Readiness is dynamic
Sleep, circadian disruption, workload, cognition, stress, nutrition and individual physiology interact. Static thresholds miss the pattern.
Private & confidential
Investor / R&D funding deck · 2026
VITAORBIT
AI readiness intelligence for human spaceflight — built with astronauts first, then scaled through elite performance.
Astronaut-first pilot
Task-specific readiness
Human-in-the-loop AI
Athletes as second market
VITAORBIT turns fragmented physiological, cognitive and operational data into an explainable readiness forecast for the next mission-critical task.
Investment thesis
Problem
Primary wedge
Secondary engine
Moat
The valuable asset is not another dashboard. It is a longitudinal model of human readiness under extreme conditions.
Readiness changes hour by hour, yet high-stakes teams still assemble the decision from disconnected wearables, medical checks, cognitive tests and expert judgement. VITAORBIT begins where the cost of a wrong decision is highest: astronaut training and human spaceflight. Elite sport is the secondary market and validation engine, adding frequent interventions and measurable outcomes to a shared readiness model.
Astronaut decisions are high-value
Training and mission tasks are tightly planned, heavily monitored and safety-critical — the strongest environment for proving operational value.
Elite sport accelerates learning
Athletes create denser repetitions of load, recovery and performance, helping validate portability without diluting the astronaut-first focus.
Outcomes compound the model
Each task, intervention and result strengthens a proprietary dataset linking human state, operational context and performance outcome.
Build the readiness layer for human spaceflight, validate it in astronaut operations, then scale the same intelligence across elite performance.
The problem
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Mission readiness is a high-stakes decision assembled from low-resolution, fragmented signals.
Teams can collect more human-performance data than ever, yet the operational question remains unresolved: is this individual ready for this specific task, at this specific time — and what should the team do next?
Fragmented evidence
Wearables, sleep, cognitive tests, training loads, medical observations and self-reports live in separate systems.
Population thresholds
Generic norms hide individual baselines, sex-specific and cyclical physiology, and the effects of environment or mission context.
Retrospective dashboards
Most tools describe what happened. Few forecast task-specific readiness over the next operational window.
Manual synthesis
Flight surgeons, trainers and performance leads must translate competing signals under time pressure, with no shared confidence layer.
Core gap: the market has sensors and experts, but no trusted intelligence layer that learns the individual, forecasts readiness and explains uncertainty.
Why now
Demand
Data
AI
Continuous sensing, personalised AI and a new human-spaceflight economy have converged.
VITAORBIT is possible now because mission-relevant human-performance signals can be captured continuously, multimodal time-series models can learn individual baselines, and spaceflight organisations need scalable ways to protect readiness as crew profiles and operating environments diversify.
More complex crew operations
Commercial, research and analogue programmes create more training pathways, mixed-experience crews and readiness decisions.
Signals can travel with the human
Wearables, cognitive tests, subjective check-ins, task loads and environmental data can be combined across training and operations.
Models can learn the individual
The next leap is a calibrated readiness model that updates with each person, flags uncertainty and remains accountable to human experts.
Primary pilot market
Primary user
Primary buyer
First outcome
Secondary market
Astronaut training is the proving ground. Elite sport is the scale engine.
VITAORBIT starts with the users for whom readiness is mission-critical and the institutional buyers who already coordinate medicine, training and operations. The second market — elite sport — increases data velocity, commercial reach and repeatable performance outcomes.
Astronauts and candidates
Participants need a clear, personalised view of recovery, cognitive state and readiness during demanding training and mission preparation.
Spaceflight organisations
Operators, training providers, analogue programmes and space-medicine teams need consistent, auditable decision support.
Task-specific readiness
Forecast the next 24-hour readiness window for high-load training or mission-relevant tasks, with confidence and risk drivers.
Elite athletes
Teams and performance centres provide higher-frequency training, recovery and return-to-performance outcomes using the same engine.
First product: an explainable 24-hour readiness forecast for astronaut training and mission-relevant tasks, updated as new physiological, cognitive and operational data arrives.
Product
From raw human-performance signals to an auditable readiness recommendation.
VITAORBIT is a decision-support system, not an autonomous medical-clearance tool. It shows the forecast, the drivers, the confidence and the recommended next check. Final authority remains with the astronaut, flight surgeon, mission commander or training lead.
Signal layer
Readiness intelligence
Human decision
Continuous physiologySleep, HRV, resting heart rate, temperature, movement and recovery trends.
Learns the individual baseline; detects deviation, accumulated fatigue and incomplete recovery.
Continue, adapt workload, add recovery time or request expert review.
Cognition and self-reportReaction, attention, fatigue, stress, mood and perceived readiness.
Estimates cognitive readiness and reconciles subjective state with sensor patterns.
Re-test, change task timing, introduce a countermeasure or escalate a discrepancy.
Operational contextTraining load, task demand, travel, circadian shift, heat, hypoxia and schedule changes.
Produces a task- and time-specific forecast instead of a generic wellness score.
Modify sequence, staffing, timing or monitoring intensity.
Governed clinical contextApproved medical observations, biomarkers, nutrition and sex-specific or cyclical factors where relevant and consented.
Adds context without over-claiming diagnosis; records provenance and model uncertainty.
Route to the responsible clinician or operational authority — never issue an autonomous go/no-go.
The product loop
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Observe. Personalise. Forecast. Act. Learn.
Every participant creates an individual baseline. Every task and intervention produces an outcome. Every governed outcome strengthens the readiness model.
Observe
Connect consented physiological, cognitive, behavioural, workload and environmental signals.
Personalise
Learn the individual's baseline, response patterns, uncertainty and relevant physiological context.
Forecast
Estimate readiness for a defined task and time window; expose the drivers and confidence level.
Act and learn
Record the human decision, intervention and outcome; update the model for the next forecast.
Long-term product: a simulation-based human readiness twin that helps authorised teams compare countermeasures before applying them.
Platform architecture
Core engine
Primary application
Secondary application
Trust layer
One core readiness engine. Two initial applications.
Astronaut readiness establishes the safety-critical workflow. Elite sport validates the engine at higher frequency. Both applications use the same core capability: predict an individual's response to workload, stress and intervention in context.
Individual readiness model
How does this person respond to load, sleep loss, circadian shift, stress, environment, nutrition and recovery?
Astronaut readiness
Participant view, expert review, mission-relevant task forecast and documented escalation workflow.
Elite performance
Athlete readiness, training-response forecasting, recovery decisions and return-to-performance support.
Accountable by design
Confidence scoring, data provenance, consent controls, access roles, audit logs and human authority.
Defensibility
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The moat is governed, task-linked readiness data from environments that are difficult to access and harder to reproduce.
VITAORBIT's defensibility is not the interface or a generic model architecture. It is the longitudinal record connecting an individual's state, operational context, human decision, intervention and verified outcome.
Multimodal and contextual
Physiology, sleep, cognition, self-report, workload, environment and governed expert observations.
Task- and outcome-linked
Not passive tracking: each forecast connects to a defined task, human decision, intervention and performance result.
Individual and longitudinal
The model learns within-person change across training blocks, travel, circadian disruption, recovery and extreme environments.
Trust and access compound
Competitors can copy features. They cannot easily recreate participant trust, institutional workflows, data rights and expert-labelled outcomes.
The governed evidence loop becomes the company.
Market architecture
Primary pilot
Primary expansion
Secondary market
Adjacent market
Platform layer
Enter through human spaceflight. Expand through elite performance.
The beachhead is intentionally narrow: high-value astronaut-readiness workflows sold to institutions. Elite sport is the second commercial market, using the same readiness engine with greater participant volume and more frequent outcome cycles.
Astronaut training
Astronauts, candidates and analogue crews; training providers, programme operators and space-medicine teams.
Human spaceflight operations
Mission preparation, high-load task windows, crew monitoring and research protocols across commercial and institutional programmes.
Elite athletes
Readiness, training response, recovery and return-to-performance for teams, federations and performance centres.
Extreme-performance teams
Aviation, polar, maritime and defence-related research settings where fatigue and readiness affect safety.
Research and licensing
Longitudinal human-performance studies, model licensing and approved integrations for expert-led decision systems.
Business model
Layer 01
Layer 02
Layer 03
Layer 04
High-value enterprise contracts first. Recurring licences as evidence compounds.
The initial business is B2B: paid astronaut-readiness pilots with organisations, followed by recurring platform licences. Elite-performance contracts form the second revenue line. Pricing below is an initial hypothesis to validate, not booked revenue.
Paid feasibility pilots
Fixed-scope contracts covering integration, readiness workflows, expert review and prospective validation.
Enterprise platform
Annual organisational licence plus implementation, participant capacity and premium support.
Participant and expert modules
Per-participant readiness models and optional cognitive, biomarker, environment or specialist-review modules.
Research and model licensing
Contract research, cohort analytics and approved model integrations for institutions and technology partners.
Customer
Initial product
Revenue model
Spaceflight and training organisationsOperators, astronaut-training providers and analogue programmes.
6–12 month astronaut-readiness pilot with integrations and expert workflow.
Indicative: £50k–£150k per pilot, converting to an enterprise licence.
Operational and research institutionsSpace-medicine, universities and human-performance laboratories.
Governed cohort analytics, readiness engine and research reporting.
Indicative: £100k–£300k annual licence plus integration and support.
Elite-performance organisationsProfessional teams, federations and high-performance centres.
Athlete readiness, recovery and training-response application.
Indicative: £30k–£120k annual licence, scaled by cohort and modules.
Go-to-market
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Win through access, evidence and trust — before scale.
The first year prioritises a small number of high-quality astronaut-readiness partners, named operational users and a prospective protocol. The athlete cohort follows as a deliberate secondary validation stream.
Secure anchor access
Sign 2–3 astronaut-training, analogue-mission or human-performance partners with defined users and data rights.
Build trust into the product
Implement privacy, consent, role-based access, data provenance, model confidence and human-review workflows from day one.
Prove operational utility
Measure data completeness, forecast calibration, expert usefulness, time saved and whether the output improves a real decision.
Open the second market
Use the validated engine with elite-performance partners, then convert both markets into annual licences and modules.
Founder-market fit
Domain access
Applied AI
Feasibility
Operating principle
Built at the intersection of astronaut training, applied AI and responsible human-performance innovation.
VITAORBIT is grounded in direct domain immersion rather than a remote technology thesis. The founder's training and research create a practical route to discovery and early feasibility testing; institutional partners, ethics review and prospective validation remain essential before operational use.
Human-spaceflight training
Admitted to an intensive five-month Human Spaceflight Certificate in Toulouse beginning in October 2026, creating first-hand exposure to astronaut-readiness workflows.
Oxford research lens
Completing the Executive Diploma in AI for Business at the University of Oxford, with applied work on machine-learning decision support for astronaut EVA readiness.
Human-performance pilot design
A founder-led feasibility protocol links wearable biomarkers, cognitive readiness and self-reported state before expansion to partner cohorts.
Ethics by design
Human authority, consent, explainability, sex-aware modelling and international collaboration are treated as product requirements.
Founder advantage: close proximity to the problem, the ability to test the earliest workflow at low cost and a credible bridge between spaceflight, AI, ethics and high-performance communities.
Proof plan
The pilot is designed to retire investor risk — not merely generate engagement.
The round should fund four explicit evidence gates. Targets are proposed pilot thresholds and will be finalised with operational, research and ethics partners before prospective testing.
Proof
Investor question
Proposed evidence gate
Technical feasibilityCan heterogeneous signals be captured reliably in operational settings?
Can the platform produce a stable, individual readiness timeline?
Target: at least 85% usable planned data-days, traceable provenance and reliable cross-device ingestion.
Predictive valueDoes a personalised model outperform a simple rolling baseline?
Is the signal more useful than a wearable score or static threshold?
Predefined accuracy, calibration and false-ready metrics for a 24-hour task-readiness forecast.
Operational utilityDo authorised experts trust and use the output?
Does VITAORBIT improve a real workflow without displacing human authority?
Expert-rated usefulness, decision time, alert actionability, overrides and documented reasons.
Commercial pullWill institutions pay and will the engine travel to sport?
Is there a repeatable enterprise wedge and a credible second market?
At least two paid pilots or equivalent commitments, renewal intent and a secondary athlete validation cohort.
Competition
The market has sensors and dashboards. It lacks a trusted operational readiness layer.
Alternative
What it does well
Where VITAORBIT wins
Wearables and recovery scoresDevice-specific sleep, strain and recovery products.
Continuous sensing, familiar interfaces and strong participant adoption.
Combines multiple sources with task demand, individual context, confidence and human decision workflow.
Crew and performance dashboardsMonitoring, scheduling, workload and medical records.
Operational visibility, reporting and established workflows.
Adds a prospective, personalised forecast instead of another retrospective data view.
Clinical and expert assessmentFlight medicine, sports science and specialist judgement.
Domain authority, contextual interpretation and accountability.
Augments experts with longitudinal synthesis, calibrated uncertainty and an auditable evidence trail.
Generic AI and analyticsCopilots, dashboards and horizontal machine-learning platforms.
Flexible analysis and fast prototyping.
Purpose-built readiness ontology, governed data rights, prospective validation and safety-critical workflow design.
R&D and public-funding fit
WP1
WP2
WP3
WP4
The technical risk is the product: safe, individual readiness forecasting from sparse, multimodal data.
The funded project tackles a genuine R&D challenge: building an explainable model that learns within-person change, transfers carefully across contexts and communicates uncertainty in a safety-critical human workflow.
Readiness ontology
Define the architecture linking human state, task demand, environment, intervention, decision and outcome.
Personalised time-series model
Build baseline, variation, anomaly, response and confidence models that work with small individual datasets.
Forecast and trust engine
Predict a defined readiness window, expose contributing signals, quantify uncertainty and trigger escalation rules.
Prospective validation
Test first in astronaut-relevant training and analogue settings, then assess portability with an athlete cohort.
Public-funding rationale: material technical uncertainty, responsible-AI requirements, a credible enterprise pathway and strategic relevance to human spaceflight and high-performance innovation.
Roadmap
0-3 months
3-6 months
6-12 months
12-18 months
18+ months
Astronaut-first validation. Athlete-powered scale. A compounding readiness platform.
Lock the protocol
Confirm the readiness task, outcome labels, data rights, ethics pathway, pilot partners and human authority model.
Build and sandbox the MVP
Integrate wearables, cognition, self-report, workload and environment; launch participant and expert views.
Run the primary pilot
Target 12–20 astronauts, astronaut candidates or analogue participants across 2–3 partner programmes.
Validate the second market
Test portability with a larger elite-athlete cohort while converting primary pilots into annual contracts.
Scale the platform
Expand enterprise licences, partner integrations, research use cases and governed readiness models.
The ask
Seeking investors and primary pilot partners to validate astronaut readiness intelligence.
VITAORBIT is raising milestone-based pre-seed and non-dilutive R&D funding to build the readiness engine, run the astronaut-first pilot and establish elite sport as the second commercial market. The exact round size will be tied to the final protocol and partner scope.
Astronaut-first validation
24-hour readiness forecast
Responsible AI
Elite sport expansion
01Capital
Fund an 18-month programme covering product, data engineering, responsible AI, prospective validation and enterprise readiness.
Fund an 18-month programme covering product, data engineering, responsible AI, prospective validation and enterprise readiness.
02Primary pilot partners
Spaceflight operators, astronaut-training providers, analogue programmes and space-medicine teams with named expert users.
Spaceflight operators, astronaut-training providers, analogue programmes and space-medicine teams with named expert users.
03Secondary validation partners
Elite teams, federations and high-performance centres able to test the same readiness engine at greater frequency.
Elite teams, federations and high-performance centres able to test the same readiness engine at greater frequency.
04Research and technology partners
Human-performance researchers, wearables, cognitive testing, biomarkers, data governance and AI-safety specialists.
Human-performance researchers, wearables, cognitive testing, biomarkers, data governance and AI-safety specialists.
First-phase success: a working readiness MVP; 2–3 primary partner programmes; a target cohort of 12–20 astronaut, candidate or analogue participants; a secondary athlete cohort; prospective evidence against baseline; governed longitudinal data; and a clear path from pilot contracts to recurring revenue.
Astronauts first. Athletes second. A human-readiness platform built for the most demanding environments.