CliniqOps

AI-native clinical operations

Fragments in.
One signed record
out.

A referral, a spoken sentence and an imaging paragraph arrive in different places. CliniqOps structures the evidence, keeps its source attached and prepares one record for a clinician to approve.

See the flow
6 fragments
one synthetic encounter
0 re-keying
intake → chart
Every field
traced to a source
Resolved patient recordAmara Okonjo
MRN 88-4419
Synthetic patient
FAX · P.1St Marien Orthopaedics · referral0.98
FAX · P.79 weeks physiotherapy, no relief0.95
SPOKEN · 14:22…into the big toe. Worse standing.0.94
MRI · P.2Right L5–S1 foraminal narrowing0.92
CODEM54.16 · radiculopathy, lumbar0.94
PAYERAuthorization evidence not found0.43
Record confidence0.93
Assembling · awaiting review Signed · E. Halloran 14:41clin-note v2.4

Six fragments, four sources, one clinician-approved record

Fax · 14 pp/Payer portal PDF/Voicemail transcript/Scanned intake form/Appointment CSV/Radiology report/Referring note/Prior auth letter/Clinician addendum/Fax · 14 pp/Payer portal PDF/Voicemail transcript/Scanned intake form/Appointment CSV/Radiology report/Referring note/Prior auth letter/Clinician addendum/

Nine systems.
One patient.
Nobody holds the thread.

the gaps are where the money and the safety go Clinical operations does not fail at the diagnosis. It fails in the gaps—between the incoming record and the chart, the conversation and the note, the note and the code, the approval and the report that finally reaches the patient. CliniqOps is built for those gaps.

The operating flow01 / 05 · Ingest
cliniqops / document-ingestion
FAX_4471.PDF · P.3

Typed fields · 11 of 12

patient.name
Okonjo, A.
referral.reason
M54.16
imaging.date
2026-05-19
auth.number
not found

1 exception routed to operations

The note drafts itself.
The clinician still decides.

Ambient capture separates the encounter into editable fields. No draft becomes a released record without a named decision, and every generated field keeps the evidence used to produce it.

Field · assessment

Right L5 radiculopathy, subacute; conservative therapy unsuccessful.

confidence 0.94prompt soap-v23 sources
  1. 01“…outside of the calf, into the big toe.”Transcript · 14:22:07 · patient
  2. 02Right L5–S1 foraminal narrowing, moderate.MRI lumbar · synthetic source · p.2 ¶4
  3. 039 weeks physiotherapy, no sustained relief.Referral fax · synthetic source · p.7

Audit trail

  1. Structured draft generatedsystem
  2. Assessment edited · “subacute” addedclinician
  3. Alternative code rejected · rationale retainedclinician
  4. Record approved for patient releaseclinician

Why it matters ← inspect the claim

Clinical AI is credible only when its output can be challenged. Source, schema version, model attempt and human action must remain attached to the run—not hidden behind a polished paragraph.

The whole clinic, one accountable surface.

the tenth item is deliberately honest → Ten capabilities

01

Scoped operational dashboard

Real clinic data

Functional
02

Patient recall and follow-up

Filtered patient records

Functional
03

Live consultation capture

Streaming transcript

Functional
04

Structured SOAP generation

Schema-gated draft

Functional
05

Clinician review and release

Explicit approval boundary

Functional
06

Revocable patient access

Hashed expiring token

Functional
07

Appointment ingestion

Validated CSV import

Functional
08

Governed data questions

Allow-listed read plans

Functional
09

Revenue review

Record-level opportunity

Functional
10

AI provenance explorer

Portfolio demonstration

Synthetic

See it running

no sales call, no sandbox request

Walk the clinic before
you believe the pitch.

The authenticated workspace is explorable with synthetic clinic data. Real routes, permissions, review boundaries and data-backed operational views remain connected underneath the design.
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