AI native applications to reduce medical cost

Sanoki Orchestrator

Simplify workflows and
control medical cost

Agents read every source on a case and take the repetitive steps. Your team decides and signs. Payers and providers apply one rule to every case.

sanoki orchestrator context model → → applications sanoki orchestrator context model → → applications
FIG. 01 · One case, from the Context Model through the Orchestrator
The opportunity
Every case reviewed
with no value floor
55%
of the savings come from simplifying the processes you run
10x
faster than manual review

The problem

Cases passed desk to desk Rules applied from memory Status found by asking One case, different answers

Care is authorized, priced and paid desk to desk, by hand.
Each desk applies its own reading, and waste, abuse and fraud get paid.

From your process to one workflow

Start from the process your team runs today

With the Sanoki Context Model in place, we design the workflow with your team.

01

Context

The Sanoki Context Model

Your data and rules, defined.

02

Design

The workflow from your process

Each step and handoff, with you.

03

Assign

A step to an agent or a person

Agents read, people decide.

04

Run and decide

Your reviewers on the workflow

A named reviewer signs each case.

You share the processWe design it with your teamYour first workflow runs within weeks

How the Sanoki Orchestrator works

Each case runs the same workflow, step by step

Hand off

The case carries what each step found

The next step starts from what the last step found.

Branch

Each case type takes its own path

Authorizations above a set amount add a second review.

Track

Every case shows where it stands

You see each case's step and owner. A stalled step goes to a person.

Control

Autonomy set step by step

You set each agent's autonomy and can pause any workflow.

Sanoki Orchestrator · Agents

Agents read across sources and take the repetitive steps

An agent does one task on one step, and hands the next step the finding, the lines it checked and the rule.

  • Agentsread · relate sources · compare · draft · check · flag
  • Peopledecide · sign · call · negotiate · escalate

Where agents sit in a workflow

  1. Chain

    One after another

    Read the record, compare each line to the tariff, draft the finding.

  2. Sort

    One sorts, the rest follow

    The first agent tells a hospitalization bill from an outpatient one and sends each down its own branch.

  3. Parallel

    Several at once

    Five checks on the same bill in one pass: authorization, dates, tariff, annex, member.

  4. Draft and check

    One writes, another verifies

    A second agent checks every cited line against the rule before your reviewer sees it.

Each agent runs on a model from Anthropic, OpenAI or Google, under the data terms you sign, with the permissions of the person operating it.

What changes

The same decision on every case, whoever reviews it

  1. 01

    Every case reviewed

    Small and complex, before the money moves.

  2. 02

    Your team on the decisions

    Agents relate the sources. People decide and sign.

  3. 03

    Traceable

    Each step logs who acted, on which evidence, and when.

  4. 04

    Better with every verdict

    Each rejection tunes a threshold or a definition.

Today three readings With the Orchestrator one decision Today three readings With the Orchestrator one decision
FIG. 02 · One case, three readings today and one decision on a workflow

Agents read the whole case, so your team decides on every one.

In a workflow, an agent can

Example

Bill B-2041, 7,000 pages

Hours instead of days. The agent reads every line against the clinical record and the contract.

Read from

  • Bill B-2041, all lines
  • Clinical record, 1,000 pages
  • Contract C-2210, in force
  • Line 212, unsupported service

Pillars it relies on

0102

Every case reviewed, Your team on the decisions

At stake US$3,900Next: A reviewer signsHeld

Next steps

Let us help you simplify your workflows
and control medical cost

Get a demo

See how Sanoki helps healthcare organizations reduce medical cost.

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