Nextmv

Overview

Nextmv turned the hard, neglected work around optimization models into a developer platform. Founded in 2019 by former Grubhub decision-engineering leaders Carolyn Mooney and Ryan O'Neil, it combined model building, deployment, testing, observability, and collaboration under the label DecisionOps.^[1][2]

This is an acquisition story, not a conventional startup failure. Nextmv made optimization easier to ship, but enterprise decision tooling rewards distribution, solver breadth, and trust as much as developer experience. Its July 2025 integration with FICO Xpress became a preview of the strategic fit: Nextmv supplied the lifecycle layer, while FICO supplied an incumbent decision platform and enterprise reach.^[3] FICO acquired Nextmv in May 2026, with no price disclosed.^[4]

Founding Story

Mooney and O'Neil came to Nextmv through operating experience, not an abstract thesis. Both worked on decision engineering at Zoomer and Grubhub. Mooney had also analyzed simulations at Lockheed Martin; O'Neil had worked in operations research and later led teams responsible for forecasting, scheduling, routing, and simulation. Their common problem was that a useful mathematical model was only one part of a production decision system. Teams also needed infrastructure, APIs, tests, version control, monitoring, and a way for engineers and operators to review changes.^[1]

The initial wedge was logistics, where each delivery decision must balance time, distance, capacity, and changing business rules. In TechCrunch's 2021 Series A coverage, Mooney framed the ambition directly: "There are hundreds of thousands of operations researchers ... But there are millions of developers out there. Why can't this be a superpower that every developer has in their pocket."^[5] The comparison was Twilio: package specialist infrastructure so ordinary developers could use it.

Nextmv raised a reported $2.7 million seed and then an $8 million Series A led by FirstMark. The Series A financed Nextmv Cloud, broader distribution, and educational content. By 2023, the company had widened from routing and delivery into a general platform for vehicle routing, scheduling, order fulfillment, packing, and custom decision models.^[5]

The research did not surface a second long-form founder interview. The founders' acquisition announcement supplies the other direct statement: "We are excited to announce that FICO has acquired Nextmv!"^[4] The gap matters because public materials explain the product well but disclose little about commercial performance or sale mechanics.

Timeline

• 2019: Nextmv began with a mission to make production decision models easier to build and operate.^[2]
• 2020: The company raised a reported $2.7 million seed round.^[5]
• December 2020 / February 2021: An $8 million FirstMark-led Series A closed and was announced.^[5]
• November 2023: Nextmv 1.0 unified building, testing, deployment, and model operations.^[2]
• July 2025: Nextmv announced its FICO Xpress integration.^[3]
• April 2026: The Nextmv MCP Server became generally available.^[6]
• May 2026: FICO acquired Nextmv.^[4]

What They Built

Nextmv sat between a company's operational data and the systems that execute decisions. A team could write a model in Python or Go, use open-source solvers such as OR-Tools and HiGHS or commercial engines, deploy the model behind an API, and manage it through a shared console. The platform also offered prebuilt applications for routing and shift scheduling.^[2]

The important product was not the solver. It was the workflow around the solver. Teams could compare model versions against historical data, define acceptance thresholds, shadow a production model without affecting operations, or run switchback tests across periods or locations. Run history captured inputs, outputs, metrics, errors, and version identifiers. That made an optimization model behave more like ordinary production software: reviewable, testable, reversible, and observable.

Nextmv kept expanding the abstraction. The FICO Xpress integration let teams bring an incumbent commercial solver into the same testing and collaboration system.^[3] In 2026, the MCP Server exposed the system of record to AI agents. An agent could inspect failures, summarize scenarios, examine configuration, and initiate controlled rollouts or rollbacks. Nextmv emphasized that the agent operated through deterministic controls, not by replacing the mathematical model with an LLM.^[6]