Actively

I'm one of the founders of Actively. We're building best-in-class machine learning and LLM-powered scoring for outbound sales teams. Our first product lives in Salesforce, ingests data from a variety of sources (firmographics, intent signals, marketing interactions, and prior engagement, including unstructured call transcripts, email chains, and notes), and combines LLMs with structured models to tell sales reps who they should reach out to each day (and why) to be laser-focused. Our paying customers are fast-growing unicorns you've definitely heard of with large outbound sales motions, where the reps use us to target their outbound every day. Our thesis is that scoring (a known/'need to have' part of the stack -- but able to be done 10x better with LLMs because you can incorporate the goldmine of unstructured engagement data) is the right wedge into building the intelligence-driven outbound sales stack of the future that _actually works_ for large companies that need to generate millions of dollars in pipeline each quarter. Unlike most other companies in the space, we are explicitly building for companies of this scale and have them using our product today 'in production.' We started with the vision of bringing AI to every business team, and have since narrowed down to focus on outbound sales teams who have a bunch of attractive properties (there are a _ton_ of them out there, they all use the same stack, the data is consolidated in one place, lift is measurable and directly touches the top line, etc.). We're a team of 6 working in-person in NYC with a team from Scale/Waymo/Google/etc. (including some very senior folks) and looking to bring on another engineer as we start scaling our customer base. If you have at least a few years of experience, are highly entrepreneurial / excited to work closely with customers + dig in across the business, and are excited to work on some combination of LLMs/data infra/across the stack, we would love to chat: mihir [at] actively.ai! Keywords: AI, ML, LLMs, machine learning, Salesforce, explainable AI, product engineering, data infrastructure