Exceptional founders building at the intersection of AI & UX. We're proud to back these companies, write their first checks, and stay close enough to actually help.
Andiron makes it easy for marketing teams to understand what really drives business. The insight is that the data that often drives buying decisions is found outside of the traditional analytics and marketing channels. Andiron surfaces these insights and turns them into actions.
Arbor solves the content multiplication problem that every thought leader faces. You have hours of valuable video content from podcasts, talks, and interviews, but turning it into social posts, clips, and articles is a full-time job. Arbor’s AI transforms one piece of long-form video into optimized content for every channel.
Deviceflow turns the chaos of medical device operations into streamlined automation. Sales reps spend 72% of their time not selling, buried in case scheduling, inventory tracking, and coordination across systems. Deviceflow’s AI agents interpret texts, emails, and calls to handle it all automatically.
Empromptu turns ‘AI features in the backlog’ into shipped, production-ready applications. The problem: 95% of AI features never make it to production. Empromptu’s Self-Managing Context technology delivers 98% accuracy versus the 60-70% industry average, letting teams deploy real AI capabilities without rewriting their platform.
Solvrays brings modern AI orchestration to one of the most paper-heavy industries on earth. Insurance back offices are drowning in manual processes like claims, underwriting, and policy admin. Solvrays deploys agentic AI that automates 70%+ of these workflows, deploying behind the firewall in weeks instead of the typical 12-month enterprise rollout.
Via AI kills cold outreach by mapping your network for warm paths to any prospect. The insight is simple: buyers trust people they know. Via analyzes your organization’s relationships to surface warm introduction opportunities you didn’t know existed, so you never have to start cold again.
WarmStart makes networking feel human again by turning your email history into relationship intelligence. The platform summarizes every interaction you’ve ever had with every contact, learns your communication style, and crafts authentic, personalized outreach that achieves 20-50% response rates because the messages aren’t templates, they’re genuinely you.
Made In Motion builds your CRM around how your company actually sells, without the consulting bill. Keep Salesforce, HubSpot, or Microsoft Dynamics as the source of truth and they build the working apps it never gave you, like renewals and onboarding, or start fresh with a CRM shaped by a short interview. Tell it how you work, and its agents keep changing it as your business does.
TrueSignal gives AI models and agents better data for evaluating and comparing service businesses. Its TrustRecords turn fragmented business information and first-party operational data into structured, source-backed records that AI can use when answering questions and making recommendations. As discovery shifts from search engines to AI, TrueSignal is building the trusted data layer behind those decisions.
StackYak unifies AI infrastructure into a single stack: GPU compute, model inference, and private network fabric, sold as one quote with one bill. Instead of stitching together separate vendors for reserved GPUs, vLLM serving, and cross-connects, teams pick a layer or take the whole thing, with zero handoffs. It’s infrastructure built for the AI agents founders need to ship next quarter.
Trouve is the AI software operator for enterprise systems. Describe a task in plain language and Trouve’s agents carry it out inside NetSuite, Salesforce, SAP, and HubSpot, following best practices with a full audit trail. Teams get hours of tedious admin work back without touching a single configuration screen.
Nth AI helps enterprises become AI-native. Its platform, Nexus, turns fragmented data, metrics, policies, and business logic into governed context, doing the ontology and data migration work AI agents need before they can be trusted with real decisions. It reuses what it learns across every deployment, so each new team gets to working agents faster.
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