Opening Statement
You're shipping faster than ever.
Your research can't keep up.
Feature · Research Intelligence · 2025
AI has compressed the build cycle from months to days. Copilots write the code. Models generate the designs. The bottleneck has moved — and it has landed squarely on understanding what to build in the first place.
Understanding is the research platform built for this new velocity. When you can ship in a week, you need insight in a day. It runs your qualitative studies while you run your product.
The Problem
The AI revolution did not slow product development down. It did the opposite. Teams that once shipped quarterly now ship weekly. Code that took a sprint takes an afternoon. The entire build cycle has been compressed by an order of magnitude — and yet the research cycle has not moved at all. Recruiting still takes weeks. Synthesis still requires analysts. The gap between shipping velocity and understanding velocity is now a canyon.
The result is a dangerous asymmetry: teams that can build anything, faster than ever, but still have no rigorous way to know what they should build. Dashboards proliferate. Customer calls dwindle. The product accretes features at dizzying speed — features that serve the data rather than the person behind it.
Understanding is built from a single conviction: that the conversational interview — the most direct method for learning what people actually struggle with, value, and desire — should be as scalable and frictionless as running an A/B test.
"AI gave us the ability to ship in days. Understanding gives us the confidence to know what's worth shipping."
Our AI interviewer conducts conversations with the depth and patience of a seasoned researcher. It listens, follows threads, probes assumptions, and knows when to sit in silence rather than rush past a hesitation. It does not fatigue. It does not have a preferred hypothesis. It does not accidentally telegraph the answer it is looking for.
What it produces is a corpus of rich qualitative evidence, automatically structured into the frameworks that product teams already use to reason about their work.
Methodological Foundations
Frameworks built into the instrument,
not bolted on afterward.
Qualitative research is only as useful as the theory of knowledge it operates within. Understanding is designed around three frameworks that represent the state of the art in product discovery methodology.
Jobs to Be Done
Users do not buy products. They hire them to accomplish something. JTBD theory restructures your inquiry around the functional, emotional, and social progress people seek. Understanding's interview protocol surfaces the job context, the struggle moment, and the metrics by which participants measure success.
Artifacts Generated
Job Map · Switch Interview Analysis
Empathy-First Discovery
The five-stage Stanford model begins where most product teams end — with deep, non-judgmental empathy for the human experience. Our AI interviewer is tuned for observation and listening at this stage: no leading questions, no solution-probing, only the patient excavation of context and constraint.
Artifacts Generated
Empathy Map · Persona Synthesis
Satisfaction Architecture
Not all features are created equal. The Kano model distinguishes between what delights, what satisfies, what is merely expected, and what actively repels. Embedded Kano questioning throughout the interview protocol produces a satisfaction grid that makes prioritisation decisions empirically defensible.
Artifacts Generated
Kano Satisfaction Grid
The Process
From question
to insight in
three acts.
Your team ships in days. Your research should deliver in hours. Understanding collapses the research cycle into a disciplined, repeatable workflow that matches the velocity AI has brought to everything else.
"Configure once. The AI holds the thread across every conversation."
Configure Your Study
Define the research question. Select your framework — JTBD, Design Thinking, or Kano — and configure the study parameters: target participant profile, interview depth, topic boundaries, and synthesis preferences. Understanding's study builder translates your research intent into a precisely calibrated interview protocol.
~30-60 minParticipants Join. AI Interviews.
Share a link. Participants arrive at understanding.you and are guided through a conversational interview by the AI — an exchange that adapts in real time to what they say. As a researcher, you monitor sessions live, watching transcripts develop, flagging moments for closer review. The platform runs twenty interviews simultaneously without breaking a sweat.
Concurrent & asyncSynthesis Arrives
When your target sample is reached, Understanding synthesises the corpus automatically. Job Maps trace the sequence of progress participants seek. Empathy Maps capture what they think, feel, say, and do. Kano Satisfaction Grids rank features by their capacity to delight or disappoint. Each artifact is editable, exportable, and team-shareable.
Automated on completionResearch Artifacts
Evidence that speaks
the language of
product decisions.
Synthesis is where research either earns its place in the room or gets left in a folder. Understanding produces artifacts that map directly to the frameworks your team already uses — so insights enter workflows rather than slide decks.
Every artifact is a living document: editable, commentable, and built to be challenged by the team. Research is not a handoff. It is the beginning of a conversation — one that the evidence should sustain long after the study closes.
Job Map
An ordered sequence of the steps participants take to accomplish their core job — from definition through execution to resolution. Pinpoints where progress stalls and where competitors leave gaps.
Empathy Map
A four-quadrant synthesis of participant consciousness: what they think, feel, say aloud, and do in practice. The divergence between internal experience and external expression is where product insight lives.
Kano Satisfaction Grid
Features and attributes plotted against their capacity to satisfy or disappoint — distinguishing delighters from basics from performance attributes. Makes prioritisation an empirical rather than political exercise.
Switch Interview Analysis
A structured breakdown of the switching moment — the timeline of events, forces, and emotional states that led a participant to abandon one solution and seek another.
Opportunity Map
A combined view of the most important, least satisfied jobs — the intersection of high importance and low satisfaction that defines genuine market opportunity.
Research Transcript Archive
The complete, searchable record of every interview — timestamped, speaker-attributed, and tagged by theme. The primary source that all synthesis artifacts derive from.
A Considered View
On the ethics
of the
artificial listener.
The question we are asked most often is not whether AI-led interviews work. The answer to that is increasingly settled. The question is whether they are right.
We think about this carefully. Participants on understanding.you are always informed they are speaking with an AI. There is no deception. The AI does not pretend to share experiences it does not have. It listens, reflects, and asks — which is what a good researcher does, without the politics that human researchers inevitably carry into a room.
There is a particular kind of honesty that people reserve for non-human listeners. The same phenomenon that makes diary studies so revealing. The absence of social performance. What participants tell Understanding's AI is often more candid than what they would say to a researcher who they know represents the company whose product they are criticising.
This is not a bug. It is, we believe, the point.
In Practice
"We ran our first JTBD study in a single afternoon. By the next morning, we had a Job Map that changed how we thought about the problem entirely."
Principal PM, Series B SaaS · Beta participant
Audience
Built for PMs
who take
discovery seriously.
Solo PM & Founder
You are the entire research function. Understanding gives you the ability to run rigorous qualitative studies without a research team — so you stop shipping on assumption.
PM at a Growing Startup
Your backlog is longer than your bandwidth. Understanding parallelises research across multiple studies simultaneously, so discovery keeps pace with development.
Senior PM & Research Lead
You know the frameworks. You have run the studies. Understanding removes the operational overhead so you can spend your time on interpretation and strategy, not scheduling and synthesis.
PM Platform & Research Ops
You are building the research capability for a team. Understanding provides a consistent, framework-driven methodology that scales across product lines without compromising rigour.
Early Access
Research at the
velocity of
modern product.
Understanding is in private beta. We are onboarding product teams deliberately — to learn from how they use it, not just to grow.
If you are a PM whose team now ships faster than you can validate, Understanding closes the gap. Join the waitlist. We will be in touch.
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