Model marketplace with ready‑to‑use routing, scheduling, packing, and price‑optimization apps
- SDKs and API endpoints for seamless integration with existing codebases, CI/CD pipelines, and cloud services
- Versioned model repository and collaboration tools for teams of data scientists, ops researchers, and engineers
- Support for commercial solvers (Gurobi, OR‑Tools, HiGHS) and open‑source frameworks (Pyomo) within the same platform
- Role‑based access control, SSO, and audit logs for enterprise security and governance
- Scalable cloud execution with pay‑as‑you‑go credits and optional private‑cloud deployment