Inside Glasshouse, the context layer we run on
Why we built Glasshouse, how a sentence in a note becomes a fact an AI agent can trust, and what it costs to run, in eleven screenshots.
Deep Context. Dynamic knowledge structures that map how your business actually operates, not static files or flat lookup tables.
True Identity. Precision identity resolution built for automated execution, not ad-tech retargeting.
Real Authority. Autonomous systems empowered to make decisions and execute, not rigid scripts playing pretend.
Proof in Production. High-impact lifecycle decisions and personalization that deliver clear, measurable outcomes.
System-Wide Guardrails. The brackets surrounding all four layers. Complete agency across data, actions, and personalization within total operational safety.
Meaning, Anchor, Agents, Decision — four layers under one contract. Guardrails are the brackets around all of it.
Built for premium enterprise brands that need agents to act — not just answer.
How we work ↗Why we built Glasshouse, how a sentence in a note becomes a fact an AI agent can trust, and what it costs to run, in eleven screenshots.
What AI agent governance is, what the EU AI Act, NIST and Singapore expect, and why guardrails have to be designed into the system, not bolted onto each agent.
What agent sprawl is, why buying AI agents tool by tool causes it, and what to build instead: one agent factory with shared context, identity and guardrails.
Why product data models fail agents, and what a described relationship actually buys you.
Match rates are a vanity metric until an agent acts on the match.
A field guide to what is actually running in production agent stacks.
Budgets, blast radius, and the approvals a CFO will sign.