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Context Components · Context Graph

Improve agent behavior
with active decision traces and evals.

A context graph records the decisions behind the data: what was resolved, why, and what still applies. Atlan captures agent traces, evals, and human overrides, then promotes the pattern into governed memory every agent inherits.

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What was decided, and why

An agent trace recorded in the context graph: the disputed charge that came in, the tool call that found it refund-eligible, the decision to escalate, the human review that approved it and set a standing rule, and the outcome that was logged.

AGENT TRACE · run #81271 OF 5 NEAR-IDENTICAL

support-agent · yesterday, 4:15 PM

INPUTDisputed roaming charge · $40falls inside the BK-07 outage window
TOOL CALLknowledge_graph.lookup()⇒ refundEligible = true
DECISIONNew dispute patternescalated for human review
HUMAN REVIEWApproved · tower fault mis-triggered roamingstanding rule: refund BK-07-window disputes
OUTCOME$40 refunded · reason code: outage_credittrace logged to the context graph
ANSWERS“What has already been decided about cases like this?”
A knowledge graph knows what exists. A context graph knows what was decided.

Trusted by AI-forward enterprises

"Atlan is our context operating system to cover every type of context in every system including our operational systems. For the first time we have a single source of truth for context."

Sridher Arumugham

Chief Data Analytics Officer, DigiKey

"We built a revenue analysis agent and it couldn't answer one question. We started to realize we were missing this translation layer. We had no way to interpret human language against the structure of the data."

Joe DosSantos

VP Enterprise Data & Analytics, Workday

"Atlan has been a really good partner in helping us figure out how to register AI models and applications, and what metadata to put in place to meet the transparency requirements that [AI Governance] legislation asks for."

Sherri Adame

Data Governance Lead, General Motors

"We're focused on how we can scale context development as much as possible, and where can we leverage Atlan AI to build the most robust definitions across our data estate and make sure we're propagating it upstream and downstream."

Takashi Ueki

Head of Enterprise Data & Analytics, Elastic

WTF IS THE CONTEXT LAYER

A bi-weekly live series for AI leaders and builders. One burning question per episode, an open AMA floor, and guests who've actually built context infrastructure.

EP 06Can a Context Graph Alone Make AI Reliable?Thu, Sep 17 · 12:30 PM ET
Late last year, Jaya Gupta called the context graph AI's next trillion-dollar opportunity: the reasoning behind a company's decisions that systems of record never stored. What it left unsettled is whether a strong graph is enough alone, or whether reliable AI needs the context layer around it — the wider system that governs how those decisions get used. Jaya joins Austin to work through what a context graph must hold and where it stops.
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Can a Context Graph Alone Make AI Reliable?
THE AI CONTEXT GAP

One question.
Three kinds of context.

Knowledge is what happened before. Expertise is what the team did about it. Norms are who signs off. A context graph keeps the record of all three.

Knowledge

Has this happened before?

Three prior spikes at store 412 — two turned out to be POS clock drift, not a real slowdown

Expertise

What did we do last time?

Check the POS clock first. That became the standing first move after the second false alarm

Norms

Who signs off on the finding?

A clock-drift call ships itself; a real slowdown goes to the regional lead first

CONTEXT COMPONENTS

No agent runs on
a context graph alone.

It remembers what was decided. What a metric means, which table is certified, and how the business is structured are held elsewhere.

What was decided before, and why?

Working and episodic memory die when the session resets. Decision traces and the lessons behind them belong in durable, governed memory, where the next agent starts from what the last one learned.

Explore Memory & Context Graph
EPHEMERAL · DIES WITH THE SESSIONCase #4471cancelled 23:42, chargedCase #4522cancelled 23:51, chargedCase #4610cancelled 23:58, chargedpromotehuman reviewDURABLE · GOVERNED · SHAREDSEMANTIC MEMORYBatch posts cancellationsup to 3h latecertified · v2 · ops-billingPROCEDURAL MEMORYOn cycle-boundary disputes,use request_ts not processed_tsFive identical cases become one certified lesson

EPHEMERAL · DIES WITH THE SESSION

Case #4471cancelled 23:42, charged
Case #4522cancelled 23:51, charged
Case #4610cancelled 23:58, charged
promote · human review

DURABLE · GOVERNED · SHARED

SEMANTIC MEMORYBatch posts cancellations up to 3h latecertified · v2 · ops-billing
PROCEDURAL MEMORYOn cycle-boundary disputes, use request_ts not processed_ts
Five identical cases become one certified lesson
HOW IT WORKS

Most systems let agent traces expire as logs.
Atlan promotes them into context every agent inherits.

The evidence already exists. It just usually gets thrown away.

Most systems let traces sit as logs and expire. Atlan treats them as runtime signals and feeds them back into the context layer, where a repeated pattern becomes visible instead of being rediscovered by each new agent.

Scout
Ranks assets by usage intelligence — surfaces what your team queries most.
Stage 1 · Foundational
⚡ Purpose
Ranks assets by usage intelligence — surfaces what your team queries most.
Task Plan
Scan SQL query historyacross all teams and use cases
Identify top-queried assetsby team, frequency, and function
Rank by usage scoreand assign enrichment priority
Revenue Assets
Product Analytics
Customer Data
Revenue assets · ranked by usage
5 assets
finance.revenue_table
847 queriesGold Layer ↑
finance.arr_cohort
693 queries
billing.invoices
541 queries
finance.mrr_breakdown
418 queries
finance.ltv_by_segment
263 queries

Precedent becomes policy only when someone owns the call.

A pattern is a candidate, not a fact. Context Engineering Studio runs it through the same lifecycle every other piece of context gets, so what becomes canonical is what a human owner decided should be.

Context Studio/Repositories/finance-revenue
revenue.yml
synced to 4 agents
Last updated 2h ago · v3.1.2
name: "revenue"
domain: finance
version: 3.1.2
definition: "Net sales after returns, post-tax"
window: "Q4 — fiscal year close"  # updated by AI · approved by @jsmith
consumers:  # Cortex · LangGraph · Genie · Claude
framework: any # LangGraph, Cortex, Genie, or your own
Recent activity
AI drafted revenue.yml v3.1.2 — updated fiscal window definition
2h ago
@jsmith approved — no changes needed
2h ago
Pushed to 4 agents — all consuming v3.1.2 automatically
2h ago
Consuming this repo
Snowflake Cortex
LangGraph
Databricks Genie
Claude (MCP)
All on v3.1.2

What one agent learned on Tuesday, every agent knows on Wednesday.

A lesson that reaches one agent is a patch. A lesson that reaches every agent is institutional memory. Atlan serves certified decisions through the same interfaces that carry the rest of the context layer.

Cortex Analyst
Natural Language Query
Run
Powered by Snowflake Cortex
via Atlan MCP
Fetching context from Atlan MCP...
→ resolve_metadata · search_assets
MMetricCertified
revenue
Net sales after returns, post-tax
@jsmith
TTable
98/100
orders_fact
owner: Data Engineering
Primary transaction table
Generated SQLQuery ready
1SELECT
2 product_line,
3 SUM(net_sales) AS revenue -- metric defined by Atlan
4FROM orders_fact
5WHERE fiscal_quarter = 'Q4'
6GROUP BY product_line;

See the context layer, built live.

Watch Atlan engineers bootstrap, test, and deploy enterprise context on real data — from cold start to production-ready agents.

The Enterprise Context Layer Architecture in ActionWed, Aug 26 · 11 AM ET
The teams winning with AI are not the ones with the best models. They are the ones building context that compounds. Watch Atlan mine knowledge from your existing stack, build and certify a context layer through a development lifecycle, and deploy it to any agent platform.
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Isabella Steains
Isabella SteainsStrategic Solutions Engineer

Stop relearning
what your team already knows.