Glow is the private introduction and scouting platform. The matching intelligence that already helps people find their people, now working for the communities, marketplaces, events and revenue teams whose growth depends on the right connection.
Glow brings value from day one because two systems work together to unlock the right connection without the cold-start problem that breaks most matching products. Identity, intent and context live inside one private graph; the two engines decide what to do with it.
Glow understands who someone is and what they're honestly looking for, then matches across deeper dimensions than labels. A growing user understanding makes every introduction sharper than the last.
Scout looks outward, proactively finding the people, communities and businesses that should already be in your graph, and surfacing the warmest path to a real introduction. External networks become scouts; cold lists become obsolete.
Three commitments shape every part of the platform. They are the same commitments that make consumers trust Glow with the most sensitive things they want to share, applied to the introductions, recommendations and routing your business depends on.
Beyond filters, beyond ICP labels. Glow learns context: goals, situation, history, what the person is actually trying to do this week.
The most predictive signals are the ones people would never share publicly. Latent embeddings, zero transcripts, no raw data stored. Privacy is the product.
The right person is often outside your network. Glow finds the warmest route to them through customers, members, alumni, or trusted intermediaries.
Glow is designed for organizations whose business depends on the quality of the introductions they make: communities, conferences, marketplaces, service teams and modern revenue orgs. Each use case starts as one workflow on the same private graph, then compounds.
Glow sits between the agents and humans on each side of an introduction. It computes matches on latent embeddings, also known as privacy-preserving vectors, so the platform learns who fits whom without storing transcripts, raw conversations, or public profiles.
Most enterprise GTM tools work by capturing more and more signal about people who never opted in. Glow is the opposite. Customers and members share openly with their own agent, and Glow uses that intent to make the right introduction without exposing the raw data, even to you.
Sensitive preferences become latent vectors. Privacy-preserving matching turns intent into introductions, without saved transcripts, public profiles, or raw data to defend.
Identity, intent and matches are computed on privacy-preserving vectors. Your team sees outcomes: accepted intros, meetings, qualified leads. Not raw conversation content.
Members and customers stay in control of what gets shared and with whom. Permissions follow them across every introduction, recommendation and scout run.
SSO, audit logging, data residency, SCIM, VPC deployment, and a model boundary your security team can actually defend to the board.
Glow connects to your CRM, helpdesk, community platform, event stack, calendar and messaging, so introductions and recommendations show up where work already happens. No rip-and-replace, no data migration required to start.
Whether you run a community, a conference, a marketplace or a revenue team, Glow helps you make more of the connections that actually move the business forward. Pilots run in 90 days: one workflow, one integration, one success metric.