System walkthrough

Watch the Brain Engine turn raw evidence into an intervention decision.

See how OrthancIQ's Brain Engine turns product context, user behavior, and commercial history into a Daily Risk Inbox. Each stage reduces uncertainty: what value means, who is drifting, why it matters, and whether action can still change the outcome.

Setup simulator

Choose how customer evidence enters the Brain Engine.

OrthancIQ does not pretend a request form is enough. The first product moment is defining the evidence boundary, choosing a data path, and turning approved sources into a risk-ready model.

Fastest way to start

Upload the first evidence set with a guided mapping call.

Use CSV or JSON exports, product documentation, billing snapshots, CRM notes, and support history. OrthancIQ maps the fields with you before the Brain Engine creates the first dossiers.

InputsExports, docs, billing, support
Setup motionFounder-assisted mapping
First useful output48 hours after data boundary
Best fitFree Churn Risk Audit
Brain coverage58%
Automation levelManual review
Trust boundaryExplicit exports only
Private rollout path

Install a read-only data agent that structures evidence before it leaves your system.

The agent can sit beside approved systems, normalize events into OrthancIQ's contract, and send only the fields your team has approved for retention modeling.

InputsWarehouse, product DB, support, CRM
Setup motionRead-only connector review
First useful output24 hours after install
Best fitFounder Inbox / Growth Inbox
Brain coverage72%
Automation levelSchema-aware
Trust boundaryApproved fields only
Operational inbox path

Stream product events and business context into a living user-health model.

Once the evidence contract is stable, API events and webhooks keep the Brain Engine current: usage, activation milestones, billing movement, support heat, and ownership changes.

InputsEvents, webhooks, CRM, billing
Setup motionEvent contract + validation
First useful outputDaily refresh cycle
Best fitScale Inbox / Retention Lab
Brain coverage84%
Automation levelContinuous
Trust boundaryValidated event contract
Live walkthrough

Follow one user through the Brain Engine.

The walkthrough below shows the internal path from messy customer evidence to a ranked founder action. Click any stage, or let the sequence run.

Sources · Bring your evidence
Upload the evidence your dashboard does not understandCSV, PDF, Markdown, JSON · or connect a source
DOCProduct docs12 files
EVTEvent dictionaryparsed
CRMCRM notes238 rows
SUPSupport / churnsynced
BILBillingconnected
USGUsage events87%…
Customer Value Map · Value mechanics
User value moments inferred from your product model
Connected first data source
Activation
Ran core workflow 3+ / week
Habit
Invited a second teammate
Expansion
Exported a result downstream
Stickiness
Reached reporting milestone
Proof
Evidence blueprint · Custom signal catalog
SignalTypeReliability
core_workflow_runs_7dbehavioral
0.91
champion_last_activerelational
0.84
seats_active_ratioadoption
0.72
support_sentiment_30dsignal
0.61
invoice_eventsbilling
0.55
+ 24 more signals compiled, weighted, and tied back to the product model
Brain Engine model · Maya Chen
Relationship state
ChurnValue
90-day churn hazard
31%
▲ rising · was 19%
Recovery potential
68%
likely movable with action
Expected saved revenue
$29k
of $42k value at risk
Daily Risk Inbox · Today
01
M
Maya Chen
Workflow owner · 14 seats
Recoverable
$42kValue
Core workflow drop + owner inactive
Book call
02
N
Noah Patel
Ops lead · renewal owner
Critical
$18kValue
Renewal in 14 days + value gap
Check-in
03
H
Hannah Lee
Research lead · dormant
Low leverage
$80kValue
Cancel intent · no usage 31d
Park for now
User evidence · Maya Chen
Maya Chen
$42k value · confidence 0.88 · priority 01
Recoverable risk
Dominant cause
Core workflow runs down 61% over 3 weeks; Maya last active 19 days ago.
Supporting signals
9 signals firing · seats_active_ratio ↓ · support_sentiment flat
Recovery potential68%
Suggested founder action
Book a workflow-recovery call; re-onboard Maya around exports.
Founder feedback · Close the loop
After your call with Maya Chen, what happened?
Saved — workflow recovered
Still at risk — needs follow-up
Churned anyway
Wrong call — not actually at risk
OrthancIQ calibrates from outcomes. Every logged result updates signal reliability and recovery-potential estimates, making the next inbox less speculative and more operational.
Decision lab

Change the user and watch the reasoning change.

A dashboard shows the same chart to everyone. The Brain Engine changes the diagnosis, evidence, action, and commercial priority depending on the user state.

Selected user

Maya Chen

Workflow owner · 14 seats · export workflow adopted

Recoverable
90-day churn pressure +18 pts over baseline
risk gap

The vertical gap is the signal: how far this user's risk has moved beyond normal behavior for the same product stage.

Risk pressure 31%
Saveability 68%
Expected saved revenue $29k risk × saveability × value
Dominant signal Core workflow drop Owner inactive 19d
Evidence dossier
  • Workflow runs down 61% over 3 weeks.
  • Maya was last seen 19 days ago.
  • Support sentiment is neutral, not hostile.
  • Export milestone was previously completed.
Intervention test

Book a workflow-recovery call and re-onboard Maya around the export workflow she originally adopted.

Projected saveability after action 74%

Connect your data before the Brain Engine runs.

A Risk Audit only becomes useful after OrthancIQ receives product events, account context, billing, CRM, support, and product documentation.