Account Executive
Trellis
Account Executive
Trellis
AI-driven state trial court research analytics
Salary Range: 100000 to 200000 (Currency: USD) (Pay period: per-year-salary)
You'll proactively identify and engage decision-makers across legal departments, including general counsel, risk management teams, and other key stakeholders. From initial outreach and discovery to product demos, negotiations, and closing, you'll own the full sales cycle and be accountable for driving new customer acquisition.
While you'll have access to inbound leads from marketing and our website, your primary focus will be on generating your own opportunities through strategic outbound prospecting, cold outreach, and relationship building. You'll also maintain accurate and organized pipeline activity in HubSpot, ensuring consistent follow-up and visibility into deal progression.
As part of a lean, rapidly growing team, you'll need to be resourceful, self-motivated, adaptable, and comfortable operating with a high degree of autonomy. You'll thrive in an environment where priorities evolve, initiative is valued, and you're empowered to take ownership of your results.
Above all, you'll be an ambassador for Trellis, representing our brand with professionalism and enthusiasm while building meaningful relationships, understanding customer needs, and turning new business opportunities into long-term partnerships.
Trellis is an AI-powered legal research and analytics platform focused on state trial court data. It provides a comprehensive search engine for state trial court records, allowing lawyers to find and analyze case law, legal documents, and data. Features include Judge Analytics, which offers insights into a judge’s ruling history and verdict data. The platform uses artificial intelligence to analyze and categorize court opinions, helping users quickly identify relevant information. Trellis serves law firms and legal professionals on a subscription basis. Its goal is to make legal research and case strategy more efficient and effective by aggregating and analyzing large volumes of trial court data.
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