Alvys puts a build-your-own AI agent layer inside its freight TMS

Alvys, a transportation management system provider founded by Nick Darman, launched Alvys Foundry on August 17th, a platform that lets carriers and brokers build custom AI agents in plain English, deploy prebuilt agents, or have Alvys engineers create them. The product includes over 20 templates for tasks like detention filing and rate auditing, and is rolling out initially to a controlled cohort with a governance layer called Agent Shield. Alvys, which helped Archerhub pass $90 million in annual revenue before becoming a standalone product in 2020, aims to embed AI agents directly into its TMS to automate multi-step freight operations.

Nick Darman https://alvys.com/resources/about-us , founder and CEO of Alvys https://alvys.com/ , is turning the transportation management system he originally built for his own freight operation into a place where carriers and brokers can build AI workers. Alvys announced on August 17th https://www.prnewswire.com/news-releases/introducing-alvys-foundry-customizable-ai-agents-built-natively-into-tms-302853316.html that Alvys Foundry https://alvys.com/foundry will let customers deploy prebuilt agents, assemble their own in plain English or have Alvys engineers create them. The launch follows a familiar Darman pattern: take a problem he encountered as an operator, build the missing software and then sell the resulting system to the rest of the freight market. Darman grew up in a trucking family, started the asset-based brokerage Archerhub in 2014 and assembled an engineering group after existing TMS products failed to fit its workflows. Alvys says the internal system helped Archerhub pass $90 million in annual revenue before Darman turned it into a standalone software product in 2020. Darman paired that freight experience with co-founder and CTO Leo Gorodinski https://www.prnewswire.com/news-releases/former-jetcom-tech-exec-leo-gorodinski-joins-alvys-as-co-founder-and-cto-301160395.html , Jet.com's first employee and former vice president of engineering. Walmart acquired Jet.com for $3.3 billion in 2016. That division of labor has shaped Alvys from the beginning: Darman supplies the operating scars, while Gorodinski brings experience building large cloud systems. Foundry is the clearest attempt yet to package that combination as a platform rather than a collection of AI features. Alvys already offered AI-assisted load creation, a reporting assistant called Insights and real-time weather and load alerts through Intel. Foundry adds an agent layer that can carry out multi-step operating procedures using the load, customer, document and financial data already stored in Alvys. A controlled launch, not a universal switch Alvys says Foundry includes more than 20 templates covering detention filing, document intake, rate auditing, track-and-trace, claims, compliance and load creation. Users can describe a workflow in plain English, review the generated process, test it against simulated data and then deploy it on a selected lane or a larger book of freight. The second path is conventional: choose a prebuilt agent for a standard workflow. The third puts Alvys engineers into the implementation, building and tuning an agent for a customer that lacks its own technical staff. The product is beginning with a controlled rollout. Alvys previewed Foundry at its June 17th customer advisory board meeting, filled the initial customer cohort and opened a waitlist for a second group. That sequence matters because autonomous actions inside a TMS can touch invoices, compliance records, customer communications and payments. Foundry is being introduced as operating infrastructure, though the initial deployment is closer to a staged production test than a broad release to every Alvys user. Alvys is pairing the agents with a governance layer called Agent Shield. According to Alvys, administrators can set spending and approval thresholds, require human sign-off for consequential actions, pause agents and inspect an audit trail of decisions and overrides. Alvys also says enterprise agreements prevent model providers from training on customer data. The architecture includes a model router that assigns work based on cost, speed and quality rather than committing every task to one large language model. The approach could become important once an agent moves from a demonstration to processing thousands of loads. A premium reasoning model may make sense for an unusual claims dispute. Reading a standard proof-of-delivery document may call for something cheaper. The TMS is becoming the distribution channel Alvys is entering a freight software market that has moved quickly from AI assistants to agents embedded in the system of record. Trimble announced AI agents https://news.trimble.com/Trimble-Announces-New-AI-Agents-and-Workflows-to-Automate-Critical-Transportation-Operations?asPDF=1 for order intake, invoice scanning and roadside breakdowns in November 2025. Tai TMS introduced an automated track-and-trace agent https://tai-software.com/tai-tms-introduces-ai-track-trace-agent-making-check-calls-a-thing-of-the-past/ in April 2026. Transfix previewed AI exception management https://transfix.io/press/transfix-previews-end-to-end-ai-exception-management-for-freight-brokers-and-3pls in May. On August 5th, McLeod Software and Augment announced https://www.mcleodsoftware.com/why-mcleod/resources/press-releases/mcleod-software-and-augment-announce-ai-integration-to-automate-logistics-workflows-in-powerbroker-tms/ that Augment's agent would operate inside McLeod's PowerBroker TMS for carrier selection and shipment tracking. That competitive activity narrows the significance of Alvys' claim that Foundry is built in rather than bolted on. Embedded AI is rapidly becoming table stakes in transportation management. Alvys' sharper distinction is the attempt to give operators a builder, reusable templates and implementation help within the same product. Darman is framing that design as an answer to vendor dependence. In the launch announcement, he recalled paying software providers for each customization, report and integration while running his freight operation. "Vendors got me started, then charged for every customization, every report, every integration," he said. Foundry turns that frustration into product strategy. Alvys wants customers to encode standard operating procedures themselves instead of sending every change request to an automation vendor. That is attractive in freight, where two carriers moving similar loads can still have different escalation rules, customer scorecards, appointment practices and approval limits. The promise also creates a new form of dependence. Once a freight operator has converted its procedures into agents that run on Alvys data and integrations, changing the underlying TMS becomes a larger migration. The customer may control the workflow blocks, but Alvys owns the environment where those blocks access operational context and take action. Foundry can give operators more control over individual automations while making Alvys harder to replace. That is sound vertical-software strategy. AI features are easy to demonstrate and increasingly easy for competitors to copy. Deeply encoded operating procedures, approvals, integrations and historical freight data create a stronger retention mechanism. Darman's $40 million AI commitment reaches the product Foundry is the first major test of the AI plan Alvys attached to its September 29th, 2025 Series B https://alvys.com/blog/alvys-raises-40m-series-b-to-drive-ai-powered-efficiency-and-roi-for-carriers-and-brokers . RTP Global https://rtp.vc/going-the-extra-mile/ led the $40 million round, with Alpha Square Group https://www.alphasquare.com/ , Titanium Ventures https://ti.vc/ , Picus Capital https://www.picuscap.com/ and Bonfire Ventures https://www.bonfirevc.com/news/why-we-invested-in-alvys participating. Alvys says it has raised $77 million in total. At the time, Darman said the capital would put AI at the center of dispatch, decision-making and back-office workflows. Foundry moves that spending from a roadmap statement into a product that customers can test. It also gives Alvys a route to expand beyond TMS subscriptions by becoming the automation layer for work that previously required staff, outsourced services or separate point products. Alvys has not described Foundry's commercial model in the launch materials. Its economics will still shape adoption. Model calls, implementation help and continuous agent execution introduce variable costs that ordinary seat-based software does not carry. The intelligent model router addresses the compute side, while templates can reduce the amount of engineering Alvys must provide for each customer. The other part of the expansion is customer size. Alvys said on August 17th that its TMS would be accessible to fleets of all sizes, including owner-operators and small carriers. That returns Alvys to Darman's original thesis: smaller freight operators should have access to software capabilities historically reserved for larger carriers and brokers. Alvys reports more than 2,000 customer companies, more than 3,000 motor-carrier authorities, over 150 employees and more than $7 billion in annual freight moving through its software. Those are Alvys figures, and revenue and Foundry adoption have not been reported. Still, the installed base gives Alvys something standalone freight-agent vendors must build through integrations and partnerships: direct access to the records and workflows that determine what an agent is allowed to do. The real test is boring work at production scale Foundry's strongest early use cases are deliberately unglamorous. Detention tracking, document classification, status calls and invoice preparation happen constantly, follow repeatable rules and consume labor without usually requiring strategic judgment. They also leave clear records that managers can audit. That makes them practical entry points for cautious operators. A carrier can begin with an agent that identifies a late appointment, calculates when detention begins and prepares the required notice. A human can approve the notice before it reaches a customer. The operator gains measurable time without handing the agent control over pricing, safety or a high-value payment. Alvys customer Spartan Carrier Group https://www.spartanfamilyholdings.com/about is serving as the launch reference. Founder and CEO Carlos M. Llanes Jr., a U.S. Army combat veteran who built the Fort Worth carrier around just-in-time and automotive freight, described Foundry as an embedded research and development resource. His endorsement supports Darman's pitch that smaller freight operators can gain technical capacity without hiring an internal AI group. It remains a qualitative account rather than a production benchmark. Alvys will need to show that ordinary operations staff can maintain agents after the implementation specialists step away. Plain-English builders can simplify the first draft of a workflow. Freight procedures still contain edge cases, customer exceptions and legacy habits that rarely fit a clean demonstration. The value of Foundry will come from how quickly an operator can identify a failure, understand why it happened and adjust the workflow without creating another support ticket. Darman has spent years arguing that freight software should match the way operators already work. Foundry pushes that thesis into AI: preserve the procedure, expose the controls and automate the repetitive execution around it. If Alvys can make that loop reliable, the TMS stops being a database employees update after the work. It becomes the place where much of the work gets done.