Personalised AI for Human Progress
Building confidence through technology
Applied AI
Machine learning built for tangible human growth.
Behavioural Science
Deep insights into human motivation and change.
Evidence-led
Proven interventions for real-world impact.
Adaptable Model
Personalised test-and-adapt framework.
BrainHatch is a UK applied-AI company developing persistent, personalised services designed to help people overcome adversity and make measurable progress in the real world.
Meet Capability Coach
Personalised support for sustainable employment and greater independence.
Capability Coach will be BrainHatch's first service. We are developing it for people who may need more than conventional job-search support to find, return to or remain in suitable work.
Capability Coach builds an evolving understanding of the individual — their health, capabilities, confidence, skills, circumstances, aspirations and barriers to work. It provides personalised support as those needs change: from rebuilding routine and confidence, to navigating the challenges of starting and staying in employment.
One person. Changing circumstances. Continuous support.
How it works
From conversations to outcomes
Some of the hardest human problems aren't solved by providing more information. Finding sustainable work, rebuilding capability after illness or changing long-established behaviour requires support that understands the individual, adapts as circumstances change and is available when it is needed.
BrainHatch is exploring how persistent AI can provide that continuity at scale. Our approach is simple: Understand → Identify → Intervene → Observe → Measure → Learn → Improve. The objective isn't more engagement with AI. It's better outcomes in the real world.
First Principle
AI always human-backed
AI can provide continuity, remember context, support reflection and preparation, and help maintain momentum between human interactions. But not everything should be automated. Human expertise remains essential for safeguarding, clinical judgement, complex cases and decisions affecting people's rights or benefits.
Capability Coach is designed to extend the reach of human support, not replace the people who matter most.
Second Principle
Evidence before claims
Capability Coach is being developed. Its effectiveness has not yet been demonstrated in a controlled trial. That's important. We want to test whether persistent, personalised AI support can improve sustainable employment and work retention while protecting health, wellbeing, agency and trust.
Our approach is: Build → Test → Measure → Learn → Improve. We intend to develop the evidence through rigorous real-world evaluation and collaboration with research and delivery partners. Because knowing that something doesn't work can be just as important as discovering that it does.
Build the Evidence with Us
We are interested in conversations with researchers, universities, public-service and employment-support organisations, employers, behavioural scientists, technology partners and early-stage investors. If you're interested in helping test where personalised AI can — and cannot — improve real-world outcomes, we'd like to hear from you.
Maya, 29 — health, confidence and a disrupted career
Starting point: Maya worked in hospitality management until a period of ill health. She has been out of work for 14 months. Her health is improving, but her sleep is irregular, confidence is low and applications feel overwhelming. She tells her work coach that she is “looking for jobs”; in reality she often avoids opening job sites because they make her anxious.
Weeks 1–6 — rebuild before job search. Capability Coach discovers through repeated conversations that Maya's immediate constraint isn't lack of vacancies or CV skills. It's routine and confidence.
They agree on very small actions: getting up consistently, leaving the house, reconnecting with a former colleague and gradually spending time thinking about work without immediately applying.
Crucially, Maya can say:
“I didn't do any of it this week. I basically hid from everything.”
She is willing to say this because she understands that the conversation is not a compliance report to the benefits system. Capability Coach can challenge avoidance without Maya fearing that an admission of a bad week will automatically be interpreted as non-compliance.
Months 2–4 — the problem changes. Maya's routine improves. Capability Coach remembers that she enjoyed training junior staff, hated late-night shifts and previously mentioned being good at handling difficult customers. Instead of simply returning her to hospitality, it helps her explore customer success and training roles.
Applications now become useful, so the intervention changes: CV, occupational exploration, application planning and interview practice.
Month 5 — employment. Maya gets a customer-service role. Capability Coach doesn't declare success and disappear.
Months 5–9 — retention. After three weeks she starts saying she is exhausted. The Coach connects this with earlier conversations about recovery and notices that she is slipping back into an all-or-nothing pattern: trying to prove she is “completely better”.
Support changes again: pacing, preparing a conversation with her manager, thinking through adjustments and protecting sleep.
What this case demonstrates: Capability → occupational fit → job search → transition → retention. The objective was never simply to maximise applications.
Darren, 52 — redundancy after 27 years with one employer
Starting point: Darren has worked in warehousing and logistics since he was 24. His employer closes the site. He isn't ill and considers himself perfectly capable of working, but has never written a modern CV, feels humiliated by online recruitment and believes employers want younger people.
He doesn't need therapy. He needs translation, confidence and practical momentum.
Week 1. Capability Coach learns his employment history conversationally. Darren initially describes himself as “just a warehouse supervisor”. Over several interactions, the system helps unpack what that actually meant: shift management, health and safety, stock systems, training, resolving staffing problems and meeting dispatch targets.
Weeks 2–5. It remembers that Darren dislikes lengthy written exercises and responds better to short practical tasks. Support adapts accordingly: ten-minute actions rather than long coaching sessions.
When an application asks for an example of leadership, Capability Coach can retrieve the substance of a story Darren told three weeks earlier about managing a Christmas staffing crisis. He doesn't have to reconstruct his life history every time.
Month 3. Several unsuccessful applications knock his confidence. Rather than mechanically telling him to apply for more jobs, the Coach recognises the change, reviews what appears to be happening and helps him widen the search towards facilities and operations roles.
Month 4. He gets an operations coordinator job.
Months 4–6. Now the challenge is digital confidence. Capability Coach remembers which software and terminology he struggled with during the job search and helps him build a learning plan for his first few weeks.
What this case demonstrates: Memory isn’t merely remembering Darren’s name. It creates an accumulating working model of his capabilities, preferences, experiences and effective ways of supporting him.
Aisha, 38 — caring responsibilities and constrained availability
Starting point: Aisha wants to return to work after several years caring for children and an elderly parent. Her qualifications are good, but her available hours are complicated and unpredictable.
A conventional employment interaction could frame those constraints as barriers to be overcome.
Capability Coach instead needs to distinguish constraints that can change from constraints that the job needs to fit around. Over several months it helps Aisha map realistic availability, rediscover professional skills, explore suitable occupations and prepare applications.
She turns down a role.This is an important moment.
If she believes Capability Coach is effectively reporting to the body determining her benefits, she may conceal why. Instead she can explain that the nominally flexible employer revealed at interview that staff were routinely expected to stay late.
The Coach doesn't judge the decision as “failure to enter employment”. It incorporates new information: predictable finishing times are a critical component of sustainable job fit.
Later it helps her identify a role with somewhat lower starting pay but reliable hybrid hours.
Six months into employment, caring pressures increase. Capability Coach already understands the family context and helps her think through options before resignation becomes the default response.
What this case demonstrates: Optimising for sustainable employment, rather than the fastest possible job entry, can produce very different decisions.
Claire, 46 — currently employed but at risk of falling out of work
Claire has a chronic health condition and has begun taking intermittent sick leave. She is increasingly convinced she cannot continue working.
Initially the Coach helps her understand patterns around fatigue, workload and recovery.
Over time it becomes apparent that particular duties and consecutive long days are associated with the worst periods.
Capability Coach cannot diagnose Claire or decide what adjustments she requires.
It can help her organise observations, prepare for a GP/occupational-health conversation, understand questions she wants to ask and rehearse a conversation with her manager.
Several months later, if Claire remains in work, the relevant outcome isn't “job obtained”. It is labour-market detachment potentially avoided.
What this case demonstrates: The employment journey can start before unemployment. Prevention may eventually be one of the most economically interesting applications of the model.
Leo, 23 — executive-function difficulties and repeated setbacks
Starting point: Leo has had several short jobs and periods of unemployment. He wants to work but repeatedly misses appointments, leaves applications unfinished and loses jobs after being late.
He has heard a lot of versions of “you need to be more organised.”
Capability Coach gradually learns something more useful: Leo responds well to immediate, concrete prompts but poorly to multi-step plans extending over several days.
So the service adapts. Instead of:
Update CV → search vacancies → shortlist five → draft applications → submit by Friday
the Coach might work with him one action at a time.
Months later, Leo starts work in a kitchen. The intervention changes completely. The Coach helps him prepare clothes and transport the night before shifts, anticipate rota changes and work out what happened after a late arrival rather than treating it simply as a motivation failure.
After an argument with his supervisor, Leo tells Capability Coach:
“I nearly just didn't go back.”
Because this isn't automatically transmitted to his benefits office, employer or employment adviser, he has somewhere to disclose the wobble before it becomes job loss.
The Coach can help him slow the decision down, understand what happened and decide whether he needs human help.
What this case demonstrates: Persistent support may be particularly valuable at the small moments where trajectories change.
Born in the UK, Built for Progress
Restoring confidence and employment through human-centric AI. We empower individuals to reclaim their independence and achieve sustainable growth through innovative technology.