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 words. Your rules. Your evidence.
DIVE™ is the backbone, and it runs the way your team works. Teach reOS your vocabulary and your standards once, and every analysis in every project applies them - without anyone tuning a prompt.
Product names, internal terms and acronyms, spelled right in the transcript, said right by the AI moderator, understood right in the analysis.
Workspace context carries what your team means - what counts as a “churn risk”, how severity is graded - into every run.
Voice, formatting and the things you never say, applied to every document the AI writes. Set it org-wide, or per document type.
The model homework, already done.
You never pick a model. We benchmark them against hand-coded ground truth and run every step on the one that gets it right - not the cheapest, and not whichever is in the headlines this week.
Accuracy and relative cost are measured per step and re-tested as new models ship, so today’s analysis runs on today’s best.
When something better wins the benchmark, your analyses simply get better. Nothing for your team to evaluate, switch or maintain.
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.