Independent clinical quality control

Use AI for the repetitive work. Use clinical judgment for the decisions that matter.

Lower review cost. Faster clinical analysis. RN-validated work product for attorney use—whether your firm already has an AI-generated report or wants Sierra Pacific to begin with the raw record.

Validate an existing AI output or begin with raw records

Scoped around a defined clinical question

Available to plaintiff and defense firms

What AI validation adds

Speed is useful. Source support is decisive.

Independent SPNC review of AI-generated medical record analyses has shown a consistent pattern: most findings are supported, but a clinically meaningful share still needs qualification, correction, or a closer look beyond the original output.

92%

Supported

of AI-generated findings were supported by the underlying medical record.

6.7%

Needed context

required clinical qualification, clarification, or additional context.

4.3%

Not supported

included statements that the source documentation did not adequately support.

1 in 4

Reviews surfaced an omission

identified at least one clinically significant issue not adequately surfaced in the original AI output.

AI accelerates the analysis. Validation determines what the record actually supports.

An SPNC AI Validation Report provides an independent RN review of AI-generated findings, identifies unsupported or potentially misleading statements, and adds necessary clinical context. When omission review is included, the review also looks beyond the AI output for clinically significant information that may have been missed.

The result is not another AI summary. It is a source-checked clinical review showing counsel which findings are supported, which require qualification, and where additional attention may be warranted.

Metrics reflect observations from independent SPNC testing and review of AI-generated medical record analyses. They are presented as practice-based observations and are not the results of a controlled clinical or scientific study.

Choose the depth of review

One clinical layer does not fit every matter.

The correct level depends on whether you need confirmation of reported findings, an independent omission search, or a complete AI-assisted workflow beginning with raw records. Select a tier to see a representative case and deliverable.

Tier 1

AI Verification Review

Confirm whether findings in an AI-generated summary, chronology, or analysis are supported by the source record.

Starting at

$450

Up to 2,500 pages

Standard turnaround: 7 business days

Representative case

An attorney uses an AI platform to review an 8,000-page medical record. The AI identifies:

A postoperative infection
Delayed recognition of sepsis
Multiple hypotensive episodes
A medication change before deterioration

SPNC reviews the AI-generated findings against the source record. Most findings are supported, but one episode labeled as “hypotension” reflects a single isolated blood pressure reading, and the medication change occurred after—not before—the documented clinical deterioration.

What the attorney receives

Verified

Postoperative infection and sepsis findings are supported by the record.

Qualified

The hypotension finding requires additional clinical context.

Corrected

The medication timeline is inaccurate.

Source-linked

Each validation finding is tied to the relevant medical documentation.

The value

The attorney does not need to assume the AI output is correct. The report identifies what can be relied on, what needs clarification, and what should not be repeated without correction.

Review full scope

Tier 2Flagship

AI Validation + Omission Review

Validate reported findings and independently identify clinically significant omissions tied to your case question.

Starting at

$750

Up to 2,500 pages

Standard turnaround: 7 business days

Representative case

An AI-generated review of a 10,000-page hospitalization identifies:

Progressive respiratory failure
Increasing oxygen requirements
Transfer to the ICU
Intubation
Subsequent complications

SPNC first validates those findings against the record. The RN then independently examines the record for additional clinically significant events and identifies information the AI summary did not adequately surface:

Information the AI did not adequately surface

Repeated abnormal respiratory assessments before ICU transfer
Increasing frequency of nursing escalation
A delay between documented deterioration and physician reassessment
Relevant prior respiratory history that changes the clinical context

What the attorney receives

Validated AI findings

The major events identified by the AI are checked against the source record.

Corrections and qualifications

Findings requiring additional context are clearly identified.

Omissions

Clinically significant information not adequately surfaced by the AI is added.

Clinical context

The relationship between findings is explained from an RN perspective.

The value

This answers two different questions: Did the AI get it right? What did the AI miss? That is the core advantage of the flagship validation service.

Review full scope

Tier 3

Comprehensive Clinical Validation

Start with the raw medical record. Sierra Pacific performs the AI-assisted analysis workflow and clinically validates the work product before delivery.

Starting at

$1,500

Up to 2,500 pages

Standard turnaround: 14 business days

Representative case

An attorney submits a complex 15,000-page raw medical record involving:

Multiple hospitalizations and chronic comorbidities
Surgical complications and conflicting specialist documentation
Changing functional status
An alleged delayed diagnosis
Questions regarding clinical progression and causation

SPNC processes the raw record through its AI-assisted analysis workflow. An RN then validates the resulting findings against the source documentation, corrects unsupported statements, restores clinical context, and identifies significant information related to the defined case question.

The clinically validated analysis identifies

Which generated findings are directly supported by the record
Statements that overstate or mischaracterize the documentation
Clinically significant events requiring greater emphasis
Conflicting documentation between providers
Changes in condition that may warrant closer legal review
Baseline conditions that affect interpretation of later injury or deterioration
Documentation gaps and areas where additional records may be helpful

What the attorney receives

AI-assisted analysis

Sierra Pacific develops the initial work product from the raw medical record.

RN clinical validation

The resulting analysis is checked against the source before delivery.

Defined primary deliverable

The format and clinical question are established during scoping.

Corrections and context

Unsupported statements, ambiguity, and material clinical relationships are addressed.

Source-linked findings

Relevant findings are tied to the supporting medical documentation.

The value

The firm can begin with raw records while retaining a human clinical quality-control layer. AI reduces repetitive review work; RN judgment determines what the record supports and what matters to the defined question.

Review full scope

Human in the loop

Where clinical review changes the output.

Source support

Confirm that dates, diagnoses, treatments, and quoted findings can be traced to the actual record.

Clinical context

Evaluate sequence, response, nursing observations, escalation, and relationships that extraction alone may flatten.

Defined omissions

When selected, independently search for clinically significant information tied to the case question.

Common questions

Clear scope. Clear expectations.

What is AI medical record validation?

It is an independent clinical review of AI-generated summaries, chronologies, or findings against the underlying medical record. The goal is to confirm support, restore clinical context, and define important limitations before the output influences litigation decisions.

Does validation replace the legal AI platform?

No. Sierra Pacific works after the platform produces its output. The AI remains part of the firm's workflow, while an RN adds a separate clinical quality-control layer.

What is the difference between verification and omission review?

Verification tests whether the findings already reported by AI are supported by the record. Omission review also performs an independent search for clinically significant information related to the defined case question that the AI output did not include.

Can Sierra Pacific validate an AI-generated chronology?

Yes. The review can examine whether dated events, clinical relationships, medication changes, escalation, and other relevant details are accurately represented and supported by the source record.

What if the firm has raw records but no AI-generated report?

Comprehensive Clinical Validation begins with the raw medical record. Sierra Pacific performs the AI-assisted analysis workflow, then an RN validates the resulting work product against the source documentation before delivery.

Attorney resources

Use the validation layer with intention.

Practical guidance for deciding what to validate, how to scope the review, and what an RN should check in an AI-generated medical chronology.

Begin with a scoped inquiry

Ready to add an RN validation layer?

Start with the AI output, approximate page count, deadline, and the clinical question your team needs answered.

Start a validation review

Use AI for the repetitive work. Use clinical judgment for the decisions that matter.

Speed is useful. Source support is decisive.

AI accelerates the analysis. Validation determines what the record actually supports.

One clinical layer does not fit every matter.

AI Verification Review

AI Validation + Omission Review

Comprehensive Clinical Validation

Where clinical review changes the output.

Source support

Clinical context

Defined omissions

Clear scope. Clear expectations.

What is AI medical record validation?

Does validation replace the legal AI platform?

What is the difference between verification and omission review?

Can Sierra Pacific validate an AI-generated chronology?

What if the firm has raw records but no AI-generated report?

Use the validation layer with intention.

Attorney guide to AI validation

AI chronology validation

Frequently asked questions

Ready to add an RN validation layer?