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For journalists
Vet ten sources before deadline. None of them on your phone.
Totem runs the same questions with every source. The consistencies surface, the divergences too. You walk into the on-record interview already knowing where to push.
Silent betaFully free in beta
Story Vetting, Crestline Acquisition
Story vetting, multi-source. Totem ran this conversation across 9 sources and synthesized what came back into the takeaway below.
Key findingsAI-synthesized from 9 sources
Six of nine place the timing inside the same 72-hour window. Three diverge by more than a week, the line worth pressing. Five named the same internal comms freeze around the announcement; two more hedged. Four sources independently mentioned a board call the night before, none of them was supposed to know.
- Timing aligned
- Timing diverged
- Comms freeze named
- Hedged on freeze
- Knew about board call
- 20%Positive
- 20%Friction
- 60%Focus
- Responses
- 0
- Fully completed
- 0/0
- Avg. completion
- 0%
- Avg. length
- 0m
From silent-beta calls
“Two sources told me the same story. Totem flagged the line where their accounts diverged. I knew exactly which one to call back, and what to ask first.”
— an investigative reporter at a national paper
What journalists ask first
“But sources won't open up to an AI.”
Some will, some won't, same pattern as humans on the phone. The sources who'd talk to you anyway talk to Totem first, usually faster and at length, because there's no scheduling tax and the probes are sharper. The ones who won't open up are the ones who weren't going to give you the story; you find that out in 15 minutes instead of 15 emails.
What journalists start with
The interviews behind the interviews.
Source vetting
Source vetting
Same questions to every source, before any of them hit your phone.
Audience research
Audience research
What readers do, not what they say in the open-rate dashboard.
Concept testing
Concept testing
Reactions to a rough idea before you build.
Why journalists pick Totem
- 01
Same questions, every source. Consistency across the cohort is what makes inconsistencies meaningful. The story-divergence point is the lead.
- 02
Off your phone, on your timeline. Sources show up async, in their language, on their schedule. The hour you'd spend on each pre-interview is yours.
- 03
Audience research as a routine. Which beats your readers actually read, which they skim, which they'd kill the newsletter for. The dashboard tells you what reads. Totem tells you why.
What changes
What changes for journalists.
- 01
Source vetting at scale
Same prompt, same probes, every source. The cohort hears the same listener; inconsistencies between accounts become legible signal, not memory work. Triangulation across sources, the foundation of verification, scales when the pre-interview does.
Journalism methodology · Kovach & Rosenstiel, The Elements of Journalism
- 02
Pre-interviews off the calendar
The hour-each you'd spend warming up sources, hosted async. The on-record call is the call worth recording.
- 03
Reader research, weekly
What readers actually do with each beat, surfaced in their words. The newsletter you keep editing for them gets edited based on what they keep telling you.
Common questions
What journalists ask before they try Totem.
- How can journalists vet sources at scale?
- By moving the pre-interview from a 30-minute phone call to an async AI-moderated conversation. Totem runs the same structured questions with every source, surfaces what's consistent across the cohort, flags where two accounts diverge, and produces a vetting summary that earns or doesn't earn the on-record call.
- What's the best tool for journalistic source vetting?
- Most source-vetting workflows are unstructured (cold call, email, judgment) or built on CRM-style tools (Pipedrive, Notion, Airtable). Totem runs the conversation itself: same questions, same probes, every source. Inconsistencies between accounts become legible signal, not memory work.
- Can AI replace journalistic interviews?
- Not the on-record interview that earns publication. Totem replaces the pre-interview — the warmth, the vetting, the rapport-building you used to do in 30-minute phone calls. The on-record call goes from ten in a week to ten worth recording.
- How does AI-moderated source vetting affect reliability?
- It improves consistency. Drift between source-by-source phone calls — different journalist mood, different time of day, different probes — is one of the unmeasured sources of variance in pre-interviews. Same prompt, same listener, every source: the pattern across accounts is the lead.
- How is Totem different from Otter.ai or transcription tools?
- Otter and similar tools transcribe calls you make. Totem runs the calls. Different stage in the workflow: Totem replaces the warm-up and vetting; transcription tools handle the on-record conversation. They're complementary.
- Can Totem help with reader research?
- Yes. Beat-by-beat reader feedback at scale: which beats readers actually read, which they skim, which they'd kill the newsletter for. The dashboard tells you what reads. Totem tells you why. Same prompt across a reader cohort, run weekly or monthly, surfaces editorial signal grounded in what readers say.
Your turn
Describe the story. Hear every source first.
One prompt seeds the protocol. Totem runs the same intake with every source. You wake to the consistencies, the divergences, and the pressure point that earns the on-record call.
Drop your promptFree during the betaNo cardYour prompt, your data