For decades the hard part of launching something new was building it. That's over. AI creates the app, makes the deck, ships the prototype. Building digital products got cheaper. What didn't get cheaper is knowing which problem deserves the next six months of your life. And the tools out there made that harder: general-purpose AIs agree with whatever you type, AI product builders build anything you ask and never ask why, while consultants charge six figures to tell you in September what was true in March.
Ironically, it has never been easier to build the wrong thing.
Ainna solves that. It gives you solid methods and tools to frame your idea and stress-test it, grades it against a published framework, and puts it to the people whose judgment you trust, until you know whether it's worth your next six months.
Built to grade, not to please. Ten dimensions, one letter, the reasoning in the open, and the one dimension holding the grade named. Ainna is not on your side. It's on the problem's side.
An Opportunity in Ainna · the header, the verdict, the risks, the assumptions, the recommendations
The journey to an opportunity
Unpack. Discover. Grade. Decide.
Every problem goes through the same four moves, so every opportunity that comes out is framed the same way, graded the same way, and comparable with the rest.
01 · Unpack
Name the problem, the need, the gap.
Bring a sentence. Ainna asks what a sharp advisor would ask: who it hurts, what it costs, why now. Then it pushes back on the weak answers until the problem holds on its own, before anyone proposes a solution. Personas, Market Outlook and Competitive Landscape fill in who it's for, how big it is and who else is there.
02 · Discover
Fill the solution space.
Brainstorming Mode develops the alternatives you hadn't considered, keeps the rest as options, and works with you to turn the promising ones into concepts worth grading. Your first idea is rarely the best one. This is how you find it.
03 · Grade
Get a grade, and the reason for it.
The Judge grades each concept across ten dimensions using a scoring model built on a published framework, shows the reasoning behind every score, and names the one thing holding it back. Reframe it to fix what it named, and grade it again. As many rounds as it takes, always free.
04 · Decide
Invite the people you trust, then decide.
Bring in advisors, domain experts, or the customers you're building for. Each assesses independently: they won't see the Judge's grade until they've given their own. Where they disagree, Ainna shows you the disagreement instead of averaging it away. Then pivot, park or take it forward: Pivot History keeps every turn, and Branded Documents and Themed Decks produce the pitch deck, PRD and one-pager.
Inside the brainstorm
Your first idea gets company.
Ask for as many ideas as you want against your framed problem. Every round brings fresh seeds for you and your team to judge, and Ainna learns from what you reject as much as from what you promote. Pick one and frame it as an opportunity, with the market and the competition mapped.
Every graded concept lands in your portfolio, ranked against the rest on the same ten dimensions: one venture's alternatives, or a whole team's quarter. What comes out: a framed opportunity, a grade with its reasoning, the personas, a market size you can defend, the competitive map, and the documents to carry it. Or a clear no, three weeks in, not three quarters.
But this is good news. Ask ten AIs about your idea and nine will congratulate you. Stanford measured it: production models affirm what a user wants to do 49% more often than a person would. The Judge grades the concept, shows its work, names the one dimension doing the damage, and tells you what would change it. A D is the most useful thing that can happen to an idea about to cost you six months.
Ten dimensions · the one holding the grade, “certainty of demand”
Problem Radar · the Index
Problems the world wants solved.
Ainna listens to public reporting, continually. Its Problem Radar picks out the problems worth solving, frames each to one standard, shows where each one came from, and keeps the record on the Index (24 entries across 1 edition), free to start solving. Every entry is Ainna's own framing; the problems you bring stay yours, private, and never appear here. The same Radar works in your context too, tuned to your market, or to your company's own agenda.
Media
Unverifiable AI answersReaders can't check the AI answer they were given
Use of AI assistants for news is rising while stated trust in them stays very low: people take answers from a source they openly doubt, because it is faster than the alternative. The gap is not ignorance; it is the absence of anything that lets a reader check an answer at the moment they receive it, without abandoning it and starting a separate search.
For whom
Anyone getting news through an assistant · publishers whose work is summarised without attribution · educators teaching source literacy
Invisible small-firm creditSmall firms can't prove a trading history lenders accept
Small firms are assessed on documents they were never required to produce. Audited accounts, filed returns and collateral registries are what credit models expect; a profitable shop with a phone, a supplier relationship and ten years of trading has none of them. The lender cannot see the business, so the business does not exist to the lender, and the money goes to whoever already had the paperwork.
For whom
Owner-managed and informal firms · community and development lenders · the suppliers already extending them credit informally
Grid connection backlogEnergy developers are blocked by paperwork, not engineering
The constraint on the energy transition moved from manufacturing to administration, and no tooling followed it. Projects sit in interconnection queues longer than they took to design, studies are redone by hand each time the queue ahead reshuffles, and developers cannot see where they stand or what would move them. Most of the capacity that enters the queue is eventually withdrawn, often after years of waiting.
For whom
Independent power producers · utility interconnection teams · the financiers whose models assume a connection date
No AI-exposure offrampWorkers can't move out of the roles AI reaches first
We can now say with some precision which occupations generative AI reaches first, how that varies by country, and that the exposure falls hardest on clerical and administrative work done mostly by women. What does not exist is the other half: a route from an exposed role into an adjacent one that uses the same accumulated judgment. Retraining is too often offered as courses unrelated to what the person already knows how to do.
For whom
Clerical, administrative and business support workers · employers holding the institutional knowledge in those roles · public employment services
A widening cyber-security gap between big and small firmsSmall firms can't scale their defences to match AI-powered attacks
AI has made cyber attacks cheap to run and easy to scale. Large firms can answer in kind: they have security teams, budgets and tools, and they can grow each as the threat grows. Small businesses cannot. Their systems are often set up and looked after by outside suppliers, their defences are seldom tested, and a break-in is often found by someone else. So the same change raises the risk for big and small firms alike but the defence only for the large, and the gap between big and small firms widens. What is missing is defence that scales the way attacks now do: priced for a small firm, and able to run without a security team.
For whom
Owners of small businesses without a security team · the IT and web suppliers that set up and look after their systems · customers whose data is taken in a break-in · the banks and insurers that carry the losses
Digital identity exclusionPeople without ID lose the services that moved online
Benefits, banking, health records and school places are moving to interfaces that begin by asking you to prove who you are online. Hundreds of millions of people cannot prove who they are at all, and billions more have no digital means of doing it, so each service added to the digital channel quietly removes itself from the people who most need it, while the statistics record improved efficiency.
For whom
People without foundational or digital ID · agencies moving services online · the frontline staff handling every exception by hand
Blind antibiotic prescribingDoctors prescribe antibiotics without knowing what works locally
Resistance is as much a data problem as a drug problem. Surveillance depends on cultures, and much of the world's prescribing happens where there is no microbiology laboratory within reach, so the clinician makes a reasonable guess, and what happens next is rarely recorded anywhere that would improve the next one. The map of what still works is drawn from the minority of cases that reach a lab.
For whom
Prescribers in primary and rural care · national AMR programmes · hospital pharmacy and stewardship teams
Unverifiable student workTeachers can't tell who learned and who prompted
Most institutions are writing or planning a policy about AI; few have changed what they actually measure. The essay, the problem set and the report were proxies for thinking that worked only while producing them was expensive. That assumption is gone. Detection tools are unreliable enough to risk accusing the wrong students, and much of what is graded no longer shows reliably what a student understands.
For whom
Teachers and lecturers redesigning assessment alone · students wrongly suspected · institutions whose credentials depend on the answer
Withdrawn home insuranceHomeowners lose insurance their mortgage still requires
Insurers are withdrawing from places where people still live and still owe money. The mortgage requires cover; the cover depends on a risk model that has stopped holding. Homeowners find out at renewal, with weeks to replace a policy that may not exist at any price, and often no accepted way to show an insurer the work they have done to make the building safer, because that evidence is rarely collected in a form an underwriter will accept.
For whom
Homeowners in high-risk areas · mortgage lenders and brokers · local authorities watching values move
A familiar voice or face no longer proves who's callingAI fakes now pass the voice and face checks people rely on
For generations a voice on the phone or a face on a video call was good enough proof of who was there. Banks built call-centre checks on it, companies approve payments on it, and families trust it when a relative asks for help. AI now copies voices and faces cheaply and well enough to pass, so the signal most people rely on has stopped being proof. Scammers pose as banks, officials and relatives, and victims move money believing the person is real. Checks that ask a person to judge whether a call is genuine keep failing, because that judgement is exactly what the fakes defeat. What is missing is a way to prove a real person is present that does not depend on how they look or sound.
For whom
People targeted by impersonation scams · families asked for money by someone posing as a relative · banks and payment firms checking customers by phone or video · companies that approve payments on calls
The same Radar runs in your context. What you see here is Problem Radar, free. Tune it to your market and it listens to the sectors, themes and geographies you set, landing every find in your portfolio, graded: that's the Team plan. Tune it to your company and it listens to your innovation agenda and to your own people: that's Enterprise. Both are private to you: nothing they find is ever published.
What the Radar finds, in your inbox.
Problems worth solving, when there are some worth sending. No product talk. Leave any time.
Who it's for
Founder, product team, or head of innovation?
Ainna adapts to each, with the right tools for the job: the market it watches, the agenda it grades against, and whose judgment sits on the Panel.
Founders
Your next big thing.
Use it hard for a season, then go build. Bring the problem that won't leave you alone. Ainna frames it, opens it wide and grades every concept before you spend a month on the wrong one. You leave with an opportunity that holds and a decision log from problem to MVP, so months later you can still say why the product is shaped this way. Or with the pivot found while it was still cheap.
Turn on the Market Radar and the team gets a standing feed of problems worth solving, in your market, shaped by what is actually happening out there. Brainstorm against them with Ainna and with each other, frame what holds into opportunities, and rank them on the same ten dimensions. Repeat, and the work stops evaporating: it compounds into your Innovation Space.
An evolving network of every problem, idea and judgment in the organisation, each linked to the others it touches, so nothing good is lost when the workshop ends. Ainna builds it as you work: your cloud, your brand, everyone invited, and a Radar tuned to your agenda. Problems surface from the Radar and from your people, and every one is graded to the same standard by the Judge and by your Panel. Decisions get faster, budget follows evidence, and the organisation starts innovating as one.
The human-in-the-loop principle puts a person at the end of the process, to monitor and approve what the machine decided. Our human-at-the-core thesis puts innovators at the centre of it: AI carries the volume and the speed; people bring the problem and the inspiration, and keep the judgment, the scrutiny and the decision. In Ainna, you shape the problem, the ideas and the agenda: Ainna asks what a sharp advisor would ask. You create the solution space: Ainna widens it. Your experts grade the concepts: blind to the Judge's score, with the same standing, disagreement shown and never averaged. And you decide. Ainna is your partner in the work, never the authority over it.
A panel you choose yourself, for the expertise they bring.
Verdict · two perspectives · reviewers invited
Documents and decks
Ready to pitch? Yes, you are.
Nothing gets built until the people around it agree, and agreement is won with documents that make the case when you're not in the room. Once your opportunity holds up, the hard part is already done, and Ainna writes the rest: the pitch deck in about a minute, the full PRD in minutes, not weeks. Every file is PowerPoint or Word, yours to edit, and can carry your logo.
Pitch deckThe case, the market and the ask
PRD deckWhat to build, for whom, and why
Social carouselsReady to post, for the idea and the problem
Samples made by Ainna for fictional concepts. IM-Water, IM-Health and IM-Talent are demo organisations (IM for Innovation Mode, the company behind Ainna), and the people named are invented.
Problem framingWhat's wrong, for whom, and why now
Problem framing deckThe problem, agreed before the pitch
Problem carouselRally your network around it
Brainstorm deckFor those who weren't in the room
One-pagerThe idea on a single page
Idea carouselYour idea, for LinkedIn or Instagram
PRDWhat to build and why, in full
PRD deckThe PRD, for the alignment meeting
PRD briefThe case, for the meeting that decides
Pitch deckThe story, from problem to ask
Made from your work, not around it.
Every document draws on what you have already done: the problem you framed, the market you sized, the competitive map, the Judge's reasoning. There is nothing to fill in, and where a piece of the work is missing, the document leaves it out rather than padding it. What comes out is something you can put your name on.
Assessing an opportunity is not a general-purpose task. It takes a position on what makes a problem worth solving and which evidence counts. Ainna is built on The Innovation Mode, a methodology published by Springer Nature in 2020 and rebuilt for the AI era in 2026, reflecting twenty-five years of designing products and innovation programmes. Every question Ainna asks, every grade it gives and every challenge it raises comes from that published framework, and you can go and read it.
PublishedTwo editions. Springer Nature, 2020; rewritten for the AI era, 2026.
TaughtOn the syllabus at top universities.
PractisedTwenty-five years of designing products and innovation programmes.
LiveMarket signals and reporting, listened to continually; 24 problems framed by the same method so far.
Ainna is the AI Innovation Agent: an AI product innovation platform that helps founders, product teams and innovation leaders find what's worth building. Bring a problem or a rough idea, your own or one from Problem Radar, and Ainna works it with you before anything is built: it frames the problem, opens the solution space, profiles the users, sizes the market, maps the competition, grades every concept on ten dimensions with the reasoning shown, and brings in the experts you trust. It keeps every pivot and produces the pitch deck, PRD and one-pager.
Founders use it to grade a concept before they commit six months to it; product managers to build the case for what to build next; heads of innovation for a steady flow of well-framed opportunities instead of a once-a-quarter scramble. Organisations use its sibling product, Ainna Enterprise, the Opportunity Discovery System. Ainna is built by Innovation Mode Limited in Dublin, on The Innovation Mode methodology (Springer Nature).
How is Ainna different from ChatGPT or Claude?
A general-purpose assistant gives you ideas and prose, a small part of the work, then leaves you to be the strategist, the analyst and the reviewer. Ask it to size a market and you get plausible numbers with no method; ask for a competitive map and you get a list, not an assessment. And it is built to be agreeable: in a study published in Science in 2026, researchers at Stanford and Carnegie Mellon found that 11 leading AI models, including ChatGPT, Claude, Gemini and DeepSeek, affirmed users' actions 49% more often than people did (Cheng et al., Science, 2026).
Ainna runs the whole method. It frames the problem, sizes the market against a defensible model, grades the concept on a published framework with the reasoning shown, names the one dimension holding the grade down, brings the people you trust in to challenge the result, and hands you the pitch deck, PRD and one-pager, from one body of work, in minutes. It is not on your side; it is on the problem's side.
Can I bring my own problem, or do I pick one from the Radar?
Either. Type your own problem into the field at the top of this page, in a sentence or two, and Ainna starts from your words. What you bring is private to you and is never published. No idea yet? That's a good place to start: the strongest opportunities often begin as a problem with no solution attached.
Or pick one from Problem Radar. Ainna listens to public reporting, continually, and frames the problems worth solving to one standard; a few are framed by Ainna's innovation team from conditions most people will recognise. Every entry says which, and news-backed entries link the reporting they were drawn from. The Index is Ainna's own work: nothing on it comes from what users bring.
How do I turn a rough idea into a validated opportunity?
Bring a hunch, a problem or a half-formed concept, and Ainna does the structured work: it frames the problem, opens the solution space, sizes the market, maps the competition, profiles the personas and puts the concept before the Judge, which returns a grade across ten dimensions with the reasoning shown, the one thing holding it back named, and the recommended next move. What took an innovation team weeks takes minutes.
An idea is worth building when it solves an important problem for a real, reachable user, in a way you can deliver, with enough demand and strategic fit to matter, and the only way to know is to assess it honestly before you commit. The grade isn't the finish line: the experts you invite assess the same opportunity independently, you iterate as your thinking sharpens, and what survives becomes a defensible case. What doesn't fails here, where failure is cheap.
How does the Judge grade, and will it tell me my idea is bad?
Yes, if it is, with the reasoning, and the one thing that would change the grade. Every concept is graded on ten dimensions across two lenses, one for the problem and one for the solution, each scored with its justification, so the letter always comes with the reasoning behind it. The dimension holding the grade back is named, and so are the risks and the silent assumptions the concept rests on. Alongside, holder fit rates the opportunity against your Innovation Agenda: whether it matches the focus you have set and the assets you actually hold.
The model evolved from the assessment model published in The Innovation Mode, which grades on nine dimensions; the one in Ainna goes further, at ten across two lenses, and it is configurable, because what matters depends on the decision you're making. The letter follows from the scores. The verdict (proceed, reframe or stop) is a judgment, and you can appeal it with new evidence. Appeals are free, always.
How do the experts I trust take part?
On the Panel. Co-founders, advisors, specialists, even target customers assess the same opportunity independently: they don't see the Judge's grade until they have given their own. Where their judgment and the Judge's diverge, Ainna shows you the disagreement instead of averaging it away.
It is the principle the product is built on: not human-in-the-loop, where a person checks what the machine decided, but human-at-the-core, where people do the work and the AI makes them better at it. The AI is the analyst and the honest second opinion; you and your experts decide. The Panel comes with Pro, Team and Enterprise.
What documents does Ainna produce, and do I need a template?
No template needed: Ainna writes the documents from the work you've already done. Once an opportunity is framed and graded, it produces the pitch deck, a visual Product Requirements Document (the problem and goals, target personas and user journeys, requirements, and an implementation outline) and the one-pager, in your branding, with contextual visuals rather than a blank outline to fill in.
All three come from one body of work, so the story stays consistent across every format, and everything exports as fully editable PPTX and DOCX files that are yours to keep. Bring your own judgment to the numbers and claims, and it's ready for stakeholders.
What is The Innovation Mode methodology?
A methodology for running innovation as a disciplined, repeatable function: from spotting problems worth solving, to assessing the opportunities with evidence, to building the ones that earn it. It was published by Springer Nature in 2020 and rewritten for the AI era in 2026, and it is the framework Ainna is built on rather than a thin layer over a language model: a structured way to frame problems, a multi-dimension model for grading opportunities, the human-at-the-core principle, and a portfolio view where the strongest ideas compete on consistent criteria.
At its centre is the Innovation Graph: an evolving network of problems, ideas, assessments and market intelligence in which every item is linked to the others it touches. AI maintains the links (one idea extends another, two overlap, compete or complement each other), so an idea from a January brainstorm can surface again in a March hackathon. It is how innovation stops being episodic and starts accumulating.
What is an Innovation Agenda, and do I need one to start?
An Innovation Agenda is a clearly stated focus for innovation, linked to your strategy: the themes you will invest in, the outcomes you are after, and the targets that count. It is the reference every idea is measured against, which is what makes two opportunities comparable rather than two opinions.
You don't need one to start: bring a single problem and Ainna frames and grades it straight away. The agenda becomes useful once more than one idea is in play, because holder fit scores each opportunity against the focus you have set and the assets you hold. Ainna challenges and sharpens the agenda the way it challenges an idea, and it is versioned, so you can see which version an assessment was graded against.
Can the Radar listen for my market, or my company?
Yes: it's one instrument at three scopes. Problem Radar is what you see on this page, free. The Market Radar, in the Team plan, is tuned to the sectors, themes and geographies you set, and lands what it finds in your portfolio, graded. The Corporate Radar, in Enterprise, is tuned to your innovation agenda and fed by your own people as well as the news. Both are private to you; nothing from them is ever published.
How does pricing work, and can I try it for free?
Start on Starter, with a real problem of your own: the full strategic conversation and a real grade from the Judge with its reasoning, with no credit card and no time limit. It isn't a demo on sample data. Pro adds the Panel for your own experts and full document generation, for an individual; Team adds seats and a shared workspace, an Innovation Agenda every idea is graded against, the Market Radar tuned to your market and a ranked portfolio. Paid plans start at $99 per month, annual billing saves up to 25%, and there are no hidden fees and no lock-in; larger organisations move to Enterprise. Everything you created on Starter is still there when you upgrade.
An Opportunity is one problem taken all the way through: framed, opened, graded and documented. A Brainstorm is one round of opening the solution space against a framed problem. Your plan sets how many of each you can use, the paid allocations reset monthly, and refining or re-grading an Opportunity you've started never uses another. And with Ainna Fellows, bringing people into the work pays both ways: more Opportunities on your side, a head start on theirs; your invite link appears after sign-in.
Who owns what Ainna generates, and is my data used to train AI?
You do. The ideas, strategies, analysis and substance in everything Ainna generates belong to you, to use for your own business: investor pitches, internal alignment, engineering handoff. Downloaded files are yours to keep, whatever happens to your plan. The one boundary is the methodology itself: the frameworks and document structures embedded in the outputs remain The Innovation Mode's, so they can't be repackaged or resold as templates, and agencies producing client deliverables need a commercial licence.
Your content is never used to train AI models, never shared with other users, never sold, and never published. It is seen only by you, by your teammates when you make an idea discoverable or ask for their assessment, and by the people you invite to your Panel. Your account is hosted in EU data centres under GDPR. Generated documents aren't stored on our servers: each is rendered when you download it and can be regenerated any time the Opportunity exists. Your work stays in your account until you delete it; a free account with no login for 12 months is deleted after 30 days' notice. Export anytime, delete any idea in one click, close your account whenever you choose. Delete means delete.
