Not the cheapest AI analysis. The most accurate.
Every piece of data in reOS - interviews, tickets, emails, survey answers - flows through DIVE™, a human-led, four-stage pipeline built to reduce hallucination and keep every claim traceable. No black-box AI.
Four stages between data and claim.
reOS is the only platform that runs every analysis through DIVE™. It exists for one reason: accuracy. Each stage checks the last, hallucinations get filtered out, and everything stays traceable.
Raw transcripts, tickets, and answers become structured observations - who said what, about which moment, with what feeling. Nothing summarized away.
Observations are sharpened and deduplicated. Vague claims get tightened or dropped; near-duplicates merge with their counts intact.
Every observation is checked against its source. If the quote doesn’t actually support the claim, the claim doesn’t survive.
Validated findings are enriched with context from your wider research - past studies, related tickets, open research questions - so every observation can be found again and recombined into new insight.
Cheap analysis you double-check. Accurate analysis you ship.
You tell the AI what’s true.
DIVE™ pauses when it hits an ambiguity instead of guessing. reOS surfaces what’s unclear - and the assumption it would otherwise run on - so you confirm, correct, or rein it in before the analysis moves on. Nothing material is decided silently.
Every ambiguity and possible moderator bias is flagged before it can quietly shape the data - ranked by how much your answer could change the findings.
Each question shows the current best interpretation - the default it proceeds on if you skip, so a run never blocks.
Confirm, correct, or add context. The AI never makes a micro-decision on its own without showing you the call.
A participant says they listen to “a lot of SoundCloud” alongside curated playlists. It’s unclear whether SoundCloud serves a need the playlists don’t.Which interpretation do you confirm?
Your models. Your prompts. Your flows.
DIVE™ is the backbone - what runs inside it is yours to shape. Pick the AI models you trust, bring your own prompts and snippets, and compose analysis flows that match how your team actually works.
Different stages, different models - a fast one for decoding tickets, a careful one for validating claims.
Encode your team’s definitions - what counts as a “churn risk”, how severity is graded - and reuse them across every flow.
Every analysis is an explicit, inspectable pipeline. Anyone on the team can open it, edit exactly what the AI is asked to do, and make it their own.
Templates with the homework done.
Don’t want to tune models? Take a premade template. We benchmark them continuously against hand-coded ground truth and default each one to the best answer for your money, not the cheapest model.
Every template ships with measured accuracy and relative cost, re-tested as models change.
Start from a template, then override any step - your changes ride on top, and the benchmark tells you what they cost.
Your support inbox is a research study.
Connect your support email as a channel and every message flows into reOS, through a DIVE™ pipeline of your choosing - continuously. Interviews are one source; this is how you analyze everything else, at any scale.
Tickets, support emails, call transcripts, form answers - one analyzable stream, themes surfacing as they emerge.
Some projects never close - track customer sentiment as an always-on study, analyzed as each message lands.
Ten interviews or two hundred thousand tickets: the same validation rules apply, and every theme still cites its sources.
When a channel theme spikes, plan a study from it in one click - the loop starts again with evidence in hand.