# Forgepoint raises $9.8M to shrink quote time _Forgepoint raised $9.8M led by Primary and a16z speedrun to scale Frank, an inbox-native quoting agent seeing 30% more throughput._ **Published:** 2026-10-14 **Source:** https://www.startuphub.ai/ai-news/funding-round/2026/forgepoint-raises-9-8m-to-shrink-quote-time --- Forgepoint raised $9.8 million in seed funding led by Primary Venture Partners and a16z speedrun, the company said , with angels from [OpenAI](https://www.startuphub.ai/ai-news/prediction-markets/2026/ai-ipos-markets-weigh-openai-vs-anthropic), Brex, Vercel and SoFi also participating. The number that matters is speed to quote. Forgepoint said customers using Frank, its AI Inside Sales Rep, process 30% more quotes per month on average while cutting time-to-quote by more than 55%, and that the company reached seven-figure ARR within six months of launch as of October 2026 with hundreds of engineers, estimators and sales reps using Frank weekly. Gardner Intelligence put context on that in 2025, finding nearly 50% of manufacturers expect a vendor response within 24 hours, according to Forgepoint. Frank is not a portal. It joins like an employee, with an email address on the company domain, and works inside the systems quoting teams already use. When an RFQ lands, Frank reads the email and attachments, flags missing specs and asks the buyer for clarification, then builds a draft using the shop's own pricing rules, surfaces similar historical jobs and routes it for human review. After approval it generates the document in the company template, sends it, handles follow-up and logs the thread, per the announcement. That configuration is the mechanism. Quoting logic varies by process, so Forgepoint said it tailors Frank per shop. At a metal service center Frank matches material lists and cut lengths to the catalog, applies customer-specific pricing and checks inventory. At a foundry it reviews part files, gathers missing drawing specs and prepares a first draft for an engineer. The same pattern extends across injection molding, automation, fabrication, stamping and machining, with engineers and salespeople keeping technical and commercial decisions while Frank carries the handoffs and data entry. "We kept meeting manufacturers with strong demand and capable teams, but their best people were spending hours on administrative work. Speed is a competitive advantage, so we built Frank to keep jobs moving," said Jack Strauss, CEO and co-founder, who previously worked at Northrop Grumman, Bain's Advanced Manufacturing practice and Xwing. Co-founder and CTO Alex Pareto was previously Head of Engineering for Brex's Spend Management organization. The data do not show win rate or margin impact. Throughput and time-to-quote are averages across early customers, without disclosure of shop count, ACV, retention or how often drafts require major rework, and without a benchmark for RFQs that still need engineering judgment. One disclosure would change the read: a cohort view of quotes that needed no edits versus those routed for review, tied to purchase orders won. If Frank preserves every email and pricing decision as a system of memory, as Forgepoint said, the open question is whether that memory raises close rates without pulling humans back into the loop it was built to clear. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory. © StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training on this content requires a license. See https://www.startuphub.ai/terms.