Cortex
CortexThe Architecture of High-Yield Inference

AI is metered in tokens. Humans care about outcomes.

Cortex reconstructs work from scattered AI conversations, cross-application artifacts, and token streams so organizations can value, govern, and improve the outcomes.

The semantic engine · animated

Signals become attributed work.

Cortex observes activity, links the surrounding context, and infers Work Units that retain their people, agents, applications, and cost.

Observed
Linked
Labeled

Complete semantic flow:

  • Observed activity from Slack, Cursor, Jira, Claude, GitHub, and Notion.
  • The Semantic Engine links the surrounding context.
  • Labeled Work Units retain people, agents, applications, and cost.
  • Related Work Units form the Customer escalation responses Work Stream.
Work StreamCustomer escalation responses
Work Unit · Customer escalation responseSources and inferred relationships remain inspectable.
The work model

The system adapts to the organization.

Work topology

Units become streams. Streams advance the roadmap.

Every Work Unit retains its source records. Work Streams stay linked to the roadmap items they advance, alongside Google Workspace, Jira, Notion, and conversation evidence.

Work Units

3 of 38 shown
SUP-928
SlackJiraNotion

Respond to API outage

Resolved · Trace impact and verify recovery.

People
Models
Cost
$2.84
SUP-913
JiraSlack

Resolve billing dispute

Resolved · Validate charges and the approved adjustment.

People
Models
Cost
$1.62
SUP-902
JiraNotion

Find missing evidence

Reopened · Reconcile the incomplete case record.

People
Models
Cost
$0.94

+35 more Work Units

Work Stream
Customer escalation responses

Resolve urgent customer issues

38 Work Units22 min baseline · 91% accepted
People
12 contributors
Models
126 model calls
Cost
Total across 38 WUs · 30d$73.10

Roadmap item & linked records

Google WorkspaceCustomer experience roadmap · Q3JiraSUP projectNotionEscalation runbookSlack#support-escalations

Work Units

2 of 17 shown
KB-144
NotionGitHub

Publish incident runbook

Published · Turn the response into reusable guidance.

People
Models
Cost
$1.76
KB-139
NotionSlack

Review escalation playbook

Reviewed · Check steps against recent outcomes.

People
Models
Cost
$0.88

+15 more Work Units

Work Stream
Support knowledge maintenance

Keep support guidance current

17 Work UnitsMonthly cadence · Maya Voss
People
8 contributors
Models
49 model calls
Cost
Total across 17 WUs · 30d$28.70

Roadmap item & linked records

Google WorkspaceService quality roadmap · Q3NotionSupport knowledge baseGitHubRunbook repository
Product principles

Quiet by default. Explicit when it matters.

Cortex runs in the background, learns the existing workflow, and surfaces only when it can help or when a decision needs attention.

  • 01Observe quietlyLearn from supported capture paths in the tools people already use.
  • 02Intervene at decision pointsRoute, approve, restrict, or block only on configured managed paths.
  • 03Explain every actionKeep the reason, policy, and supporting evidence inspectable.
Atlas

Atlas maps work, learns its baseline, and ranks what matters.

Repeated Work Units reveal the expected pattern, meaningful variance, and the highest-value place to investigate next.

Cortex workspace · Work Stream

Customer escalation responses

38 related Work Units · 30-day learned baseline · SUP-928 selected

Maya Voss

Review owner

Maya Voss · Support operations

Linked evidence
  • Slack18 messages
  • JiraSUP-928
  • NotionP1 playbook
  • GitHubPR #1842

01 · Expected baseline

Evidence-linked response

22 min baseline

Expected pattern

  • Ticket, playbook, and mitigation are linked before drafting.
  • Owner verifies the evidence before the customer send.

02 · Observed variance

41 min observed
  • Context rebuilt manually across four source systems.
  • Two edits added evidence already present in the Work Unit.

03 · Outcome feedback

91% accepted
  • Positive: owner-approved, linked response accepted.
  • Negative: reopened, edited, or missing-evidence response.

04 · AI Opportunity Map

Ranked from observed work

Directional priority
  1. 01Reduce context reconstruction72/100
  2. 02Automate evidence verification61/100
  3. 03Tune the escalation route47/100
Atlas observes and ranks. It does not change the workflow.Window · Jun 29 through Jul 28, 2026 · 38 Work Units · priority is not production ROI.
Foundry

Foundry intervenes and optimizes.

Atlas supplies the constraint, success measure, and safety boundary. Foundry selects the intervention it can defend.

Foundry decision receiptAtlas context · Customer escalation responses

SUP-928 · customer escalation response

Foundry decision receipt

Owner approval pending

Work Unit requirements

Constraints travel with the work
Policy
Linked evidence
Release gate
Owner approval
Quality floor
≥ 0.92 verifier
Cost ceiling
≤ $0.18 / call
Latency target
≤ 3.2s p95

Candidate routes

Private eval replay · 250 cases · Jul 28, 2026
  1. ClaudeClaudeClaude Sonnet 5
    Selected
    Policy
    Eligible
    Quality
    0.94
    Cost
    $0.14
    Latency
    2.8s
  2. OpenAIOpenAIGPT-5.6 Terra
    Policy
    Eligible
    Quality
    0.90
    Cost
    $0.11
    Latency
    2.4s
  3. GeminiGeminiGemini 3.6 Flash
    Policy
    Eligible
    Quality
    0.88
    Cost
    $0.07
    Latency
    1.9s

Route selected

Semantic routing selected

Claude Sonnet 5

Why this route

  • ✓ Linked evidence makes the route policy-eligible.
  • ✓ Clears quality, cost, and latency requirements.
  • ✓ Preserves the owner approval gate.

Replay snapshot

0.94 quality · $0.14 · 2.8s p95

Single model invocation per case; customer send still requires owner approval.

Foundry suite

No silver bullets. Use the right lever.

Governance and security surround every intervention; supported and configured paths define the enforcement boundary.

  • Use when

    Model cost and quality vary by task

    Semantic routing

    Choose against the Work Unit requirements.

  • Use when

    The request is missing approved context

    Just-in-time prompt enrichment

    Bring linked evidence into the request at runtime.

  • Use when

    Repeated work has private verifier data

    Model distillation

    Hill-climb against proven private outcomes.

  • Use when

    An agent exceeds appropriate autonomy

    Agentic governance

    Apply the right policy and approval boundary.

  • Use when

    Sensitive context approaches an unsafe destination

    Semantic security

    Control the configured path using full work context.

Map your first Work Stream.

Bring one important workflow. We will trace the work, its outcomes, and the constraints that should govern it.