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Adoption outpaces oversight
AI moved from experiment to infrastructure in eighteen months. Governance, controls, and workforce capability are not catching up on their own.
HR Rebooted is building the operating system for AI governance, the layer where strategy, policy, controls, evidence, workforce capability, and continuous monitoring all live in one connected system. We have the platform. We have the methodology. We have the team. We are raising capital to scale.
Every other layer of the AI stack — models, infrastructure, applications — has a winner emerging. The governance layer does not. The organizations actually using AI today cannot see how, cannot evidence what, cannot demonstrate compliance, and cannot keep pace with the regulators piling on obligations. That is the gap we are closing, on a timeline that does not wait.
AI moved from experiment to infrastructure in eighteen months. Governance, controls, and workforce capability are not catching up on their own.
NIST AI RMF, ISO 42001, the EU AI Act, sectoral fair-employment and fair-lending rules, state-level laws. The list of obligations only grows.
CEOs and audit committees increasingly want a structured, current read on AI exposure. Most organizations cannot produce one.
Capability without trust drives quiet resistance. Trust without capability drives unmanaged over-reliance. Both are governance problems.
A policy in Word, a monitoring dashboard, a consultant's report — none of these add up to defensible governance. Buyers know it.
Categories are defined by the leader who shows up with a complete system before the market settles. That window is open in AI governance today.
Leading this category requires three things: a real product, a defensible method, and people who have done the work. Most contenders have one. We have all three, and we built them to plug into each other.
The SaaS platform. Nine modules covering committees, use cases & risk, documentation, training, safeguards, monitor & control, policy generation, AI directory, and grow & scale. Ten behavior evaluators on every model call (hallucination, drift, bias, dangerous advice, injection, refusal calibration, bigotry, logical fallacy, partisanship, misinformation) backed by a 200-rule, patent-pending guardrail library shared with the Governance 1st Browser Extension. Asset governance across five asset types (use cases, agents, prompts, guardrails, filters) at three tiers (template, organizational, individual). Built multi-tenant from day one.
A seven-area audit framework (GAP Analysis, Leadership 360, Compliance Readiness, Workforce Skills, Workforce Anxiety, Shadow AI, Policy Review) resolving to a single five-level maturity index across eight governance domains, plus a nine-workstream implementation program executed across three phases. Documented in client-facing program manuals, defensible to a board or a regulator.
Founder Michelle Strasburger brings 20+ years of HR executive experience and recognition as a top CHRO; CTO Kelly Cunningham brings 30+ years engineering high-performance systems, including leading 120-person global teams. HR practitioner depth where the buyer lives, paired with senior engineering where the product gets built.
Most competitors offer a piece: a policy library, a monitoring tool, a consulting engagement, a compliance template. We have all of those as one connected system, with technical depth that lets us govern AI use itself rather than chase the tool of the month.
Tools change monthly. The durable object of governance is how people apply AI to work. Our platform models AI use, not vendor SKUs, so the value compounds as the ecosystem churns.
Hallucination, drift, bias, dangerous advice, injection, refusal calibration, bigotry, logical fallacy, partisanship, and misinformation evaluation on every model output, backed by a 200-rule, patent-pending guardrail library. Most monitoring tools cover one or two. We cover the full range of ways AI fails in production.
When an audit closes, the findings, the inventory, the policies, and the controls land in the same platform that operationalizes them. No static report. Re-assessment is a living capability.
Use cases, agents, prompts, guardrails, and filters governed at template, organizational, and individual tiers. The model is novel, the implementation is shipped, and it matches how AI is actually used.
NIST AI RMF, ISO 42001, HIPAA, GDPR, FedRAMP, SOC 2, PCI DSS, CCPA, Colorado AI Law. The obligations are built into the framework, not retrofitted onto each engagement.
AI Policy FastTrack and a browser-extension entry point let buyers start in days, then grow into the full Governance 1st platform without re-platforming. Most platforms are all-or-nothing. We are not.
The product is shipped. The methodology is documented. The team is in seat. Capital is what turns proof into category leadership: the engineering capacity to support enterprise scale, the go-to-market motion to reach the buyers, and the certifications that unlock larger deals.
Multi-tenant capacity, enterprise SSO and identity, deeper integrations across HRIS and SaaS, more evaluators, deeper monitoring instrumentation. The roadmap is well defined; capital accelerates it.
AI Advocates team expansion (audit and implementation specialists), partner channel for systems integrators and consultancies, marketing for category education. The product sells; we need the reach.
SOC 2 Type II, ISO 27001, eventually FedRAMP. Each unlocks a tier of enterprise and public-sector buyers we cannot fully serve today.
Thought leadership grounded in real workforce and governance data, including MyCareer Navigator's research infrastructure. Category creators win by educating their market, not just selling to it.
A 30-minute conversation: where we are, where we are going, and where capital can take this. If the thesis lands, we will follow up with the deeper materials.