John Glasgow of Campfire, chief executive officer and co-founder, appears in this theCUBE Research interview hosted by John Furrier and Gabe Olave at the NYSE Wired Business Transformation Edge series. Glasgow discusses artificial intelligence-native finance transformation, enterprise resource planning migration, domain-specific models for accounting workloads and agent-driven finance automation. They explain Campfire's approach to migrating legacy ERP systems, building post-trained finance models and deploying agents to automate reconciliations, accruals and continuous close workflows.
Key takeaways include accelerated migration timelines, deterministic finance models and agent-driven automation that reduce manual accounting work. Glasgow states Campfire's post-trained models and agent layer enable near-zero tolerance for inaccuracies in financial reports, support real-time continuous close and convert token-driven AI costs into manageable capital expenditure when running proprietary models. Analysts on theCUBE note parallels with Ramp and a broader shift up the AI-native stack.
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John Glasgow, Campfire
John Glasgow of Campfire, chief executive officer and co-founder, appears in this theCUBE Research interview hosted by John Furrier and Gabe Olave at the NYSE Wired Business Transformation Edge series. Glasgow discusses artificial intelligence-native finance transformation, enterprise resource planning migration, domain-specific models for accounting workloads and agent-driven finance automation. They explain Campfire's approach to migrating legacy ERP systems, building post-trained finance models and deploying agents to automate reconciliations, accruals and continuous close workflows.
Key takeaways include accelerated migration timelines, deterministic finance models and agent-driven automation that reduce manual accounting work. Glasgow states Campfire's post-trained models and agent layer enable near-zero tolerance for inaccuracies in financial reports, support real-time continuous close and convert token-driven AI costs into manageable capital expenditure when running proprietary models. Analysts on theCUBE note parallels with Ramp and a broader shift up the AI-native stack.