Women are being failed by a medical system that was never designed to understand them. We are building the infrastructure to change that, starting with educating the practitioners women already trust, and working up until no woman has to inform her own doctor about her own body.
Kōnenki.ai · A New Season. A New Standard of Care.Kōnenki.ai is an AI-powered practitioner education and certification platform for perimenopause and menopause care, built to close the gap between what research shows and what women are actually told.
The failure is not individual doctors being uninformed. It is structural: medical education, research funding, clinical guidelines, and cultural attitudes compounded over decades. That gap is the business case.
Perimenopause and menopause are more than hot flashes and mood swings. They are a hormonal transition with documented consequences for cardiovascular health, neurological function, bone density, mental health, and metabolic risk. When practitioners are not trained to recognise and treat the full picture, women pay for it with their health.
A peer-reviewed study found that structured menopause education significantly improved clinician confidence across all measured competencies. The gap is not awareness. It is infrastructure.
We don’t replace clinical thinking. We accelerate it. The platform is not a diagnostic tool. It is the trusted, research-backed resource that neither the women suffering nor the practitioners treating them currently have access to.
An AI-powered practitioner education and certification platform that trains the practitioners already in these women’s lives to have genuinely evidence-based perimenopause and menopause conversations. The platform retrieves current, peer-reviewed evidence in real time rather than relying on static content, meaning what practitioners learn is always grounded in the latest clinical guidance from The Menopause Society, NICE, RCOG, and PubMed.
Built on three integrated disciplines: pedagogy and learning science, AI and digital development, and practitioner-facing experience design. The platform uses generative assessment, adaptive competency pathing, and AI-simulated client consultations.
Practitioners query symptoms, treatment pathways, and clinical guidelines and receive evidence-graded answers grounded in The Menopause Society and NICE guidelines in seconds. The same function OpenEvidence provides for general medicine, purpose-built for perimenopause and menopause care.
A dedicated, auditable layer for assessing medication, supplements, wellness claims, and beauty products against peer-reviewed clinical research. Practitioners can evaluate what they recommend and why, replacing marketing copy with evidence. This protects them clinically and differentiates them commercially.
Practitioners who complete the programme earn a Kōnenki.ai Certification: a visible credential their clients can look for. The mark creates pull: it signals trust, justifies premium positioning, and builds a network effect as certified practitioners advocate for the platform.
Kōnenki.ai is an evidence-based platform. Every claim in the curriculum is traceable to a published, peer-reviewed source. Every piece of content passes through a defined governance process before it reaches a practitioner. This is not a compliance posture. It is the product.
All curriculum content is grounded in the published guidelines of:
Kōnenki.ai adopts the GRADE framework (Grading of Recommendations, Assessment, Development and Evaluations), the international standard for evaluating clinical evidence quality. Applied to all curriculum claims, it ensures practitioners understand not just what the evidence says but how strong that evidence is.
The AI surfaces, structures, and personalises content. A human clinical expert approves it. No content goes live without clinical sign-off.
The pharmaceutical, supplement, beauty, and wellness industry directed at menopausal women is largely unregulated and often evidence-free. Kōnenki.ai includes a dedicated evidence evaluation layer that allows practitioners to assess product and supplement claims against peer-reviewed clinical research.
No equivalent exists in the market.
Most online courses deliver information. Practitioners read it, pass a quiz, and move on. What they do in the room with a client changes very little. Kōnenki.ai is built around a different objective: durable behaviour change. Every platform design decision maps to an established learning mechanism.
The result is a platform where completion is not the outcome. Demonstrated competency is.
FDA initiated removal of the black box warning on hormone replacement therapy on November 10, 2025, reversing a policy that suppressed prescribing for over 20 years. First labelling changes approved February 12, 2026. Demand for qualified practitioners is surging.
The Steven & Alexandra Cohen Foundation granted The Menopause Society $5M in October 2025 to train 25,000 healthcare providers in 3 years, confirming institutional appetite for exactly what Kōnenki.ai builds.
AI inference costs fell 280-fold between November 2022 and October 2024. RAG architecture for medical knowledge bases is proven in production. The technical barrier that made this impossible three years ago no longer exists.
Women's health investment hit a record $2.6B in 2024, nearly $1B above 2023. Menopause remains one of the most underfunded segments. Only ~7% of femtech startups focus on it.
The UK's Menopause Workplace Pledge, NHS menopause guidance, and British Standards Institution workplace standards have created regulatory and cultural infrastructure Kōnenki.ai can connect to directly.
The first generation to research their own health proactively is entering perimenopause. They demand qualified practitioners and will leave providers who cannot meet that bar. The demand is already here.
AI-personalised training and a certification mark for individual clinicians, private clinics, gyms, and allied health practitioners. Lowest regulatory barrier. Fastest revenue. The beachhead.
An AI tool used around patient interactions, helping practitioners make better-informed clinical decisions in the moment, not just in advance training.
Formally accredited continuing medical education: the gold standard in clinical education and the culmination of the Kōnenki.ai roadmap.
Annual licence per clinic, gym, or allied health practice. Fast procurement cycle. Clear buyer: clinic owner or operations director. ROI framed as staff capability and client retention uplift. Certification mark creates external pull.
Individual practitioners and wellness coaches at $299–499/yr. No sales motion required. Builds brand awareness and creates a pipeline of institutional advocates.
Corporate wellness programmes, self-insured employers, and insurance companies. Longer sales cycles (6–18 months) but $50K–200K contract values. ROI framed around the $26.6B annual US productivity cost.
Hospital systems, medical schools, and professional associations at $100K–1M+/yr. Co-branded or white-labelled CE delivery. Evidence infrastructure partnership opportunity: Kōnenki.ai serves the allied health and aesthetic practitioners The Menopause Society does not certify and cannot reach.
Telehealth platforms, including Midi Health ($1B unicorn, 2025) and Gennev, are building internal education functions. Kōnenki.ai builds the evidence engine and certification infrastructure those platforms would need to acquire rather than build.
| Platform | AI-Powered | Allied Health | US + UK | Cert Mark | Evidence Eval | Category |
|---|---|---|---|---|---|---|
| Kōnenki.ai | ✓ RAG-driven | ✓ Core focus | ✓ Concurrent | ✓ | ✓ | Our position |
| Menopause Society MSCP | ✗ Static exam | ✗ MDs only | US only | ✓ | ✗ | Monitor · Building own digital platform (NextGen Now) |
| BMS Certificate (UK) | ✗ Static | ✗ HCPs only | UK only | ✓ | ✗ | Phase 3 UK partner |
| Menopause Movement (UK) | ✗ Static | Fitness only | UK only | ✓ | ✗ | Direct Ph.1 UK comp |
| IWHI | ✗ | Individual only | US only | ✗ | ✗ | B2C · Individual · Deep clinical |
| Midi Health | ✓ | ✗ | US only | ✗ | ✗ | Telehealth / acquirer |
| Hirsch Academy | ✗ Static video | ✗ HCPs only | US only | ✗ | ✗ | Monitor · AI pivot risk |
| RealDocAI / Flourish | ✓ LangChain/RAG | ✗ Patient-facing | US only | ✗ | ✗ | B2C · Watch closely |
Build the evidence engine. Launch the MVP. Sign first 50–100 US and UK certification clients. Name the clinical advisor. Reach $150–300K ARR at Month 18. Validate geographic launch decision through customer discovery.
Layer clinical decision support as a premium tier. Open insurance and corporate wellness channels. Integrate wearable platforms. FDA SaMD review complete. Medical Advisory Board formed.
ACCME accreditation via clinical partner. ANCC for nursing and NP education. BMS or FSRH CPD partnership in the UK. Hospital CE departments engaged. The Menopause Society partnership conversation initiated.
Medical schools, residency programmes, NHS institutional procurement. The Menopause Society is building its own digital education platform (NextGen Now) with $5M in Cohen Foundation funding. Kōnenki.ai's differentiation is the allied health, clinician, and private clinic scope TMS does not serve. The Phase 3 conversation is a partnership on infrastructure, not a competition on audience. The goal is not an exit. It is changing the standard of care permanently.
Alliances and channel leader with 25+ years building ecosystems across Cloud, SaaS, and AI with the world's leading technology companies, including all three hyperscalers. Proven record driving strategic partnerships, revenue growth and go-to-market execution across Microsoft, SAP, Databricks, Google, Dell, and Qlik. Deep C-level relationship experience and a direct line to the enterprise buyers Kōnenki.ai serves.
A clinical team with a named lead physician at its centre. The lead is MSCP-certified and anchors the evidence framework and Human-in-the-Loop governance. The broader clinical team covers the full scope of perimenopause and menopause care: cardiovascular health, neurological function, bone density, mental health, and metabolic risk. This is a strategic differentiator, not a checkbox. Clinical conversations in progress.
Clients include AstraZeneca, British Council, UKRI, British Academy, Cambridge University Press, Pearson, LSE, Chatham House, SOAS, and the Royal College of Art. Active engagement across three phases of the Kōnenki.ai build.
| Item | Basis | 18-Month Total |
|---|---|---|
| Platform Build | ||
| Wonder Inc Phase 1 & 2 engagementConfirmed | Wonder Inc proposal: £10,000 (~$13K) | $13,000 |
| Full platform MVP buildModelled | HIPAA-compliant AI SaaS with RAG layer: $150K–$500K range (Ptolemay 2025; Biz4Group 2025). Mid-point applied. To confirm with Wonder Inc. | $350,000 |
| RAG infrastructure and AI running costsModelled | Vector DB $25–50/mo (Pinecone/Weaviate); LLM API costs at MVP scale over 18 months. | $18,000 |
| Platform subtotal | $381,000 | |
| Clinical and Medical | ||
| Fractional CMO / Clinical LeadModelled | $8–15K/mo range for fractional clinical lead (Quintuple Aim, 2025). $10K/mo applied for part-time MSCP-certified profile. | $180,000 |
| Clinical content and curriculumModelled | GRADE-aligned evidence layer, assessment design, specialist modules. $4–5K/mo for specialist contractor over 12 months. | $60,000 |
| Clinical subtotal | $240,000 | |
| Legal and Compliance | ||
| Healthcare regulatory attorneyModelled | HIPAA/FDA SaMD specialist: $300–500/hr; $25–50K for foundational setup (LA Tech & Media Law, 2025). Mid-point applied. | $40,000 |
| HIPAA compliance infrastructureModelled | HIPAA documentation required for healthcare VC diligence and BAA execution. Covers BAAs, privacy officer, risk assessments, and audit logging. [Source pending: West Monroe Partners, 2025] | $20,000 |
| Corporate legal (entity, IP, contracts)Modelled | Delaware C-Corp, IP assignment, founder agreements, advisor contracts. | $15,000 |
| Legal subtotal | $75,000 | |
| Team | ||
| Founder salary, Nawarh Khalil, 18 monthsModelled | Pre-seed CEO salary benchmarks: $100–150K annually. $120K/yr applied. | $180,000 |
| Head of Commercial, first market, 18 monthsModelled | Senior B2B SaaS sales, healthtech sector: $110–140K base. $120K/yr applied. Second geography deferred to Series A. | $180,000 |
| Team subtotal | $360,000 | |
| Operations | ||
| Operations, tools, subscriptionsModelled | CRM, PM tools, cloud hosting, accounting, HR admin. $3–5K/mo for early-stage SaaS. | $54,000 |
| Operations subtotal | $54,000 | |
| Go-to-Market | ||
| Customer discovery and researchModelled | Structured interviews, focus groups, field research across US and UK segments. | $20,000 |
| Conferences and partnershipsSourced | The Menopause Society Annual Meeting ~$1,200; AmSpa Annual ~$1,500; BMS events; travel. 3–4 key industry events over 18 months. | $25,000 |
| Brand, marketing, collateralModelled | Website, cert mark design, sales decks, first-customer acquisition support. | $30,000 |
| GTM subtotal | $75,000 | |
| Contingency | ||
| 15% contingency bufferModelled | Standard pre-seed contingency. Accounts for TBD geography, platform scope changes, and hiring timeline variance. | $176,000 |
| Total 18-month ask (rounded to $1.5M) | $1,361,000 | |
Retrieving information from memory produces stronger long-term retention than re-studying the same material. This effect holds across domains, age groups, and material types. The platform's generative assessment design, where questions and scenario parameters vary dynamically rather than being drawn from a fixed bank, applies this mechanism directly.
Memory retention decays in a predictable curve. Studying material at spaced intervals, timed to occur just before forgetting sets in, rebuilds and strengthens retention more efficiently than massed or blocked study sessions. The platform's algorithmically timed micro-learning nudges and competency review prompts apply this mechanism to busy practitioners who cannot commit to extended study sessions.
Learning that is embedded in authentic, contextually relevant activity transfers more reliably to real-world practice than decontextualised instruction. For practitioner education, this means simulating the situations practitioners will actually encounter. The platform's AI-generated client persona simulations place practitioners in realistic perimenopause consultations, making the learning immediately applicable to clinical behaviour.
Working memory is finite. Presenting learners with material that exceeds their current capacity impairs learning rather than accelerating it. Conversely, presenting material pitched below current competency is inefficient. Adaptive systems that continuously estimate a learner's knowledge state and pitch content to the appropriate level maximise the efficiency of learning time. The platform's competency gap detection and module sequencing apply this mechanism.
Clinical practice that does not update with current evidence causes harm. The half-life of medical knowledge varies by specialty, but in rapidly evolving fields like menopause care, guidelines can shift significantly within two to three years. The platform's agentic evidence surveillance layer monitors primary sources continuously and routes updates through clinical review before any curriculum change is applied, ensuring practitioners are certified against current, not outdated, evidence.
A structured telementoring programme using case-based, iterative peer learning significantly improved clinician confidence across all menopause competency domains assessed, including breast health, sexual dysfunction, and weight management. This is the most directly relevant published evidence for the Kōnenki.ai model: structured, case-driven education, applied to the specific competency gaps Kōnenki.ai addresses.