AI Inventory and Classification
Establishing what AI is in use across the organization, including capability embedded in purchased software, with classification by risk and clinical involvement.
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Hire Healthcare AI Governance Consultants
Healthcare AI governance consultants build the process by which an organization decides which AI to adopt, on what evidence, and under what monitoring. They establish inventories, intake and review workflows, documentation standards, and ongoing oversight, so AI decisions are made deliberately rather than department by department.
Taction Software is a software engineering firm, not a law firm or accreditation body. We help you build governance process and the technical artifacts it depends on. We do not provide legal advice, regulatory determinations, or compliance certification, and no vendor can guarantee your compliance. Our hire dedicated developers hub covers the engineering roles this work informs.
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What Governance Consultants Build
The output is process, documentation, and the technical capability governance depends on. A committee cannot evaluate a model without evaluation results, and cannot monitor deployed AI without instrumentation. The work below reflects that. Inventory appears first because most organizations cannot currently list what AI is running, including tools arriving inside vendor products nobody classified as AI.
Intake and Review Workflow
Designing how proposed AI reaches review, what evidence is required, who decides, and how decisions and conditions are recorded for later reference.
Evidence and Documentation Standards
Defining what a submission must contain: intended use, training and validation description, subgroup performance, monitoring plan, and human review placement.
Committee Structure and Decision Rights
Establishing who reviews what, how clinical and technical input combine, and where escalation occurs, so decisions have owners rather than diffusing across meetings.
Vendor AI Assessment Process
Building the questions and evidence requirements applied to purchased AI, since vendor products carry the same clinical risk with less visibility into their construction.
Ongoing Monitoring and Review Cadence
Defining what deployed AI must report, how often it is reviewed, and what triggers reassessment, since approval at deployment is not oversight.
Healthcare Context This Work Requires
AI governance in healthcare differs from general technology governance because the failures are clinical and the evidence questions are specific: how was this validated, on whom, and does performance differ across populations. Governance that asks generic technology questions will approve things it should not. The context below spans the healthcare work you assign.
01
Most Organizations Cannot List Their AI
Capability arrives inside purchased software without being labeled as AI. Inventory is the necessary starting point and is usually harder than expected.
02
Evidence Requirements Must Be Specific
Asking whether a model was validated invites a yes. Asking for subgroup performance on a defined population produces information a committee can actually evaluate.
03
Vendor AI Carries the Same Risk
Purchased AI affects patients identically to built AI, with less visibility. Governance must apply comparable evidence requirements to both.
04
Approval Is Not Oversight
Reviewing at deployment and never again misses the degradation that follows population and practice change. Ongoing reporting is the substance of governance.
05
Clinical and Technical Review Must Combine
Technical review cannot assess clinical appropriateness; clinical review cannot assess validation methodology. Both are required, and structuring that combination is the design work.
06
Governance Decides, Consultants Advise
We help build process and produce artifacts. Decisions about which AI your organization adopts belong to your clinical and executive leadership.
Skills and Methods This Role Requires
This work combines process design with enough technical depth to define meaningful evidence requirements. A consultant who cannot read a validation report will build a review process that accepts inadequate evidence. The competencies below reflect that. Weight technical literacy and practical process design above framework familiarity, since governance nobody follows produces documentation rather than oversight.
AI Evidence Literacy
Reading validation reports critically, recognizing where subgroup analysis is absent, and distinguishing internal test results from external validation.
Process Design That Teams Follow
Building intake and review workflow proportionate to risk, since heavyweight process applied to low-risk capability gets circumvented rather than followed.
Documentation Template Development
Producing submission templates, model documentation formats, and decision records that capture what future reviewers will need.
Vendor Assessment Question Design
Constructing evidence requests that vendors can answer meaningfully and that reveal where evidence is thin rather than inviting reassurance.
Monitoring Requirement Definition
Specifying what deployed AI must report, working with the technical teams who implement it. Our healthcare integration work covers connectivity where monitoring touches clinical systems.
Stakeholder Facilitation
Working across clinical, technical, legal, and executive functions whose priorities differ, surfacing disagreement rather than producing documents nobody owns.
How We Evaluate Governance Consultants
The distinguishing question is whether the process they built was actually used. Governance documented and circumvented is worse than none, because it creates the appearance of oversight. Our assessment centers on practical process design, evidence literacy, and willingness to recommend against adoption. Our delivery process includes review points where you can reassess fit.
Whether the Process Was Followed
We ask what happened after their governance was established. Processes circumvented by teams produced documentation without oversight.
Evidence Requirement Specificity
We ask what submissions had to contain. Generic requirements invite reassuring answers rather than information a committee can evaluate.
An Adoption They Recommended Against
We ask about AI they advised not deploying. Consultants who only enable have not exercised the judgment governance exists to apply.
Vendor AI Handling
We ask how purchased AI was assessed. Governance covering only built capability misses most of the AI affecting patients in a typical organization.
Ongoing Review Design
We ask what happened after approval. Processes without monitoring requirements approve once and never learn whether the capability still works.
Verified Governance Experience
We describe which programs each consultant worked on and what was implemented. We do not claim legal, regulatory, or accreditation credentials for consultants.
Engagement Options for Governance Work
Governance engagements are typically short and produce artifacts your organization then operates. Structures below reflect that. We also assess whether governance is your constraint, since organizations running one or two AI capabilities usually need evaluation infrastructure rather than a committee process.
Inventory and Risk Classification First
Establishing what AI is in use and its clinical involvement. This regularly surfaces capability nobody knew was deployed and reframes what governance must cover.
Governance Framework Development
Designing intake, review, evidence requirements, and monitoring cadence proportionate to your risk profile, delivered as documentation your organization operates.
Consultant With Technical Team Support
Governance depends on technical artifacts. Pairing process design with engineering ensures evidence requirements are producible rather than aspirational.
Augmenting Your Governance Function
Where you own the committee, staff augmentation adds capacity working within your existing structures rather than proposing a parallel framework.
Full Team for AI Programs
A dedicated healthcare development team builds governance-supporting infrastructure alongside capabilities, so evidence and monitoring exist by default.
Fixed-Scope Framework Deliverable
Where the requirement is documented governance process, a fixed-scope engagement under our engagement models delivers it with templates and decision records.
Tell Us What AI Is Running Today
Share what AI your organization uses, including inside purchased software, and how adoption decisions are currently made. Inventory usually reveals more than expected.
Advisory Limits, Decision Authority, and Boundaries
We build process and technical artifacts. We do not provide legal advice, make regulatory determinations, or certify compliance, and no vendor can guarantee your compliance. Where intended use may create diagnostic or treatment claims, SaMD classification is assessed during discovery with your regulatory advisors. We build to HIPAA-aligned practices where HIPAA applies; software cannot be HIPAA certified.
01
We Are Not Legal or Regulatory Advisors
Governance frameworks reference regulatory considerations without constituting legal advice. Determinations about applicable law belong to your counsel and regulatory function.
02
Your Leadership Makes Adoption Decisions
We design the process and produce artifacts. Which AI your organization adopts, under what conditions, is decided by your clinical and executive leadership.
03
Evidence Requirements Must Be Producible
Governance demanding evidence nobody can generate produces either circumvention or fabrication. Requirements are set against what evaluation infrastructure can actually deliver.
04
Monitoring Is Part of Approval
Capabilities are approved with defined monitoring and review cadence, since deployment approval without ongoing oversight is not governance.
05
Sensitive Application Review
AI touching behavioral health warrants additional review. We built CHIPSS, a behavioral health system, where such handling was foundational.
06
Positions We Would Maintain
We would not design governance that approves AI making regulated determinations, accepts vendor assertions without evidence, or omits ongoing monitoring from approval conditions.
Cost to Engage Governance Capability
Governance engagements are smaller than build engagements and produce documentation your organization operates. The pricing tiers below describe build work that governance informs. We publish no figures on risk reduction or approval efficiency, because those depend on your organization and portfolio. What we deliver is process and templates your committee can use.
MVP or Single Module
$40,000 to $80,000
Typically governance work alongside a first AI build, including evidence documentation, monitoring definition, and review support for one capability.
Full Platform Build
$80,000 to $200,000
Governance framework with inventory, intake and review process, evidence templates, vendor assessment, and monitoring requirements across an AI portfolio.
Enterprise Deployment
Starting at $200,000
Multi-facility governance with committee structures, documentation standards, and integration into existing clinical and technology governance across sites.
Discovery Phase Scoping
Discovery is paid and time-boxed. It produces an AI inventory, current decision process assessment, gap analysis against your risk profile, and an itemized fixed-scope estimate.
Cost Drivers to Expect
AI portfolio size including vendor capability, existing governance maturity, stakeholder count, evidence infrastructure available, site variation, and documentation depth required.
Ongoing Support Costs
Governance requires operation. Budget for periodic framework review, template updates as expectations evolve, and support as new capability categories arrive.
Third-party licensing, cloud infrastructure, data subscriptions, and hardware are separate from engineering cost and itemised clearly.
Why Build Governance With Taction
Two questions matter. Whether the consultant can read a validation report critically, and whether the process they design gets followed. Taction Software has built healthcare software since 2013, more than twelve years, with over 200 healthcare projects delivered and ISO 27001 certification. Leadership brings more than twenty years of personal experience in the field, which is separate from company age. Our wider case for Taction sits elsewhere.
We Build the Systems Governance Reviews
We build clinical AI, which means we know what evidence is producible and what requirements would be aspirational. Our healthcare case studies reflect that work.
Clinical Systems Built From the Inside
We built Voyant Health, an EHR platform, and CHIPSS, a behavioral health system, which informs how governance should treat clinical involvement and sensitive categories.
Experience Under Regulatory Registration
We built Revive Ease and PainKare, both FDA-registered applications. That work informs how we treat documentation and intended use in governance frameworks.
ISO 27001 Certified Security Management
Taction Software holds ISO 27001 certification covering our information security management practices. It certifies our internal processes and does not determine your organization’s compliance position.
We Set Requirements That Can Be Met
Governance demanding unproducible evidence gets circumvented. We calibrate requirements to what evaluation infrastructure can generate, which sometimes means lighter process than expected.
We Will Say You Need Evaluation, Not Governance
Organizations with one or two capabilities usually need measurement infrastructure rather than a committee. That recommendation replaces an advisory engagement with an engineering one.
FAQs
Frequently Asked Questions
We inventory what AI is in use, assess how adoption decisions are currently made, then present consultants with healthcare AI experience. You interview and approve each placement.
Governance alongside a build falls in the $40,000 to $80,000 range, framework development $80,000 to $200,000, and enterprise programs start at $200,000. Advisory-only engagements are smaller and scoped as discovery.
Our delivery history includes the Voyant Health EHR platform, the CHIPSS behavioral health system, and the FDA-registered applications Revive Ease and PainKare, within more than 200 healthcare projects delivered since 2013.
No. We are a software engineering firm, not a law firm or accreditation body. Legal and regulatory determinations belong to your counsel and regulatory function.
No. No vendor can certify compliance, which is an organizational state depending on your policies, processes, and operations rather than on any external assessment we could provide.
If you run one or two capabilities, evaluation infrastructure usually matters more. Governance becomes necessary when adoption decisions are being made across departments without consistent evidence.
Share what AI is in use including inside purchased software, how adoption is currently decided, your existing governance structures, your evaluation capability, and the engagement model you have in mind. We will inventory first and say plainly if evaluation infrastructure matters more than process. We do not promise instant matching or any compliance outcome.