/ The leading intelligent intake platform /

Eliminate intake errors before they become revenue loss.

Stop errors and preventable denials at the source. Onymos DocKnow uses lab-native intelligence to automatically capture, validate, and enrich document data the moment it reaches your lab.

  • HIPAA compliant
  • SOC 2 Type II
A clinician's hand on a test requisition form, with DocKnow highlighting the patient name, test code, specimen ID and collection date fields it extracts

Validated

Patient name
Henderson, Mary L.
Test code
CBC-WD-87654
Specimen ID
LAB2024-0892
Collection date
01.05.2026
Less rework for ops teams
60%
Reduction in data entry errors
84%
Data validation accuracy
99.7%

* Average across all Onymos customers

/ Trusted by /

  • Guardant
  • CVS Pharmacy
  • University of Cincinnati
  • Truvian
  • Vapotherm
  • Walmart
  • Mayo Clinic
  • Albertsons
  • Personalis
  • Vanta Diagnostics

/ Onymos DocKnow /

Clean data. No rework. Faster reimbursement.

Across LabOps, data gaps, manual processes, and system silos create compliance risks and downstream errors that your teams have to fix. DocKnow replaces all of these failure points with intelligent document and data processing from the first touch.

Dot-matrix illustration of documents streaming in from many sources and converging on a single purple data core

Capability Document capture

Ingest complex documents from any source.

Directly upload TRFs, medical records, and other documents, or integrate with your entire ecosystem to power a custom data capture pipeline.

DocKnow adapts to your existing systems and workflows, not the other way around. And because it’s deployed inside your infrastructure, you’re always in control.

Dot-matrix illustration of scattered unstructured data with key fields highlighted in purple and pulled out as structured lines

Capability Extraction and understanding

Extract their structured and unstructured data.

Accelerate throughput and turnaround time (TAT) by going beyond simple OCR.

DocKnow understands context, relationships, and terminology specific to precision medicine. It can identify and flag conflicting information automatically and perform eligibility checks to confirm test coverage instantly.

Dot-matrix illustration of a complete record grid with a purple column tracking every change, end to end

Capability Governance

Track every action, end-to-end.

Configure custom business rules to control how data is formatted, validated, and accessed.

Then generate granular summaries and immutable changelogs to stay audit ready and in compliance.

Dot-matrix illustration of a decision tree branching into paths, with the chosen path highlighted in purple

Capability Decision support

Drive better, smarter decision-making.

Use DocKnow’s AI, Synapse, to go even deeper into your data.

Surface clinical insights, create complex reports, or turn your lab’s SOPs into real-time operational guidance for your ops teams.

Scientist in a mask holding a blood sample tube at a lab bench

Results

Increase in efficiency
72%
Fewer overall data errors
40%
TRF processing time
1 min

/ Customer story: Vanta Diagnostics /

Building a next-gen intake system.

Vanta Diagnostics entered 2026 with a new name and an expanded vision for its role as a national diagnostics platform. By July, it had dramatically expanded its capabilities by acquiring Genomind’s genetic testing operations and growing its footprint to four CAP- and CLIA-certified laboratories serving 45 states.

That growth also created an operational challenge. Multiple test lines meant multiple complex requisitions, each with distinct requirements and dozens of handwritten fields to interpret across multiple pages.

And the faster Vanta expanded its testing capabilities and sample volume, the more important it became for its intake infrastructure to keep pace.

Since introducing the new software to the accessioning team, we’ve seen remarkable improvements across the board. These monumental wins could not be possible without Onymos.”

Mary Katherine DiFilippo Director of Specimen Analytics
Read the full story

/ Capture · Understand · Deliver /

The architecture of your intelligent intake layer.

EXTRACTED DATA DOCKNOW WORKFLOW CONDITIONAL PATH DOCKNOW / START / / END / HENDERSON_REQ_0829.PDF 11 pages · email attachment INGEST classify · split · route PATIENT Henderson, Mary L. INSURANCE Cigna DOB 02.17.85 ICD-10 Z80.3 VALIDATE DATA document intelligence ENRICH DATA propensity · eligibility EXCEPTION human-in-the-loop BI / ANALYTICS LIS / LIMS structured JSON / HL7 BILLING / RCM

01 / Capture

In this example, DocKnow’s email listeners automatically capture an incoming packet containing a test requisition and supporting documentation. The packet is classified, separated into individual documents, and routed for review.

Ingest from:

  • Fax
  • Email
  • Uploads
  • SFTP
  • Cloud storage
  • APIs
  • Databases

02 / Understand

Patient, test, and billing data is extracted, standardized, and enriched with information like insurance eligibility status. DocKnow’s AI identifies and reconciles discrepancies, flagging unresolved exceptions for human review.

Use:

  • Context understanding
  • Confidence scores
  • Business rules
  • Data reconciliation
  • Eligibility checks
  • PTP

03 / Deliver

Structured data is written directly to your LIS or other connected systems. DocKnow is optimized for on-premises and customer cloud deployments that keep data processing within your infrastructure, reducing exposure to third parties and enhancing security.

Connect to:

  • GCP
  • Azure
  • AWS
  • Salesforce
  • LabVantage
  • Ellkay
  • Epic
  • Xifin
  • Clinisys
  • Custom
Purple dot-matrix portrait of Prabhakar Ramakrishnan, President of CloudWave

From a security perspective, there was really no concern because there is no data leaving the customer’s boundary.

Prabhakar Ramakrishnan President, CloudWave

/ FAQ /

Questions, answered.

Still have questions?

Talk to our team
01

What types of documents can DocKnow process?

Documents

DocKnow processes test requisition forms (TRFs), medical records, lab reports, insurance cards, and other clinical documents. They can be typed or handwritten, single pages or multi-page packets, and arrive by upload, fax, email, SFTP, or API.

02

What makes DocKnow “lab-native”?

Lab-native

Unlike general-purpose document processing platforms, DocKnow is purpose-built for the complexity of laboratory operations.

At its core is Synapse, our domain-specific intelligence layer, developed through experience processing more than one million completed forms across 500+ variations. Synapse augments AI-generated results with laboratory-specific knowledge and programmatic logic to help ensure extracted information is ready for downstream workflows.

That specialization extends to built-in capabilities, including integrations with ICD and CPT code sets for interpreting and validating laboratory-related information.

03

Where is DocKnow deployed?

Deployment

Inside your infrastructure, either in your cloud VPC or on-premises. Documents and patient data never leave your environment, so you stay in control of security and access.

For labs that want or need it, Onymos also offers secure hosting.

04

How does DocKnow connect to our other systems?

Integrations

Through APIs, HL7 / FHIR interfaces, and SFTP. Validated, structured data is written back to your LIS, EHR, and billing systems automatically.

05

How does pricing for DocKnow work?

Pricing

DocKnow pricing is tailored to your processing volume, workflow complexity, and deployment requirements. We work with your team to understand your needs and develop a pricing structure that accounts for both the software and the infrastructure costs associated with running DocKnow in your environment.

As your document volumes grow, we can also structure pricing to make scaling more economical.

06

How long does implementation take?

Onboarding

Most teams start with a single test line and expand from there. Timelines depend on the number of document types and integrations, and our team scopes them with you up front. A typical timeline is 3-4 weeks.

Two lab scientists in protective gloves reviewing results on tablets

/ Connect with us /

Solving for data extraction in the lab?