heyjuno.co

Juno's pricing is listed on its own page at heyjuno.co/pricing, and the site offers a "Try Juno free" option alongside a "Talk to us" contact path. The site does not publish specific price figures or plan details in the material available here, so the pricing page is the only reliable place to get current numbers. If you want to ask questions before committing, use the contact route rather than guessing at costs.

Finding pricing

The site's navigation includes a Pricing link pointing to https://www.heyjuno.co/pricing. That page is where plan structure and current prices should be confirmed. Because the available site material does not state amounts, billing terms, or what each tier includes, treat anything beyond "a pricing page exists" as unverified until you open it.

What to check on the pricing page

• Plan tiers and what each covers — how many studies, interviews, or participants are included.
• Trial terms — the site advertises trying Juno free, but the length and limits of that trial are not described in the available material.
• Participant and incentive costs — Juno interviews real people, and the site references panel ethics, incentives, and consent. Whether incentives are bundled into pricing or billed separately is not stated, so confirm this directly.

Trying Juno

The homepage presents two entry points: "Try Juno free" and "Talk to us."

1. Self-serve trial — choose "Try Juno free" if you want to see the workflow yourself. Based on how the product is described, you would start by writing a plain-language brief; Juno then designs the study, runs adaptive interviews, and returns findings with inspectable evidence (quotes and transcripts).
2. Talk to us — use this if you have questions about fit, pricing, or how studies are scoped before committing. It's the safer path for teams that need budget approval first.

A concrete way to test it

A realistic first trial is a small decision you already face, such as: "Why are customers switching to a competitor?" or "What would people in a given age range pay for this product?" These are the kinds of questions the site shows Juno handling. Write the brief, let Juno propose who to speak to and what to test, then review the returned quotes and transcripts yourself — the site explicitly frames researchers as the ones who check the evidence.

Before you commit

• Confirm pricing on the page itself — no figures are available in the source material, so don't rely on secondhand estimates.
• Clarify trial limits — "free" is advertised, but scope and duration aren't specified here.
• Ask about participant sourcing and incentives — relevant if your study needs specific audiences (e.g., recently cancelled members, as in the site's switching-friction example).
• Check the standards pages — the site links to Methodology, Competencies, and Safety sections covering privacy, redaction, and participant wellbeing; useful if your organization requires research governance review.

In short: go to heyjuno.co/pricing for costs, use "Try Juno free" to run a small test study, and use "Talk to us" for anything the pricing page doesn't answer.

Juno is an AI researcher for qualitative research. You give it a plain-language brief, and it designs the study, runs adaptive interviews with real people, and returns synthesized findings with evidence you can inspect. It fits teams that need customer "why" answers — agencies, brand teams, institutions, and researchers — without standing up a full research operation. Whether it fits you depends on how much of the interview and analysis work you want delegated versus done by hand.

How the workflow runs

Juno's own description breaks the product into three stages, and the interface shown on the site follows the same sequence:

1. Brief. You state what you need to learn in ordinary language. Juno works out who to speak to, what needs testing, and how to get a usable answer. In the site's example, it asks two scoping questions first — what the study will inform, and which participants to recruit — then drafts the study plan.
2. Interview. Juno runs adaptive qualitative interviews with real people, adjusting follow-ups as the conversation develops.
3. Reveal. It synthesizes findings and exposes the underlying evidence, so you can check quotes and transcripts rather than take a summary on faith.

The example study on the site ("Switching Friction Study") shows the brief stage in practice: Juno proposes a primary focus, a deep-exploration question, and a recency check, each with a short description and a character limit, and names the participant group (members who started a switch flow and abandoned it, including recently cancelled members).

What you get to inspect

The site emphasizes "research judgment, built in" and publishes standards for methodology and competencies, plus policies on safety (privacy, redaction, participant wellbeing) and participants (panel ethics, incentives, consent). For a researcher, the practical value is that findings come with evidence attached — the site explicitly invites researchers to "check the quotes and transcripts yourself" after Juno works through the interviews.

Who it is for

The site also lists example questions Juno is meant to answer: why customers switch to a competitor, what people in an age range would pay for a product, unmet needs in a category, whether to launch in a market, whether a concept drives purchase intent, and how a group makes decisions in practice.

How to decide if it fits

• Choose Juno if your bottleneck is running and synthesizing qualitative interviews at speed, and you want a first pass you can audit against transcripts.
• Keep human-led research if your study depends on interviewer judgment in sensitive contexts, or if your stakeholders won't accept AI-conducted interviews regardless of evidence quality.
• Check before committing: the site links to a Pricing page and offers "Try Juno free," but the supplied material doesn't state prices, plan limits, or what the free trial includes. Confirm those on the pricing page, and confirm consent and data-handling terms against your own compliance requirements.

A reasonable first test: pick one narrow, decision-relevant question — for example, why recently cancelled members abandon the switch flow — brief Juno on it, and check whether the returned evidence is specific enough to act on.

Juno is an AI researcher for qualitative research: you brief it in plain language, it designs the study, interviews real people, and returns findings with inspectable evidence. It fits teams that need customer understanding but don't run a full research operation, and it also fits researchers who want to review quotes and transcripts themselves. The clearest way to judge fit is to match your team type and question type against what the site shows Juno doing.

Who Juno is built for

The site names four audiences, each with a distinct job to be done:

Two fit signals follow from this. If your team has no dedicated research function but has recurring questions about customers, members, or constituents, Juno is positioned for that gap. If you are a researcher, the value is throughput with verification: Juno runs the interviews, and you audit the underlying evidence rather than accepting a summary.

Research questions Juno is designed to answer

The site frames Juno around understanding "what they really think and feel" and lists example questions that map to common decisions:

• Switching and churn: Why are customers switching to a competitor? The sample study on the site, "Switching Friction Study," explores where a switch flow loses people and why, focused on members who started the flow and abandoned it.
• Pricing: What would people between age X and age Y pay for a product?
• Category and unmet needs: What are the unmet needs in a space or category?
• Market entry: Should we launch a product in a market?
• Concept validation: Will a concept make people want to buy? The homepage headline is "Juno is an AI researcher ready to validate creative."
• Decision processes: How does a group make decisions about a category in practice?

These are qualitative "why" questions, not quantitative sizing. If you need statistically representative numbers, that is a different instrument; Juno's output is themes and quotes you can inspect.

How a study runs, from brief to findings

The workflow shown on the site has four stages: Brief → Align → Rehearse → Collect.

1. Brief. You describe what you need to learn in plain language. Juno works out who to speak to, what needs testing, and how to get a usable answer. In the sample, it asks two shaping questions first: what the study will inform (e.g., reduce drop-off vs. decide what to redesign) and who to talk to (abandoners, switchers, or both).
2. Align. Juno drafts the study plan. In the sample brief it produces exploration areas with coverage levels, such as mapping friction across the switch flow (deep exploration), a recency check, and identifying what would make people complete the switch (moderate coverage), plus a defined participant group.
3. Rehearse. Run through the interview design before fielding.
4. Collect. Juno runs adaptive qualitative interviews with real people, then synthesises findings and exposes the evidence behind them.

The interface also shows studies in states like Live, Paused, and Closed, so you can manage multiple studies at once.

What to check before committing

• Evidence inspection. The core promise is "evidence you can inspect." Confirm that quotes and transcripts are available to you, especially if you are a researcher who needs to verify.
• Methodology and standards. The site separates Standards (methodology, competencies) from Safety (privacy, redaction, participant wellbeing) and Participants (panel ethics, incentives, consent). Read these if your institution has compliance requirements around research with patients, students, or residents.
• Pricing and access. The site links to a pricing page and offers "Try Juno free," but the provided material does not state prices or what the free trial includes. Check the pricing page directly rather than assuming terms.
• Question fit. If your question is "why" or "how," Juno's design fits. If it is "how many" or "what share," plan a quantitative method alongside it.

The practical test: take one live decision you face, such as a pricing change or a concept launch, and check whether the question list above matches it. If it does, the next step is the pricing page and a trial study.

Juno keeps qualitative work inspectable by pairing a published methodology with visible evidence: it designs studies from a plain-language brief, runs adaptive interviews with real people, then synthesises findings while exposing the quotes and transcripts behind them. That combination — stated standards plus raw material you can check — is what makes its output reviewable rather than a black-box summary. It suits teams that need directional customer understanding quickly but still want to audit the reasoning; it is not a substitute for a researcher's judgment on high-stakes decisions.

The methodology layer

Juno's site separates what it does from how it holds itself to a standard. Two pages carry that weight:

• Methodology — described as "how Juno structures rigorous qualitative research."
• Competencies — "detailed competency standards Juno applies."

The practical implication is that study design is not improvised per session. When you brief Juno, it works out who to speak to, what needs testing, and how to reach a usable answer — the site frames this as "research judgment, built in." The visible workflow runs Brief → Align → Rehearse → Collect, so the study shape is settled and reviewed before any interviews happen.

A concrete example from the site: a team asks why members drop at the switch step. Juno narrows the setup with two questions — what the study will inform (reduce drop-off vs. decide what to redesign) and who to talk to (abandoners, switchers, or both). Once the user picks "decide what to redesign — abandoners," Juno drafts the brief with explicit coverage levels: deep exploration of friction in the switch flow, a recency check on who qualifies, and moderate coverage of what would make them complete the switch. Those labels tell you, before fieldwork, how much weight each question will carry.

Evidence you can inspect

The synthesis step is where trust is usually lost in AI research tools, so this is the part to test. Juno's stated output is "the why — with evidence you can inspect," and the site describes the reveal stage as synthesising findings and exposing evidence. For researchers specifically, the pitch is that Juno works through the interviews and then you check the quotes and transcripts yourself.

In practice, that means treating any Juno summary as a claim set to be verified:

1. Open the findings and identify each theme.
2. Trace the theme back to the supporting quotes.
3. Spot-check the transcript passages those quotes come from.
4. Confirm the participants match the intended segment — e.g., that "abandoners" really started the switch flow and did not complete it.

If a theme cannot be traced to a quote from a qualifying participant, treat it as a hypothesis, not a finding.

Safety, privacy, and participant wellbeing

Juno lists Safety as a standing topic covering "privacy, redaction and participant wellbeing." The inclusion of redaction matters for anyone handling sensitive material: it signals that personal or identifying details are meant to be stripped before content reaches the synthesis layer. The site does not publish the mechanics of how redaction is performed, so if your data is regulated, confirm the specifics with Juno directly rather than assuming.

Panel ethics, incentives, and consent

A separate Participants standard covers "panel ethics, incentives and consent." This is the part that determines whether the "real people" Juno interviews were recruited and treated properly — consent obtained, incentives handled fairly, panel practices defensible. Because Juno runs the recruitment itself, these are questions to raise with the vendor if your organisation has ethics review or procurement requirements; the site names the standard but does not detail the process.

How to judge fitness for your case

The pattern across all of these: Juno gives you the structure and the raw evidence, but the judgment about whether a finding is strong enough to act on stays with you. Teams that plan to inspect quotes and transcripts — as the site invites researchers to do — will get the most reliable use out of it.

Juno (heyjuno.co) runs a qualitative study in four stages — Brief, Align, Rehearse, Collect — then synthesizes what it heard into findings backed by quotes and transcripts you can inspect. You start by describing what you need to learn in plain language; Juno works out who to speak to, what to test, and how to get a usable answer. This fits teams that need customer "why" quickly — agencies answering client questions, brand teams checking reactions before changing a product, price, campaign, or range, institutions understanding residents, members, students, or patients, and researchers who want interviews worked through but still want to verify the evidence themselves.

Stage 1: Brief — Juno designs the study

You give Juno a plain-language brief. It then shapes the study design: the audience, the focus areas, and the depth of coverage for each.

The site's own example shows how this works. A brief about members dropping at the switch step prompts Juno to ask two setup questions:

1. What will this inform? Reduce drop-off, or decide what to redesign?
2. Who should we talk to? Abandoners, switchers, or both?

After you answer ("decide what to redesign — abandoners"), Juno drafts the study scope. In the example, that becomes three exploration areas with different coverage levels:

What you do: write the brief and answer Juno's clarifying questions. What you get: a structured study design you can review before anything runs.

Stage 2: Align — confirm the design before interviews

The workflow's second step is Align. This is where the study design is settled — audience, focus, and coverage — before Juno talks to anyone. Treat this as your checkpoint: if the audience or the questions are wrong here, the findings will be too. The site's example brief shows the kind of precision to aim for, naming a specific group ("members who started the switch flow and abandoned it, including recently cancelled members") rather than a vague segment.

Stage 3: Rehearse — test the interview before it counts

Rehearse comes before Collect, which tells you the interview is practiced or piloted before real participants are involved. Use this stage to check that the questions land and the flow makes sense. The site doesn't detail exactly what happens in Rehearse, so verify the mechanics in the product itself — but the sequence makes the intent clear: don't spend real interviews on an untested script.

Stage 4: Collect — adaptive interviews with real people

Juno runs adaptive qualitative interviews with real people — the conversation follows what participants say rather than sticking to a fixed script. The site's framing is that Juno "interviews real people to understand what they really think and feel," and the example session shows live studies in progress (for instance, an electric vehicle buyers study and an insurance buyers study).

Two things to know before you rely on this stage:

• Participants come through a panel. The site lists a standards section covering "Panel ethics, incentives and consent," so recruitment, consent, and incentives are handled within Juno's process. Check the current panel terms on the site if your study has specific recruitment needs.
• Safety and privacy are built in. Juno's standards cover "Privacy, redaction and participant wellbeing." If your topic is sensitive, confirm how redaction applies to your transcripts.

Reveal — findings with evidence you can check

After collection, Juno synthesizes the interviews and exposes the evidence: quotes and transcripts you can inspect yourself. This is the key difference from a summary-only tool — the output is designed to be audited, not just read. The site positions this for researchers in particular: "Let Juno work through the interviews, then check the quotes and transcripts yourself."

How to verify findings: open the quotes behind each theme and confirm they match the transcripts. If a theme feels thin, check how many participants actually said it rather than trusting the synthesis alone.

What Juno is good for — and where to check first

The site frames Juno around concrete questions: why customers switch to a competitor, what people in an age range would pay for a product, unmet needs in a category, whether to launch in a market, whether a concept makes people want to buy, and how a group makes decisions in practice. That list is a good test of fit — if your question looks like one of these, the workflow maps cleanly onto it.

Before committing, confirm three things on the site: pricing (there's a Pricing page and a "Try Juno free" option, but the terms aren't specified here), panel details for your target audience, and how Rehearse works in practice. The workflow is documented at a high level; the operational specifics are best checked directly in the product.