Your business knows things AI doesn't.
Lore is where it remembers.
Every team carries knowledge that never makes it into a document: the vendor your predecessors abandoned, the compliance edge case that burned you, the judgment your best estimator carries in her head. Lore captures it and makes it available to both people and AI.
Four kinds of memory.
One place to query them.
Institutional knowledge is scattered across email threads, meeting notes, and the heads of senior staff who may not be here next year. Lore pulls these into a structured, queryable substrate that grows more valuable the longer your team uses it.
Why your team made the choices it made
When a decision is recorded in Lore, it carries the full context: alternatives considered, reasoning, and the conditions that would change it. Future decisions start from what you already know.
What this looks like in practice
What actually happened, not just what was planned
AI agent sessions, project timelines, workflow runs — the real record of how work unfolded. Lore indexes these against the decisions they relate to.
Why traces matter
The attempts that didn't make it into the official record
Abandoned approaches, vendor evaluations, experiments that ran before you joined. Lore surfaces this before your team wastes time rediscovering it.
The knowledge most likely to be repeated
The recurring signals across projects and quarters
When Lore can see across multiple projects, it finds connections no single project owner would notice. These become durable guidance, not tribal knowledge.
What patterns look like
Every piece of memory
relates to another.
Lore doesn't store knowledge as a list — it maps it as a graph. When you query a topic, you surface the whole web of context, not just the nearest document.
Memory is the compound advantage.
Generic AI tools have no memory of your business. They start fresh every session. Lore changes that — for your people and for the AI working alongside them.
AI that knows your history
An AI answering a question about a vendor, a project approach, or a compliance edge case should know what your business already learned. With Lore as its context layer, it does.
"The model didn't know we'd already tried that vendor. Now it does."
People who can query what came before
A new operations manager shouldn't spend six months re-learning what the previous one figured out. Lore makes institutional knowledge searchable — decisions, rationale, outcomes — so onboarding accelerates.
"Six months of context, available on day one."
Knowledge that compounds instead of decaying
Most institutional knowledge degrades when people leave. Lore inverts this. Each project, each decision adds to a substrate that becomes more useful over time, not less.
"Gets smarter every quarter. Not the other way around."
Context for the whole Foundry platform.
Lore is the knowledge substrate the rest of the platform draws from. It doesn't work in isolation — it feeds context into every layer that needs to know what your business already knows.
Context inside the cockpit
When your team reviews an AI workflow run in Forge, Lore surfaces related decisions and prior attempts — full context, not just the action in front of them.
Evidence that accumulates over time
Temper measures what's working. Lore remembers why. Experiment results and quality trends land in Lore and become searchable — so the next similar question starts from evidence.
Informed answers instead of generic ones
Any AI workflow can query Lore mid-execution. The estimator workflow knows your historical bid data. The compliance workflow knows your prior exception history. The output reflects your business.
Talk to us about Lore.
Lore is part of every Foundry engagement. When we embed, we capture institutional knowledge from day one: decisions made, approaches tried, patterns observed. By month six, your AI and your people draw from the same growing foundation.