Outcome verification and attributionfor humans and agents

Atlas ingests the events behind every outcome, resolves which actions drove it, and returns attribution your billing system, customer, and board can all act on.

Join the waitlist

Private beta. We're taking a small number of design partners.

The gap

"Did it happen" is the easy half.

Outcome-based contracts stall on a harder question: whether your product is the reason the outcome happened.

Binary verification returns a pass or fail on an event you agreed to count. It says nothing about what produced it.

The stack

Attribution belongs between verification and billing.

Executionagents · services · human providers

Verificationyour evaluators · human review · acceptance layers

Atlasevent ingestion · attribution resolution · outcome analytics

Billing and ratingusage meters · rating engines · invoicing

Finance and opsAP · revenue recognition · retries and workflows

Verification tells you it occurred. Billing charges for it. Atlas explains it.

What you get back

One outcome. The events behind it. The share you can defend.

Event ingestion

Product events, agent traces, CRM, support. Instrumented once, reused across every outcome.

Attribution resolution

Which actions contributed, which were necessary, and the rate without them. Holdouts where available, modeled contribution where not.

Outcome analytics

Attribution by segment, workflow, customer, over time. Where the outcome rate is moving and what moved it.

Questions this makes answerable

The questions that currently end in an argument.

Which actions moved this outcome, and by how much.

What would this customer's outcome rate have been without us.

Which workflows produce defensible outcomes, and which do not.

When a customer disputes an invoice, how fast can we produce evidence.

Where is our outcome rate falling, and what caused it.

Today these are answered in a spreadsheet, after the dispute.

How it works

Instrument once. Query every outcome after that.

Connect your sources

Product events, agent traces, CRM, support, billing. Atlas holds the event graph around each outcome.

Define the outcome

What counts, what proves it, what does not. Versioned, so changes show in the data.

Resolve attribution

Which actions contributed, and the counterfactual rate. Holdouts where available, modeled where not.

Return the outcome record

Occurrence, attributed share, contributing events, confidence. One record for billing, customer, and team.

The shape of it

An outcome record, not a boolean.

{
  "outcome": "meeting_booked",
  "occurred": true,
  "attributed_share": 0.72,
  "confidence": "high",
  "counterfactual_rate": 0.19,
  "contributing_events": 14,
  "window": "2026-08-01/2026-08-31"
}

Illustrative. Attributed share goes in front of the customer. Counterfactual rate makes it defensible.

Private beta

We're taking a small number of design partners.

Outcome-priced products, results-paid agent workflows, anything where a customer can ask whether you caused it.