Deep Moderation at Scale
AI Moderation That Gets to the “Why”
Real probing, real follow-ups, real contradictions caught — across web, WhatsApp, voice, and 50+ languages. The qualitative depth of an expert moderator, at the speed and scale of software.
What was your first reaction to this one — versus the previous frame?
half-second pause + raised brow at 0:42
[ the problem ]
The “Why” Never Makes It Into the Deck
Surveys collapse your question into a checkbox. Most “AI interviews” are just chatbots with a follow-up button — they log what people say and move on. You end up with shallow text, no voice, no one probing the contradictions between what people claim and what they actually do. And your ops team still runs quotas in spreadsheets. The “why” never makes it into the deck.
01
Asks the Questions a Senior Researcher Would Ask
An expert moderator doesn’t read off a script. They listen, find the thread worth pulling, and probe like a senior researcher: Why did you switch? What was the moment you noticed? Was there a point you almost stopped? Alchemic’s AI moderator does the same — trained on your category, your brand vocabulary, your prior research — so every follow-up is on-brief, not generic.
The result is the depth of a senior moderator, run hundreds of times in parallel, asking the questions you’d want asked.
“…I switched because the packaging felt — I dunno, it just felt cheaper I guess.”
vague reason given — probed for the specific moment
You mentioned hesitating — what made you pause there?
“Honestly the price was fine, it was more that — you remember how the old packaging had that ribbed bit on the side? I’d grip it in the shower with shampoo on my hands. The new one slips. That’s why I switched, even though I didn’t realise it till you asked just now.”
What else came up that you didn’t expect to remember?
02
Don’t Just Keep Them Talking — Make Them Want To
High engagement is the unlock. Most AI interview tools see respondents drop off after 5–10 minutes — short, shallow answers, abandoned sessions. Alchemic interviews routinely run 30–50 minutes because the AI feels conversational, not clinical. It picks up when a respondent goes vague, brings them back when they wander, lets them tell stories, and only moves on when there’s nothing left to learn.
Deeper signal per interview. Less recruit burn. Findings you can actually defend.
03
Reads More Than Words
The AI listens to how a respondent answers, not just what they say. Three signals run together:
- Facial expressions — a smile that fades on a price question, a brow that lifts at a new packaging reveal
- Voice tonality — pitch, pace, the half-second pause before a yes
- The words themselves — what’s said, what’s avoided, the contradictions
Every AI-noticed moment links to the exact frame, voice clip, and transcript line. You see what the AI saw, and decide for yourself.
smile + voice warming at 0:18 — positive signal on Concept B reveal
What grabbed you about that one first?
04
Qual and Quant in One Conversation
Probing matters for some questions. Structured options work fine for others. Alchemic blends both in a single interview — open-ended follow-ups where the why lives, structured questions where the math matters. Same respondent. Same conversation. Same five-minute window.
Get a quote bank and a distribution chart from the same field. No second study. No reconciling two datasets. No “we’ll add a qual leg next quarter.”
“I trust it more when I see the ingredient list — feels like they’re not hiding anything. That’s why I keep coming back.”
Same respondent. Same five minutes. Both outputs.
05
Probing That Uncovers the Real Drivers
An AI moderator doesn’t ask a question and wait for the answer to a script. It listens, catches the tone, spots the hesitation, and probes the gap between what a person says and what they actually do. When someone claims one brand loyalty but allocates money elsewhere — the AI asks why. When a respondent mentions an emotional moment, the moderator takes them back to it: “Walk me through that. What shifted in that moment?”
This is the difference between surface answers and the emotional drivers that actually move decisions.
Supported in voice notes. Supported across 50+ languages with native probing — not translation templates. Multimodal stimulus: show a live Figma prototype, a product image, a video clip. The moderator adapts.
→ How much would bring you back?
→ Walk me through when you noticed
→ What did they say specifically?
more meaningful words per interview than a fixed survey.
06
From Screener to Payout, Automated
Recruit. Screen and quota — live, adaptive. Pay incentives via UPI, bank transfer, or global rails. Flag low-quality and inconsistent responses automatically. Detect dropouts and rebalance quotas without pausing. Every audit trail logged.
The AI moderator doesn’t just interview respondents. It is the operations backbone. No separate panel team. No manual QC spreadsheets. No three-week lag between fieldwork and payout. Studies run end-to-end, concurrent, at the speed of the moderator.
customer conversations across 8 studies in 3 months.
[ reach ]
Reach the Respondents Others Miss
Where They Already Are
Web link. WhatsApp — no app, no friction, just open the message. Voice call or voice note. The respondent picks the channel that feels natural.
In Their Language
Hindi. Tamil. Telugu. Kannada. Bengali. Marathi. English. 50+ more. Built and tested with India-native enterprise clients — not a generic translation layer applying English probing rules to Hindi speech.
In Any Modality
Text. Voice notes. Video clips. Live Figma prototypes. Product images. Packaging mockups. Whatever reveals the most honest feedback.
[ live reports & alerts ]
Real-Time Insights, Not Raw Transcripts
Themes auto-build as responses arrive. Every claim links to the exact quote and the voice recording. Drill down by geography, language, age, NPS, screener variable, quota cell. Live alerts fire to Slack or email the moment a theme spikes, sentiment shifts, or a response inconsistency is flagged.
Top Themes
Emotion Timeline
Surprise spike · 0:42
Trusted by brand and insights teams at
[ faq ]
Frequently Asked Questions
How is Alchemic different from a chatbot follow-up tool?
A chatbot logs responses and moves on. Alchemic moderates — probing contradictions, asking the second question that uncovers the “why,” catching hesitation in tone. It’s a senior researcher in software form, not a transcription machine with a follow-up button.
Which languages does the AI moderate in?
50+ languages. Hindi, Tamil, Telugu, Kannada, Bengali, Marathi, English, and more. Each is built and tested with native speaker proof points — not a translation layer applying English probing rules to other languages.
Do we bring our own panel or use yours?
Both. Alchemic recruits using its own panel network (tested for quality, incentive rails, Tier 2/3 reach). Or you can supply your own respondent list and we field to them. Or hybrid — you’ve got 500, we recruit 200 more to hit quota. Your call.
How fast from brief to insights?
Typically 3 days from fieldwork close to live dashboard. Themes auto-code as responses arrive. No post-fieldwork coding window. Complex studies with heavy stimulus or very large samples may take 5–7 days. We’ve done it faster.