EnterpriseTechnology licensingTelehealth nutrition

Give every dietitian the reasoning of your best one.

Your dietitians already build plans. Clinical Reasoning interprets the labs and patient data behind those plans, and the protocol builders generate the personalized starting point — so the RDN (Registered Dietitian Nutritionist) spends the visit on judgment and the relationship rather than on assembly.

Practitioner-supervised. Rule-anchored. Evidence-cited. HIPAA (Health Insurance Portability and Accountability Act)-compliant, BAA (business associate agreement)-ready.
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15+ hours

saved per practitioner per week on interpretation and plan assembly

3

knowledge bases behind every recommendation — biomarker to condition, condition to protocol, food to condition

7

protocol domains, so the plan extends past nutrition when the patient needs it to

The bottleneck isn't the dietitian. It's the hour before the visit.

Interpreting a panel, cross-referencing it against conditions, and assembling a personalized plan is the slowest part of the job — and the part where quality varies most between practitioners.

TODAY

Manual interpretation and assembly

Each RDN reads the labs, recalls the relevant evidence, and builds the plan by hand. Output quality tracks the individual practitioner’s experience, and throughput caps at how many plans one person can assemble in a day.

Scaling the practice means hiring more senior practitioners, because the reasoning lives in their heads rather than in the platform.

WITH TERA MODULES

Reasoning and protocols, generated

Clinical Reasoning maps the patient’s biomarkers and context to possible conditions deterministically, with a citation at every step — the RDN reviews findings rather than deriving them.

The Nutrition and Supplement builders generate a personalized, evidence-cited protocol the RDN edits and signs. Embed the Patient Copilot in your app and the plan runs daily between visits.

The modules this uses.

Interpretation, protocol generation, and a patient-facing surface to deliver the plan.

02

Clinical Reasoning

Maps biomarkers and patient context to possible conditions deterministically. The LLM (large language model) summarizes findings; the rules engine produces them.

03

Nutrition Protocol Builder

Biomarker-driven meal plans, foods used as medicine, eliminations, and macronutrient targets personalized to the patient’s diagnostic and goal context.

04

Supplement Stack Protocol Builder

Evidence-cited supplement stacks across cardiovascular, metabolic, hormonal, inflammatory, and longevity domains. Brand-aware.

10

Tera Patient Copilot

AI patient portal that coaches patients daily between visits. White-labeled (hosted by Tera) or embedded as an SDK (software development kit) in your patient app.

All ten modules are available — these are the ones this use case starts with.

How it works.

The practitioner stays in control at every step — the modules do the assembly, not the deciding.

01

Patient data in

Labs, intake, and wearable data pass into Clinical Reasoning through the API or your existing integration.

02

Findings, not guesses

The rules engine maps results to functional ranges and possible conditions. The model summarizes; it never interprets.

03

Protocol generated

Nutrition and supplement protocols are generated against the findings, cited and personalized to the patient’s goals.

04

RDN reviews and signs

Your dietitian edits and approves. The Patient Copilot then delivers the plan daily inside your app.

Safe AI you can embed.

Clinical defensibility is the precondition for embedding AI into any healthcare platform — three architectural pillars built to pass your compliance, legal, and clinical leadership reviews.

01

Practitioner-supervised by design

Tera AI generates; the licensed clinician approves. Every condition hypothesis, every protocol, every adjustment is reviewed and signed off before it reaches the patient.

02

Reasoning is rule-anchored, not improvised

Tera does not ask a language model to interpret biomarkers. A proprietary clinical knowledge base maps results and wearable metrics to functional ranges deterministically, then to conditions and protocols. The model only summarizes what the rules produced.

03

Every recommendation is evidence-cited

Three knowledge bases — biomarker to condition, condition to protocol, food to condition and health goal — with every mapping backed by peer-reviewed citations. Audit-ready and inspectable.

Three ways to deploy.

Pick the integration depth that matches your engineering capacity and brand requirements. All three deliver the same clinical AI underneath.

— I — API ONLY

Server-to-server REST API

You build the UI (user interface) inside your own application. Authentication via OAuth or API key. Modules return structured JSON your app renders natively.

— II — EMBEDDED SDK

Drop-in React components

Your brand, your styling, our clinical logic. Embed the modules as React components in your existing application without building the interface from scratch.

— III — WHITE-LABEL HOSTED

We host the interface; you brand it

Tera hosts the full practitioner portal and Patient Copilot. Custom domain, custom theme, our infrastructure — no engineering work on your side.

Scale your dietitians without scaling headcount.

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