Digital health consulting

We solve digital health's hardest problems.

Coterie Health is a digital health consultancy that also builds the software. We take on the work others find too hard, from public health strategy to clinical AI in production.

Connected care
People at the centre. Systems working together.
  1. Strategy

    Sets direction through digital health strategy and technology governance.

  2. Digital Health

    Connects clinical information, coding and human review across digital health workflows.

  3. Labs

    Builds software and connects health systems through FHIR and HL7 integration.

Strategy and governance

Digital health strategy and public health technology governance.

Agentic clinical coding

Clinical coding agents with evidence and human review.
Built inside public health systems
Interoperability first
Clinical safety and governance
Agentic clinical coding
Strategy through to production code

What we do

Where we go deep.

We work across the digital health stack. The thread through all of it is hard problems that need both judgement and engineering.

Digital health strategy and governance

We set digital health strategy with health systems and agencies, then stand up the governance that keeps it safe. This is the assurance work public organisations cannot afford to get wrong.

Advisory

Agentic clinical coding

Clinical coding is our specialty. If someone says AI has solved clinical coding, they are selling a lie. We invented agentic clinical coding to surface evidence and keep coders in control.

Flagship Read more

Agentic clinical coding

Agentic clinical coding for real work.

Clinical coding is one of the hardest problems in digital health. We do not accept the claim that AI has solved it. CoterieOS is our proof point for agentic clinical coding that drafts codes with evidence and sends uncertainty back to humans.

Specialty-trained agents

We shape coding agents around a discipline, so they read clinical context like experienced coders.

Evidence before confidence

A code suggestion is useful only when the coder can see why it appeared.

Human review stays central

Corrections improve the workflow without pretending the system is fully autonomous.

example coding review 3 matched
M79.3 Panniculitis, unspecified 94%
99213 Office visit, established patient 88%
Z79.899 Long-term use of medication 76%
R52 Pain, unspecified 41%
M54.5 Low back pain 38%

Illustrative example. Codes are not from a real patient.

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The bigger picture

Good care depends on seeing the whole patient.

A patient's story usually sits in pieces that never meet. We bring those pieces together where care happens, so the people looking after someone can see what they need, when they need it.