vivegahealth

AI Enablement / Vivega Health

Claude, set up and running across the work your organization already does.

We set up AI for healthcare leaders and their teams, teach them to use it on their real work, and build the systems that put it inside clinical, operational, financial and regulatory workflows.

Book a readiness callSee the four stages
Who we build for
Health plans, provider organizations, IPAs and health systems, pharmacy and PBM teams, health-tech and digital health companies — and the executives running them.
What we deploy on
Claude in your environment — Amazon Bedrock, Google Vertex AI, the Claude Developer Platform, or your existing gateway.
What we won't do
Put a model where a licensed human decision belongs. Every workflow we ship keeps a person where the regulation — and the risk — puts one.

01 — The problem

Most healthcare organizations have AI. Very few have it in the work.

Licenses get bought. A few people find it useful. Everyone else opens it once, treats it like a search box, and goes back to what they were doing. Meanwhile the pilots that do get funded stall somewhere between the demo and the compliance review.

The technology is rarely the constraint. The constraint is that nobody has connected it to the organization's own data and policies, nobody has taught the teams to use it on the work in front of them, and nobody can explain how the output would hold up under audit. Those are operating problems before they are engineering problems.

Vivega sits on both sides of that line. We have run these functions inside healthcare organizations, and we build the AI systems that now support them.

Where it stalls

  1. 01

    Nothing is set up. Seats assigned, no configuration, no connectors, no shared knowledge — so every person starts from an empty box.

  2. 02

    No provenance. Output nobody can trace back to a policy, a regulation, a contract or a page of the record.

  3. 03

    No evaluation. A demo that impressed the steering committee and was never tested against a labeled sample of real cases.

  4. 04

    No owner. Built by IT, handed to the business, governed by neither.

  5. 05

    No integration. A chat window beside the workflow instead of inside it — so adoption dies the week the pilot funding does.

  6. 06

    No audit story. Nothing that survives first contact with compliance, delegation oversight or a regulator.

02 — What we offer

Four stages. Start at whichever one you're standing on.

Setup → Fluency → Enablement → Production

Each stage stands alone and each one feeds the next. Organizations that skip straight to production without setup and fluency tend to build the wrong thing very efficiently.

Stage 01 — Setup

Setting up Claude and AI

We get AI properly stood up for your leaders and your teams — configured for a healthcare environment, connected to the systems people already work in, and governed from day one rather than a year later.

Deliverables

  • Workspace configuration — Claude Team or Enterprise setup, single sign-on, roles and permissions, seat planning by function
  • Privacy and data posture for healthcare — what may go in, what never does, and how that is enforced rather than just documented
  • Connectors to where work already lives — mail and calendar, document repositories, CRM, ticketing, BI and reporting
  • Projects and shared knowledge bases by function, loaded with your own policies, contracts, specifications and templates
  • The right tool per person — Claude for executives and analysts, Cowork for document and file work, Claude Code for technical teams
  • Executive setup sessions — working one-to-one with leaders to put AI into how they actually run their week
  • An acceptable-use and governance policy written for a healthcare organization, plus a champion network and internal support path so adoption doesn't depend on us

Stage 02 — Fluency

Training

We teach your teams to do their actual work with Claude — not to prompt in the abstract, but to run the analysis, the review, the response or the filing in front of them.

Deliverables

  • Role-based working sessions for clinical, quality, coding, network, claims, compliance, finance and member-facing teams, using their own cases
  • Claude Code workshops for the analytics and engineering staff who build your reporting and products
  • Cowork facilitation so non-technical staff can automate document and file work without writing code
  • Leadership briefings for the executives and board committees who have to fund and govern this
  • An AI readiness assessment naming which of your workflows are ready, which need data work first, and which should stay manual

Stage 03 — Enablement

Enablement

Fluency without plumbing stalls. We build the connective tissue that puts your data, your policies and your domain logic inside the model's reach.

Deliverables

  • MCP connectors to your stack — claims and encounters, clinical and EHR data, the HEDIS engine, care management, provider directory, pharmacy, finance and document systems
  • Agent Skills for your workflows — document review, coding and documentation integrity, prior authorization, appeals, regulatory filings, provider performance, proposal response
  • Claude Projects and prompt libraries built on your own policies, model of care, provider contracts, benefit designs and current technical specifications
  • Rollout scaffolding — templates, guardrails, access model and repository wiring, so the second team doesn't start from zero
  • Evaluations and safety review for every workflow before it ships, scored against a labeled sample of your real cases

Stage 04 — Production

Applied AI engineering

When the use case is past what an internal team can build alone, we build it — end to end, in your environment, under your compliance posture.

Deliverables

  • Production agents on the Claude Developer Platform, running real volume against real queues
  • Custom MCP servers for systems that have no connector and never will
  • Deployment in your environment — Bedrock, Vertex AI, direct API or your existing gateway, configured for PHI
  • Product work for health-tech teams — AI features built into what you sell, not just what you run
  • Evaluation harnesses and monitoring that keep measuring after go-live, not just before it
  • Governance documentation your compliance, delegation oversight and audit functions can actually use

03 — Who we work with

The same four stages, tuned to what you actually operate.

Health plans

Medicare Advantage, D-SNP and I-SNP, Medicaid, Commercial and ACA. Quality, risk, utilization, appeals, network, pharmacy, compliance and member operations — the whole plan, not one department.

Provider organizations and IPAs

Documentation burden, referral and care coordination, revenue cycle, value-based contract performance, and the reporting that delegated arrangements demand.

Health systems

Clinical operations, access and scheduling, denials and appeals, service-line analytics, and the administrative load that sits between clinicians and patients.

Health-tech and digital health

AI in the product, not just in the back office — plus the evaluation, security posture and documentation your payer and provider buyers will ask for during diligence.

Executives and leadership teams

Individual setup for leaders who want AI in how they run their function: board and committee prep, contract and vendor review, market analysis, and the writing that fills a week.

Pharmacy, PBM and vendor partners

Formulary and coverage work, utilization review, contract and rebate analysis, and the client reporting that comes with delegated services.

04 — Where it lands first

The work that pays for the program.

Wherever there is high document volume, clear ground truth, and a human decision worth protecting at the end, there is usually a case. These are the ones we see most often.

Clinical and care operations

Care teams, UM, population health

Prior authorization review

Cross-reference a request against coverage determinations, clinical guidelines and the member's record, then hand a clinician a prepared summary. The approval decision stays with the clinician.

Portal message and referral triage

Rank a queue of member messages, referrals and handoffs by urgency so a care team sees the one that can't wait first, and nothing falls through the gap between two owners.

Care plan and assessment support

Pull the assessment, claims history and prior notes into a drafted care plan a care manager edits rather than writes, with the source behind every element.

Clinical policy maintenance

Track guideline and coverage changes against your current medical policies and surface which ones are now out of date, with the specific language that moved.

Revenue, quality and regulatory

Stars, risk, coding, compliance, appeals

Measure-level root cause

Pull a quality measure apart by contract, market, provider group and member segment, and get back the interventions that actually move the rate — with numerator logic cited from the current specification.

Documentation and coding integrity

Check submitted diagnoses against documentation support, flag what won't hold, and surface conditions the chart supports but the claim never carried.

Audit readiness

Assemble the documentation packet for a regulatory or validation audit — claim, chart, signature, credential — and name the gaps while there is still time to close them.

Appeals and grievances

Pull the denial rationale, the coverage basis, the clinical record and the regulatory timeline into one drafted response, with a citation attached to every assertion.

Claims and payment integrity

Surface patterns across denials, adjustments and appeals that a rules engine misses, and explain each one in language a payment integrity team can act on.

Regulatory filings and reporting

Draft and quality-check recurring submissions against the current guidance, and flag where this year's instructions differ from last year's.

Enterprise, network and growth

Network, finance, sales, leadership

Delegated and vendor oversight

Read delegate reporting, audit findings and corrective action plans across a network, and surface which partners are drifting before the annual review says so.

Contract and proposal work

Analyze provider and vendor contracts against your standard terms, and turn an RFP into a drafted response built from your own prior submissions and real program data.

Member experience and voice

Read survey verbatims, complaint logs and call notes together, and separate the themes an organization can fix from the ones it can only explain.

Finance and forecasting support

Reconcile operational and financial reporting, explain variance in plain language, and prepare the narrative a board committee needs behind the numbers.

Executive throughput

Board decks, committee prep, market and competitor reads, and the correspondence that eats a leader's week — done in their own voice and their own format.

Internal operations

Policy and procedure upkeep, training material, onboarding and job aids — the documentation debt every healthcare organization carries.

05 — What we connect

Claude already speaks parts of this language. We connect the rest.

Anthropic ships healthcare connectors and agent skills out of the box. The gap is always the same: your data, your policies, your domain logic. That gap is the engagement.

Available from Anthropic

  • CMS Coverage Database

    Local and National Coverage Determinations for coverage and prior authorization checks

  • ICD-10 classification

    Diagnosis and procedure code lookup for coding and claims work

  • NPI Registry

    Provider verification, credentialing and claims validation

  • PubMed

    Biomedical literature for clinical policy and guideline work

  • Prior Authorization Review skill

    A customizable template Anthropic publishes for UM workflows

  • FHIR development skill

    Faster interoperability work against health data systems

What Vivega builds

  • Connectors to your systems

    Claims and encounters, clinical and EHR data, care management, provider directory, pharmacy, finance, CRM and document repositories

  • Your domain logic

    Current quality and pharmacy specifications, the risk model version you are paid on, benefit designs and fee schedules

  • Your policies as context

    Medical policy, model of care, UM criteria, P&Ps, delegation agreements, provider and vendor contracts

  • Custom agent skills

    The workflows above, built to your operating procedures rather than a generic template

  • Evaluation sets

    Labeled samples from your own historical cases, so performance is measured against your ground truth

What governance gets

  • A PHI-appropriate deployment

    Configured in your own cloud environment, under your agreements

  • Human decision points, documented

    Named, placed where regulation requires, and testable

  • Traceable output

    Every assertion carries the source it came from

  • Measured performance

    Pre-launch evaluation and post-launch monitoring, both reportable

  • An audit narrative

    Written for compliance and oversight functions, not for engineers

06 — How engagements run

From an empty workspace to a workflow in production.

A typical first engagement runs about a quarter and ends with teams using AI daily, one workflow live, and the capability to build the second one without us.

Weeks 1–2

Readiness

Workflow inventory, data and document assessment, compliance posture. Output is a ranked list of candidates and an honest note on what isn't ready.

Weeks 2–4

Setup

Workspace, access, privacy configuration, first connectors and shared knowledge bases. Leaders set up individually so the tone comes from the top.

Weeks 3–6

Fluency

Hands-on sessions with the teams who will own the work, using their own cases. The candidate list gets reordered here by the people doing the job.

Weeks 5–10

Build

Connectors, skills and context for the first workflow. Evaluated against a labeled sample before anyone sees it in production.

Weeks 9–14

Production

Live on real volume, monitored, governance documentation written, and the second workflow scoped by your team rather than ours.

07 — Why Vivega

We ran these functions before we automated them.

There is no shortage of firms that can wire up a model, and no shortage of trainers who can run a prompting workshop. There are very few who have sat in the committee, defended the submission, owned the measure, and answered to the regulator — and can then build the system that does it better.

On the Anthropic ecosystem: Vivega Health builds on Anthropic's Claude platform and its published healthcare connectors and agent skills. We are not an Anthropic reseller, and we describe our partner status only where it is formally held.

  • Health plan operating leadership. Former Quality VP across SNP, Medicare Advantage, Medicaid, Commercial and ACA lines of business.

  • Quality results, not theory. Medicare Advantage contracts moved from 3.5 to 4.5 Stars; a D-SNP improved half a Star in each of two consecutive years; a Medicaid plan taken from 8th to 1st among its state's MCOs on a targeted measure set.

  • Risk and revenue depth. Program leadership across submission accuracy, documentation integrity and audit response.

  • Model range. IPA, delegated network and direct arrangements, across West Coast, Midwest, Northeast and Southern markets — because the operating constraints are not the same.

  • Built on the work. Vivega's own consulting, knowledge platform and advisory practice run on the same setup we deliver.

Start with the readiness call.

Bring one workflow you think is a candidate, or a team you want set up. We will tell you what it would take, what it would return, and what we would do instead if it isn't ready.

Email Vivega HealthReview the four stages