Heelius closes an L1 alert for $2.80 against a $32.90 loaded human cost

Pricing

You pay for investigations completed

Not seats, not alerts ingested, not a platform fee. The unit you buy is the unit your cost centre already measures — a closed alert with a narrative attached.

Ramp

$4.50

per investigation

Under 5,000 alerts a month

  • Full L1 investigation and narrative
  • Sanctions, PEP and adverse media adjudication
  • Counterparty network to 2 hops
  • Console, audit trail and exports
  • Standard policy packs
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Most common

Programme

$2.80

per investigation

5,000 to 100,000 alerts a month

  • Everything in Ramp
  • L2 investigation and escalation routing
  • Counterparty network to 3 hops
  • Your policy thresholds and narrative format
  • QA sampling programme and concurrence reporting
  • Champion/challenger with model cards
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Scale

From $1.20

per investigation

Over 100,000 alerts a month

  • Everything in Programme
  • Dedicated tenancy and choice of data residency
  • Custom typologies and corridor models
  • On-chain investigation module
  • Named model-risk contact and validation support
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Escalations are priced the same as clearances. Pricing the agent to escalate less than it should would be the wrong incentive to put into a compliance function.

The economics

Priced per alert, against a line item you already have

No seat licences and no platform minimum. You pay for investigations completed, which means the saving is legible to a CFO on the first invoice.

24K
$2.80

Annualised

$8,100,288

net saving against a fully staffed L1/L2 function

Human-only baseline
$9,475,200
Heelius investigations
$806,400
Residual human review (6%)
$568,512
121

analyst-equivalents of investigation capacity, redeployed to escalations and quality assurance

Assumes 42-minute median handling time and a $47 fully-loaded hourly analyst cost

Before you commit

The benchmark comes first

Send a month of alerts your team has already closed. Heelius re-investigates them without seeing your dispositions, and you compare — case by case — where it agreed, where it differed, and whether its narratives would have survived your own QA.