Problem

Lunavo targets freight forwarders, logistics companies, and trucking carriers whose operations depend on manual back-office coordination. Teams spend substantial time entering orders, updating portals, checking systems, answering status requests, and managing documents instead of moving freight or serving customers. The resulting information overload also hides exceptions—such as delayed pickups, missing documents, and customer escalations—until they become urgent. Lunavo’s website says a 200-truck carrier may have 30–60 back-office employees whose staffing scales linearly with load volume, while manual document workflows can extend days sales outstanding by 7–14 days and tie up working capital.

The clearest use case is a delayed truck or pickup. Without automation, a dispatcher may need to check a GPS portal, notify the customer, update the TMS, and update the customer’s portal—a process Lunavo says can take up to 15 minutes. The company also addresses a less visible problem: operational knowledge lives in experienced dispatchers’ heads, making the business vulnerable when employees leave and making it difficult to scale volume without adding headcount.

Product / Service

Lunavo is positioned as an AI workforce or AI teammate that works inside a carrier’s existing tool stack rather than replacing it. It connects to TMS platforms, email, portals, and related systems; reads incoming emails, PDFs, and spreadsheets; extracts and plausibility-checks data; applies customer-specific rules; creates or updates loads; and confirms actions with customers. Its agents can adapt using dispatcher feedback, company documentation, and user-defined rules.

The product covers order intake, quoting, shipment-status responses, margin-based dispatch decisions, document and invoice workflows, and exception handling. Routine cases can be handled automatically, while issues involving financial exposure, uncertainty, or operational judgment are escalated with context. Lunavo claims that customers can automate up to 85% of repetitive back-office work within 60 days, handle three times as many loads per dispatcher, and reduce response and billing-cycle times, though these are company-reported performance claims rather than independently verified results.

Market

Lunavo competes in vertical AI operations software, logistics SaaS, and freight-workflow automation, with an initial focus on the back offices of trucking carriers and freight forwarders. The competitive set includes incumbent TMS functionality, internal manual processes, and adjacent automation vendors. Neurored, for example, markets automation for transportation and logistics document processing, while Drumkit markets AI workflow automation for freight brokerage; these appear adjacent rather than necessarily identical, head-to-head offerings. Lunavo’s differentiation is the attempt to operate across a carrier’s existing systems and autonomously manage whole workflows and exceptions, not merely automate one document type.

The company appears to be an early commercial-stage startup. Y Combinator lists Lunavo as an active Fall 2025 company founded in 2025 with a two-person team, and PitchBook reports $500,000 raised from investors including Y Combinator and StartPort. Lunavo publicly advertises operational benchmarks and a live intermodal-forwarder workflow, but does not disclose named customers or a revenue figure in the available sources. PitchBook labels the company as generating revenue while leaving current revenue blank, so the evidence supports early commercialization but not a claim of meaningful scale.