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Curious Context Labs

Healthcare · Custom app

Clinical coding support

AI clinical coding support for coders and billing teams

Coders get a ranked list of candidate codes with the supporting text from the record, looked up in the official code sets, for them to accept or change.

01 today

The problem

Coders read long records to assign diagnosis and procedure codes, and backlogs delay billing. Missed or vague documentation leads to wrong codes and denied claims. General AI chatbots are not reliable at this on their own: they often produce codes that do not exist.

02 the run

What the AI does

  1. Step 1: Reads the finished encounter or admission record once it is signed.
  2. Step 2: Finds the statements that support a diagnosis or procedure, such as the reason for a test or the operation performed.
  3. Step 3: Looks up candidate codes in the official code set, such as ICD-10-CM, ICD-10 and OPCS-4, or CPT, rather than writing codes from memory.
  4. Step 4: Ranks the candidates and shows the exact sentence that supports each one.
  5. Step 5: Flags documentation gaps, such as an unspecified condition, so a query can go to the clinician.

paused: waiting for a person to approve

03 human in the loop

Where a person approves

Certified coders choose every final code. Queries to clinicians are written or approved by a coder, and the tool never changes the clinical record.

04 after

What changes

Coders spend their time on judgement rather than searching, and backlogs shrink. Codes are better supported by the record, which helps when claims are reviewed.

Case studyHelping coders clear the backlog without trusting AI to guess codesThe rollout, what to measure, a worked example and the research behind it.

see also

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    Referral intake and routing

    Incoming referrals are read, checked for missing information and routed to the right service, with urgency confirmed by a clinician.

    Automation

Tell us how your business runs. We'll tell you where AI fits.

A free 30-minute call. You talk, we ask questions, and you leave with a few concrete ideas — or an honest answer that AI isn't the right fix yet.

Working with teams around the world.