About
Built for the seam between your message and the machine.
Juncture is the only pharma content intelligence platform that joins a pre-MLR asset check, an approved-content system of record, and AI answer monitoring, all measured against the same approved label. Built by QueryNow, Inc., a team that builds AI products for regulated industries, our mission is to keep a pharma message intact from the approved label to the answer a machine gives, at the moment HCPs are changing how they ask.
01/The name
A juncture is a join and a moment.
From the Latin jungere, to join: the same root that gives us junction and joint. A juncture is the point where two things meet, and the moment at which things turn. Both senses describe what we do.
The join
The seam nobody owns.
Between the content pharma approves and the answer a machine gives, there is a seam. Medical owns the label. Commercial owns the campaign. No one team owns the space where the two pull apart. That unowned seam is why we built this company.
The moment
Pharma is at a juncture.
HCPs are moving from search to AI assistants. The approved message and the machine answer are drifting apart, quietly, brand by brand. This is the turning point. The decisions a brand makes now set how it is described for years.
Pharma’s message is at a juncture.
02/What it does
What Juncture does, on an asset.
Here is the pre-check on a fictional asset: it holds the asset to the label before MLR, citing the clause behind every verdict. The same label later sets the baseline Answer Monitor measures the machine answer against.
Lower readings in 8 weeks.
For adults with moderate hypertension. Proven in two phase III trials.
- Indication claim presentClaimLabel 1.1
- Efficacy figure matches dataClaimLabel 14.2
- Approved visual verifiedImageAsset 4471
- Fair balance includedRuleLabel 6.1
- Off-label use impliedOff-labelLabel 1.1
- Safety statement intactRuleLabel 5.3
Held to the label
Checked before MLR.
The pre-check reads the asset and holds every claim, figure and visual to the label, citing the clause behind each verdict. It catches an off-label use before review, not after it ships.
Backs the reviewer
It does not replace MLR.
The accountable decision stays with the human reviewer. The pre-check hands them a checked asset and a clear shortlist, with the technical controls and a sign-off behind it.
End to end
It does not stop here.
The same label that clears the asset also sets the baseline Answer Monitor measures the machine answer against. One source of truth, joined across the seam.
03/The mission
Keep the message intact, from the label to the answer.
Pharma spends years getting a message right and approved. Then a machine paraphrases it to a clinician in seconds, and the careful work can come out wrong: a dropped indication, an unverified claim, an off-label reading. Juncture exists to close that gap. We keep content creation, review, measurement and AI monitoring anchored to the one message you approved: hold the asset to the label before it ships, trace where the message is used, and watch how the machine answers after launch. One loop, one source of truth, one message that stays intact end to end.
From managing content assets to governing message execution.
04/The value, made tangible
Reuse is the value, not just claims checked.
We hold a strong conviction: the clearest value of a pre-check is showing how much of an asset is reused from content you already approved. It makes the work concrete, alongside the claim and rule checks, so reviewers spend their time on what changed.
approved content
- 3 blocksExact match to an approved module
- 1 blockLight edit of approved wording
- 1 blockHeavy edit, matched by meaning to its module: review the delta
- 1 blockNew copy, routed for a fresh claim check
Matching is semantic, so a paraphrased or abbreviated claim still finds its approved module. Only the genuinely new copy needs a fresh claim check.
- Indication: adults with moderate hypertension.Exact matchMatchedMOD-INDICATION-02
- Lower readings in 8 weeks, shown in two phase III trials.Exact matchMatchedMOD-EFFICACY-05
- Once-daily dosing, taken with or without food.Light editMatchedMOD-DOSING-01
- Readings drop in 8 wks vs placebo, phase III.Heavy editMatchedMOD-EFFICACY-05 · 89% similar
- Important safety information and fair balance.Exact matchMatchedMOD-SAFETY-03
- New campaign headline written for this asset.NewStatusNo approved match
The reuse breakdown, the stringency dial and the audit ledger are the mechanics of the pre-check. See how the pre-check works.
05/MLR review ready
Built to back the reviewer, not replace them.
The pre-check hands MLR a checked asset and a clear shortlist. The accountable decision stays with the human reviewer. Juncture provides the technical controls for 21 CFR Part 11: a time-stamped, tamper-evident audit trail, e-signature sign-off, and role-based access control. You validate it for Part 11 use under your own SOPs.
- 09:14Juncture pre-checkVerified claims against label, 1 item flagged
- 09:31A. Okafor (Medical)Assigned VAR-DTC-08 to MLR review
- 10:02R. Lindqvist (Reg.)Resolved off-label flag, edit accepted
- 10:40A. Okafor (Medical)E-signature sign-off applied
A. Okafor
Approved on behalf of Medical review
2026-06-02 · 10:40 UTC
The reviewer signs off. The pre-check backs the decision, it does not make it.
06/Why QueryNow can win this category
Built by a team that ships AI under audit.
Juncture is not a side project. It is built by QueryNow, Inc., a team that builds AI products for regulated industries, with focus and delivery experience in pharma content compliance, AI answer monitoring and enterprise AI delivery. The credibility is in the work and the problem expertise, not in a wall of logos.
What we build
AI products for regulated industries.
QueryNow builds AI software for teams that work under audit. The discipline that takes, plain interfaces, traceable outputs and controls that hold up to scrutiny, is the same discipline Juncture is built on.
Where we focus
Pharma content compliance and AI answer monitoring.
Our focus is the pharma content problem end to end: holding a marketing asset to the approved label before MLR, and watching how AI answers about the brand after it ships. Two jobs pharma has always run apart, joined against one source of truth.
How we ship
Enterprise AI, delivered under review.
We have delivered enterprise AI into regulated, review-heavy settings where a verdict without a reference is worthless. That is why every Juncture result cites the clause behind it and stays defensible when a reviewer, or an auditor, asks why.
Why this team can win this category
Pharma content intelligence is a new category, and the case for Juncture rests on two things: the problem and the approach. The problem is one we work in directly, the unowned seam between the content a brand approves and the answer a machine gives. The approach is to refuse to solve only one side of it. MLR workflow tools stop when content is approved. AI answer visibility tools start after launch and never touch the review. Juncture is the only pharma content intelligence platform built to connect pre-MLR asset checks with AI answer monitoring, both measured against the same approved label. A team that already builds defensible AI for regulated work, and that holds both sides to one source of truth, is built to own the seam neither side covers.
The controls a regulated team needs are built in: Juncture provides the technical controls that support 21 CFR Part 11, a time-stamped, tamper-evident audit trail, e-signature sign-off, and role-based access control. You validate it for Part 11 use under your own SOPs. See how the platform is built.
06/How we build
Convictions, not features.
A small set of beliefs runs through everything Juncture does. They are why the product reads the way it does, and why a reviewer can trust it.
The label is the source of truth.
Every check and every measurement resolves to the approved label. We do not invent a standard. We hold the work to the one a brand already approved.
What you approve sets the baseline.
The content a brand approves is the baseline the machine answer is measured against. The pre-check and the monitor are one continuous thing, not two tools.
Cite the clause, every time.
A verdict without a reference is an opinion. Each result points to the exact label clause behind it, so a reviewer can trust it in seconds.
Built for the people who sign off.
Medical, regulatory and commercial reviewers carry the risk. The product is plain, fast and defensible because their names are on the approval.
07/The company
Who builds Juncture.
Juncture is the only pharma content intelligence platform that joins a pre-MLR asset check, an approved-content system of record, and AI answer monitoring, all measured against the same approved label. It is built by QueryNow, Inc., a team that builds AI products for regulated industries.
09/About Juncture
Questions about the company
- What does the name Juncture mean?
- A juncture is the point where two things join, from the Latin jungere, the root of junction and joint. It also means a decisive moment, as in "at this juncture." Both senses fit: Juncture sits at the seam where the approved message meets the machine answer, at the moment HCPs are moving from search to AI assistants.
- Who builds Juncture?
- Juncture is built by QueryNow, Inc., a team that builds AI products for regulated industries. Juncture is its pharma content intelligence platform: the only pharma content intelligence platform that joins a pre-MLR asset check, an approved-content system of record, and AI answer monitoring, all measured against the same approved label.
- What is the mission?
- To keep a pharma message intact from the approved label to the answer a machine gives. Juncture pre-checks an asset against the label before it ships, then watches how the machine answers about the brand after it does, with the technical controls a regulated team needs behind every decision. The careful, approved message stays intact end to end.
- Why does this matter now?
- HCPs are shifting from search engines to AI assistants. When a machine paraphrases an approved message, it can drop an indication, surface an unverified claim, or read off-label. The decisions a brand makes at this juncture set how it is described for years.
- Why should I trust a newer company with regulated work?
- The right test is not company age, it is whether the work holds up under review. QueryNow builds AI products for regulated industries, with focus and delivery experience in pharma content compliance, AI answer monitoring and enterprise AI delivery. Juncture reflects that: every verdict cites the exact label clause behind it, and the technical controls that support 21 CFR Part 11 are built in, including a time-stamped, tamper-evident audit trail, e-signature sign-off and role-based access control. You validate it for Part 11 use under your own SOPs.
- How is this different from the MLR and AI tools we already have?
- MLR workflow tools review, approve and store content, then stop once it is approved. AI answer visibility tools track how AI answers about a brand, but they start after launch and never touch the MLR workflow. Juncture is the only pharma content intelligence platform that joins a pre-MLR asset check, an approved-content system of record, and AI answer monitoring, all measured against the same approved label. It is the control point between the approved message and the machine answer, not a replacement for MLR.
See it on your brand
See what Juncture does, on a real asset.
Bring an asset and a brand. We will pre-check the asset against the label and show how the machine answers about the brand today.