AI Advisory for Healthcare · A Service Offering

AI for healthcare, from ideation to the point of care.

A contractual advisory offering for providers and payers navigating the AI journey — an honest readiness picture across clinical and administrative operations, an executable roadmap, and AI that is responsible, auditable, explainable, and secure at the forefront.

01 · Readiness 02 · Roadmap 03 · Pilot-to-Production 04 · Embedded Advisory
The Healthcare Dilemma

The mandate is clear. The path isn't.

Four patterns we see across health systems and health plans under pressure to "do AI" — each an argument for starting with advisory rather than procurement.

01

Pilot purgatory

The ambient-scribe demo wowed the medical staff. Two years on it lives in one clinic — EHR integration, clinical governance, and unit economics were never scoped.

02

Shadow AI in the clinic

Clinicians paste notes into public chatbots; staff draft appeals with them. PHI is leaving the building ungoverned — and every paste is a reportable question.

03

The accountability gap

Boards, compliance officers, and regulators are asking where AI touches clinical and coverage decisions — questions with no owner and no evidence trail.

04

The readiness illusion

Decades of systems grew apart: EHR here, claims platform there, faxes in between. Use cases get funded before anyone checks the data can carry them.

The cost of getting this wrong isn't a failed pilot — it's eroded clinician trust and a compliance finding you didn't need.
The Healthcare Value Map

Where AI pays off in care and cost.

Four domains where AI moves real healthcare numbers — clinician time, cycle time, cost of compliance, and patient experience.

Clinician time · Burnout

Clinical operations

Ambient documentation, AI triage and guided intake, evidence-cited decision support, and care-team copilots grounded in the chart.

Cycle time · Denials

Revenue cycle & claims

Straight-through adjudication, prior-auth automation, coding and billing support, and denial and appeals intelligence.

Audit · Quality measures

Quality, safety & compliance

Deviation and complaint categorization, audit-ready document retrieval, policy lookup with citations, and quality-measure reporting.

Access · Satisfaction

Patient & member experience

Navigation and benefits assistants, correspondence drafting, post-discharge follow-up, and call-center copilots.

Your shortlist will differ — surfacing it, and ranking it honestly, is exactly what the readiness sprint and roadmap are for.
Step 01 · Healthcare AI Readiness

Know where you stand before you spend.

A two-to-three-week, fixed-fee diagnostic that replaces optimism with evidence — and gives the board a defensible starting point. Structured interviews with clinical, compliance, revenue-cycle, and IT leadership; technical deep-dives into the EHR and claims estate; scoring against our healthcare benchmark.

How the sprint runs

Week 1

Interviews with clinical, compliance, rev-cycle & IT leadership

Week 2

Deep-dives: data estate, EHR/claims landscape, privacy posture

Week 3

Scoring, gap analysis, board-ready readout

Readiness scorecard — six dimensions · illustrative

What gets scored

Data estate (clinical + claims)54
Systems: EHR · claims · HIE62
Talent & skills45
Governance & risk31
Security & privacy posture69
Use-case portfolio48
Illustrative scores only. Shown to demonstrate the instrument, not to represent any organization. Each dimension is scored 0–100 against our healthcare benchmark, and every gap is mapped to a costed remediation.
Fixed fee. Fixed calendar. If we find you're not ready, the readout says so — and says exactly what to fix first.
Step 02 · Roadmapping, Ideation to Production

A roadmap that survives contact with the clinic.

Five phases, four executive gates. Investment tracks evidence rather than momentum — and nothing advances without the numbers to justify it.

Phase 1

Ideate

Use-case discovery with the people who own outcomes and cycle time — clinicians and operators, not just IT.

Phase 2

Prioritize

Portfolio ranked by value, feasibility, clinical risk, and data readiness.

Phase 3

Prove

Pilot in one clinic, service line, or claims queue — production criteria set on day one.

Phase 4

Productionize

EHR/claims integration (FHIR, X12), privacy hardening, and MLOps / agent-ops.

Phase 5

Operate & scale

Monitoring, evals, and clinician enablement — then service line to service line.

◆ Gates

Executive decision gates

Continue, redirect, or stop. Four gates between ideation and scale; each one is a real exit ramp, priced in from the start.

Typical arc: prioritized portfolio in 6 weeks · first pilot decision in one quarter · first production workload inside two.
The Trust Architecture

AI your clinicians trust — and your auditors can verify.

Three properties we engineer into every recommendation, architecture, and pilot — because in healthcare, patients, clinicians, and regulators all have to believe the answer.

Humans in command

Responsible

Human-in-the-loop on consequential calls — diagnoses, denials, prior auth. Bias and neutrality testing across patient populations. Policy packs mapped to your reality: HIPAA, 42 CFR Part 2, state privacy.

For you: AI accelerates your clinicians and examiners — accountability never leaves them.

Evidence by default

Auditable

Append-only logs of every prompt, retrieval, and decision. Lineage from chart and claim to output, per user and per patient. Evidence packs for CMS audits, OIG inquiries, and accreditation surveys.

For you: When the auditor asks "why", you have the receipts.

Answers with receipts

Explainable

Citations to clinical evidence, policy, and the chart on every answer. Decision traceability from output back to source and policy. No black-box recommendations in clinical or coverage decisions.

For you: No determination you can't defend — to a patient, a plan, or a regulator.

Security at the Forefront

Secure by design, down to the record.

In healthcare, AI's attack surface reaches the chart — new identities, new data flows across EHRs, clearinghouses, and partners, new paths to PHI. We treat security as the first gate every recommendation must clear, not a review at the end.

Shadow-AI discovery & containment

Find ungoverned use in clinics and back office; convert it to protected paths.

PHI protection in every AI path

PHI detection and de-identification, minimum necessary, and encryption throughout.

Identity for humans and agents

Non-human identity, scoped credentials, and full attribution of every action.

Prompt-injection & model threat defense

Input shielding, output filtering, and abuse and anomaly monitoring.

Deployment sovereignty & BAAs

Your VPC or on-prem; BAA-covered services only — your keys, your residency.

Continuous assurance

Evals, red-teaming, and drift monitoring as an operating rhythm rather than an event.

Aligned to your frameworks: HIPAA / HITECH · NIST AI RMF · HITRUST · SOC 2 · 42 CFR Part 2. The result is an AI posture your CISO and your compliance officer co-sign — and an architecture that passes BAA, privacy, and audit review the first time.
Engagement Model

Contract for a step, not a leap of faith.

Four fixed-scope engagements, each separately contracted with named deliverables. You re-decide at every gate — momentum is earned, never assumed.

Step 01

AI Readiness Sprint

2–3 weeks · fixed fee
  • Readiness scorecard: clinical & claims
  • Privacy, security & governance snapshot
  • Board-ready executive readout
Step 02

AI Roadmap

4–6 weeks
  • Prioritized healthcare use-case portfolio
  • 90-day plan & 12-month arc
  • Governance & security baseline
Step 03

Pilot-to-Production

8–12 weeks
  • Pilot in one clinic, service line, or queue
  • Guardrail & integration architecture
  • Go / no-go evidence for the board
Step 04

Embedded Advisory

Ongoing · quarterly
  • Fractional AI leadership & CoE stand-up
  • Quarterly board reporting & reviews
  • Continuous assurance: evals, red-teaming
Every step stands alone — and every step de-risks the next. Most healthcare organizations begin with the sprint.
Outcomes

You leave with decision-grade artifacts.

Not observations — instruments. Each artifact is built to move a specific decision: fund, fix, pilot, or stop.

Readiness scorecard

Where you stand — clinical and claims, scored honestly against benchmark.

Use-case portfolio

Ranked by outcome and margin impact, with named owners and source systems.

Executive roadmap

A sequenced 90-day plan and 12-month arc, decision-ready.

Governance baseline

Policies, human-in-the-loop gates, and audit posture defined before the first build.

Pilot blueprint

Production criteria set from day one, with metrics, guardrails, and integration points.

AI operating model

Centre-of-excellence design, clinical roles, and decision rights.

Questions you'll answer with confidence

Q1

Where does AI relieve clinicians or cut cycle time first — and what is it worth?

Q2

Is our clinical and claims data ready? If not, what exactly is the fix?

Q3

Can we defend AI-assisted clinical and coverage decisions to patients, plans, and regulators?

Q4

What will it cost — and when does it pay back?

Q5

Who owns AI risk — clinical and corporate — and how is it monitored?

Why MTekLabs

Advice from people who ship AI for a living.

Most AI advice comes from people who have never run a model in production — or sat through a utilization-review meeting. Ours comes from doing both.

Practitioners, not analysts

We design, build, and operate production agentic-AI systems. Every recommendation arrives pre-tested against deployment reality.

Healthcare fluency

We frame AI around clinician time, cycle time, denials, quality measures, and total cost of care — not tech for its own sake.

Vendor-neutral

Provider-agnostic across Bedrock, Vertex, Azure OpenAI, and on-prem. We optimize for your outcomes, not a reseller margin.

Built to hand over

Enablement is the deliverable: your people, your operating model, your capability — stronger after every phase, independent at the end.

Credentials, not case studies. Production AI platforms designed, shipped, and operated in regulated industries — including the agentic clinical-care and claims platforms we built for providers and payers: Praman & Anvesh and Clairant, with HIPAA-grade controls in live use.

Start with one clinic, one queue, one measurable win.

One 30-minute executive session is enough to scope your readiness sprint. Two to three weeks later: an honest clinical-and-claims scorecard, a board-ready readout, and a clear decision on what comes next.

Scope a readiness sprint or email info@mteklabs.com

Responsible · Auditable · Explainable · PHI-secure by design

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