Your Knowledge. Ready for AI.
Glymr helps companies make internal knowledge usable for people, processes, and AI — by identifying knowledge friction, mapping how work actually happens, capturing critical expertise, and turning scattered knowledge into practical operating assets.
What Glymr Is
Glymr is a consulting firm focused on organizational knowledge, process clarity, and AI readiness. Most organizations already possess valuable knowledge they cannot fully use — spread across people's heads, scattered systems, undocumented processes, and informal workarounds. Glymr identifies where that friction is costing the business, maps how information and processes actually move, captures critical expertise before it disappears, and turns what's been found into practical assets people and AI can rely on.
Why This Work Exists
AI does not solve fragmented knowledge and unclear processes — it exposes them. Every company now sits on top of decades, or at least years, of decisions, exceptions, relationships, and know-how that were never written down because they didn't need to be. That knowledge was manageable when a handful of experienced people carried it. It isn't manageable anymore, whether the pressure is growth, an acquisition, a leadership transition, or a push to get real value out of AI.
Glymr was founded on the idea that this problem is solvable — not through more software, but through the deliberate work of identifying what knowledge matters, capturing it, structuring it, and governing it so it stays useful. That work has always mattered. It matters more now that AI systems are only as reliable as the knowledge underneath them.
About the Founder
Glymr was founded by Jeff Greenhouse, an entrepreneur, knowledge-management strategist, and commercial analytics executive who has spent his career turning fragmented information into systems people can actually use. Before founding Glymr, he held senior analytics and data leadership roles at AMC Networks, Discovery Communications, and Scripps Networks Interactive, building forecasting models, dashboards, and measurement systems that product, marketing, and executive teams relied on directly. A colleague from his Scripps and Discovery years described what that looked like in practice:
"Jeff can work and communicate with data engineering and marketing stakeholders both. … Ultimately the data collected and the business outcomes driven are enhanced greatly because of Jeff's ability to understand the entire data pipeline and connect groups that don't understand each other's disciplines."
That experience shaped Glymr's approach: knowledge work should be judged by whether it changes what people can do, not by whether it produces documentation. Jeff has developed several of Glymr's core methods, including Data Landscape Mapping, Knowledge Exit Interviews, and structured Executive Knowledge Transfer — used with clients ranging from founder-led companies to organizations formed through acquisition, including engagements that have mapped environments spanning more than 300 systems and uncovered technology that IT leadership believed had already been retired.
"I can tell you from first hand experience that Jeff is a no nonsense consultant that understands the underlying problem organizations have harnessing the power of existing company knowledge. … Jeff himself is the real deal."
How Glymr Makes Your Knowledge Usable for People, Processes, and AI
Glymr's engagements follow a consistent model: Identify where knowledge friction, risk, and AI-readiness gaps are slowing the business down. Map how information, processes, and systems actually move. Capture the expertise and context that would otherwise be lost. And make it usable — through documentation, knowledge architecture, governance, and adoption support that people and AI systems can actually rely on.
See how this shows up across Glymr's services and what makes Glymr different.
Related Reading
Start with Knowledge Friction to understand the core problem Glymr was built to address.
Find out whether your company's knowledge is usable by the people and AI systems that need it.
A Knowledge Friction Assessment or AI Effectiveness Assessment gives you a clear, quantified picture of where your organization is losing time, money, and AI value — and what to do about it.