Projects
Six products. The full record.
Everything we have built since 31 May 2026. Status is stated plainly: four live, one in design, one in development.
ConsumerSuit
UK rights, in plain English
The problem
Tenants, consumers and employees with a genuine claim often cannot afford help and do not know where to start.
Who it is for
UK tenants, consumers and employees, including people whose first language is not English.
Where it could go
More case types and clearer guidance at every step.
What exists today
- A live web app that helps you set out your England and Wales rights case clearly and in order, with the relevant law explained along the way.
- Covers 28 areas of civil law, from deposits and unsafe housing to flights, parking, faulty goods and unpaid wages.
- Citations are fetched from legislation.gov.uk rather than recalled from memory, so a wrong section number is a bug we can find.
- Your case can be written and read in your own language; the translated copy is for comprehension and you send the English version.
- Honest by design: free self-help, not legal advice, not a law firm.
How AI is used
Built end to end with Claude. Models read the facts of a case; a retrieval layer fixes the citations to the statute text. Accuracy is measured in public-style scorecards, including the ones that look bad.
The end goal · direction, not shipped
Law within reach
The end point is to make the law easily accessible: your rights in the palm of your hand, so you can gain the knowledge, fight your own case, prepare documents professionally, and save time.
The same approach could one day help speed up places where a backlog of cases has to be checked one by one, such as parts of government and the courts and tribunals system. A slow system prolongs the damage. Many people end up accepting injustice because the process is built to wear ordinary people down, while the companies and people who caused the harm carry on untouched. We want to shorten that distance.
- 1,500+ commits
- 92 days of founder journal
- 28 areas of law
Astral Nexus
Sky, signs and tradition
The problem
Astrology tools are scattered, ad-ridden, and rarely explain their method.
Who it is for
People who want to explore, and are curious how the sky looks different in different traditions and cultures, including their own Moon sign, rising sign and nakshatra.
Where it could go
More traditions and place-aware tools.
What exists today
- A live site with reading tools across traditions. The birth chart is calculated on your own device and explained in plain words.
- The astronomy is real: a published open-source ephemeris library does the sky maths, with a live view of where the Moon is now and for the next fourteen days.
- A library of signs, traditions, essays and verse, with interface languages including English, Spanish, French, Hindi, Indonesian, Tamil and Telugu.
- Research-led content: more than 530 sources were read, extracted and fact-checked into dossiers on card traditions, dreams and their Vedic roots.
- No AI pictures of deities, by decision. Dream readings are opt-in and their source ids are validated.
How AI is used
Claude models do extraction and synthesis; open models translate and chat; image models draw the card decks. Every AI step has a validator behind it.
The end goal · direction, not shipped
One place to read the sky, every way the world did
The end point is for everyone to try the different cultural readings of the sky in one place, and to learn how each one is calculated and derived: how people across the world saw the sky and the stars, and connected them to personality. Learning about yourself, and your connection to the stars.
Later we want to bring in ancient books, palm leaves and old papers, in one place, added by the people who work with them: researchers, scholars, archaeologists and anyone connected to the work, each with its source recorded.
- 159 commits in six weeks
- 530+ sources researched
- 7 interface languages
Kathaa 360
Spoken storytelling, one good hour
The problem
Daily spoken storytelling used to give families something to share and talk about. Many children and young people now spend evenings alone, with nothing to say to each other.
Who it is for
Children home alone, busy adults who want one good hour instead of endless scrolling, and isolated young people.
Where it could go
More series (myths, history, children’s bedtime knowledge), family accounts, and narration in familiar voices with recorded consent: adults only, no voice cloning, stored on the device.
What exists today
- A web app with the series The 12 Jyotirlingas, first three chapters: Sanskrit verses with transliteration, a story read aloud, and a private journal.
- A deliberate 60-minute daily limit. It is built to end, not to hook.
- The original Sanskrit is the authority. A rights gate blocks any story that has no rights record, enforced by a script and tests.
- Late-night stories live on a separate shelf from bedtime stories.
How AI is used
Claude audits, writes tests and checks the content pipeline. We compared neural and built-in voices by ear and put the voice on hold rather than ship something flat. Planned, if we get API credits: Claude would help with the reasoning and explanations around a story, such as what to learn from it and what to avoid.
The end goal · direction, not shipped
Bring the night-time story back
We used to sit at night to share horror stories, and sit with children for a bedtime story before sleep. We want that back. It also preserves the beliefs and generational stories of old times: people who fought for their land and their freedom and became the legends of a place.
Stories carry values. As the world moves on with information shaped by social media and the news, many people lose track of what is right and what is wrong, and what is worth fighting for. They are easily baited by people who lack morals and values, and put the wrong people in power. Governments can be at fault, but the people who put them there are citizens. Stories that teach courage, fairness and whom to trust are part of how a society chooses well.
Stories also set the imagination running. Many of our own ideas began with a story: a simple cartoon that sent the mind wandering, or a conversation where someone shared what they knew and we noted down our ideas. The Mahabharata, the Ramayana and the Bhagavad Gita do this at scale. They show a way of life, and through the stories of kingdoms, ministers, teachers, gurus, sculptors, mathematicians and others, they record how people wrote down their views and knowledge and shared them with the world. They open a door: if you walk this path, the end can look like this. They also show what is worth learning from these people, and what to avoid.
The story map ahead
Only The 12 Jyotirlingas is live today. These are stories we are hunting for. Each one will be cited to its source, and its rights will be researched and recorded before it ships: old tales may be free to tell, but a particular retelling, translation or photograph may not be.
Sammakka and Sarakka
A mother and daughter of the Koya tribe who, in oral tradition, stood against the Kakatiya king over a tax the people could not pay. Remembered every two years at the Medaram Jatara in Telangana.
Vikram and Betaal
King Vikram carries a vampire-spirit who tells a riddle story at every step. Known from the Baital Pachisi, in the Kathasaritsagara compiled by Somadeva in the 11th century.
Onake Obavva of Chitradurga
A soldier’s wife who, in the 18th century, held a narrow gap in the fort wall with a pestle (onake) while the fort was under attack.
Hero stones (Veeragallu)
Memorial stones raised across Karnataka and nearby states for fighters who died defending a village, cattle or women. Over time many became the local guardian.
Guardians of the village
Village deities and spirits that watch a boundary, a well or a bridge, and the stories told about them.
Mohini of the Puranas
The enchantress best known for tricking the demon Bhasmasura into destroying himself, a different figure from the folk spirit above.
The woman who lures by night
A folk tale told in many versions and under many names (the Yakshi or Yakshini, Mohini, and others): a beautiful woman at night, near the shore or some lonely place, draws young people in with her beauty. Once they follow her home she shows her true, aged self and devours them. The late-night shelf’s classic, to be collected in its regional variants, with each version credited.
Legends behind local landmarks
The simple, heroic stories behind the statues, bridges and memorials that became a place’s attraction. Examples of the kind: the loyal dog at Shibuya station, Hachiko, and Greyfriars Bobby in Edinburgh. We hunt for these in every region, and cite each one.
Rani Abbakka, Kittur Chennamma, Velu Nachiyar
Queens who took up arms against the Portuguese and the East India Company.
- 34 content tests
- rights gate on every story
- zero spend to build
Dish What Do I Cook Today?
Home cooking, for one
The problem
More meals are being ordered in, and more people live alone, so everyday cooking is becoming a lost skill and cooking for one feels pointless.
Who it is for
People living alone, beginners, and anyone who cannot decide what to make from what is in the kitchen.
Where it could go
Wider recipes, pantry-aware suggestions, and meals that fit a solo routine, with safety checks on every new recipe. Plus an introduction to how healthy meals are prepared, with demonstrations where they would help.
What exists today
- Type the ingredients you have and it suggests a dish with beginner-friendly, numbered steps.
- 16 built-in everyday dishes, with no-oil variants and flavour tips that upgrade a dish when you have the right extra ingredient.
- Hinglish works: tamatar, aloo, tel. Near-miss hints tell you the one thing to add to unlock another dish.
How AI is used
Built with Claude. An AI fallback on AWS Bedrock proposes a dish for combinations the tool does not know, behind a cost cap.
The end goal · direction, not shipped
Your own chef, at home
More people than ever live alone, and many choose to order food in rather than cook. Dish is for the bachelor, the beginner and anyone who does not know what to make: to cook healthy food from what is already in the kitchen.
The feeling we are aiming for is that you have your own chef in your own kitchen.
- 16 dishes
- 10 automated tests
- live in days
Circuit Lab 360
Electronics for complete beginners
The problem
Electronics feels closed to people who know nothing about it: the tools assume you already understand the maths.
Who it is for
Complete beginners, students, and curious tinkerers.
Where it could go
A guided path from first circuit to board-level thinking, built on a real simulator.
What exists today
- In design, with the engine underneath already working. Every number a learner will see comes from a real circuit solver, ngspice, running as WebAssembly in the browser. We proved it in a feasibility spike.
- An ablation engine that removes each part in turn and asks the simulator what happens, so the tutor can explain what really breaks and why.
- 24 verified circuit packs. A model proposes, the simulator decides; anything it gets wrong is rejected by the gate.
- A student loop that measures how well a model learns the lab: 96% to 100% on a hard unseen exam, with a validation gate that blocked a lesson that made things worse.
- 84 automated tests. No learner interface and no public site yet, and we say so.
How AI is used
Opus and GPT-6 author and review circuits under a hard spend cap. They never provide the numbers; the solver does. Planned, if we get API credits: Claude would power the tutor that reasons about a circuit and explains it in plain language.
The end goal · direction, not shipped
Can models find leaner circuits?
The end point is to take advanced models and test whether they can reduce the number of resistors, transistors, capacitors and other components in a circuit while keeping it working, which raises efficiency, and whether they can propose genuinely new designs and structural changes in electrical circuits.
If that works, it could feed back into the boards and modules people build with, the Arduino-class microcontroller boards and the sensor and power modules around them. Every result will be checked by a real circuit solver, never taken on the model’s word.
- 84 tests
- 24 verified packs
- real ngspice in the browser
No public site yet Volunteer to test
Hrushimanju
Wear what suits you
The problem
Most people own clothes that do not suit their colouring and have no affordable way to find out what does.
Who it is for
Anyone who wants to dress well from the wardrobe they already own.
Where it could go
Knowing what to wear without hiring a colourist.
What exists today
- In development: AI-guided personal colour analysis applied to the clothes you already own.
- We pre-registered a reliability test for colour classification before running it. It failed. We did not move the bar; we changed the product so the matching engine leads and classification is shown with honest confidence.
- Research and legal groundwork are underway, including privacy and data protection assessment. There is no product yet; a coming-soon page and a tester sign-up by email are live.
How AI is used
Claude runs the experiments and the review. The pivot came from the measurement, not from opinion.
The end goal · direction, not shipped
Design yourself
For everyday users: know what suits you for a meeting, a date or a function, using the clothes you already own instead of being sold new ones.
For the end goal: cleanly custom-design your own outfit in our software. Cosplayers who hesitate because they think they must hire a designer and pay for trials could try a character themselves. Someone interested in fashion design who could not enrol on a course gets a practical, live simulation to learn on.
Beyond that: designing yourself rather than a generic 3D model. If a VR game that scans you and turns you into a usable character arrives, this becomes the way to build a realistic one, and producing a game is a stated final goal of this project.
Measured by us
What our own experiments proved, and why the hurdle is high
What we proved
- The signal is real. At 391 people, the link between what the camera reads and the human skin-tone rating is about 6.4 standard deviations from zero (r = -0.33). It is weak, about 11% of the variation, but it is not noise.
- We know where the variation comes from. Within one fixed take it is 2.52 L*; between different people 9.31; between captures of the same person 11.25. The same face varies more with the lighting than people vary from each other, which is a measured reason to control the capture instead of trying to model the light.
- Combining captures helps. Using every capture of a person instead of one lifted the link by about a third (0.221 to 0.296).
- Undertone holds steadier than depth. In one face over five years, depth swung across almost the whole scale while undertone held to a spread of about 5 degrees. One person, so a lead and not a claim, and still untested across devices.
- Every shortcut around the lighting failed at proper size. Colour-cast correction (classic and learned), exact shading removal, an eye-white reference and more frames were each tested and did not rescue a casual photo. That is why controlled capture is the route, and not just a preference.
Why the hurdle is high
- A casual selfie reads differently each time: a second session gives a different three-way answer about 40% of the time.
- The end game needs a match within about 1 to 2 delta-E. With the camera, light, session and exposure all fixed, our readings still vary by about 2.5 L*. Across sessions it is 11.25, and across 22 seconds of casual phone photos we saw a 37-point swing. We are roughly an order of magnitude away. Published work reaches about 1.5 delta-E only with a physical colour target in the frame.
- So the road to the end game is controlled capture with a colour reference in frame: a booth first, then a kit people hold up, and not a casual app. Cosplayers are the audience most willing to do that.
- pre-registered test
- product changed, not the bar
- 81 commits
Visit hrushimanju.uk Read the experiments and the walls we hit Volunteer to test