Research that shows up where decisions are made.

bizra moderates AI conversations that probe like an experienced researcher, builds a knowledge layer that gets sharper with every study, and surfaces evidence in the tools where your team already works.

Live AI conversation
02:14
bizra Moderator AI
Tell me about the last feature your team shipped that didn't land as expected.
Participant Guest
We redesigned the settings page. Usage dropped 40% in the first week.
bizra Moderator AI
That's significant. Was this from support tickets, or did the data just show it?
Participant Guest
Both. Support tickets tripled and NPS went from +20 to -15.
Qual
Users couldn't find relocated settings
"Most people couldn't find features that moved."
Quant
NPS dropped 35 points post-launch
Segment NPS: +20 → -15
Behavioral
40% usage drop in settings page
Week-over-week engagement collapsed.
Opportunity: Settings navigation overhaul
Qual: 6 interviews mention buried settings
Quant: NPS -15, support tickets 3x
Behavioral: 40% usage drop, rage clicks up 220%
Confidence
Slack. Evidence replied in #product-decisions
Google Docs. Callout added to roadmap doc
Linear. Evidence badge on NAV-142

See how bizra interviews differently

Pick a scenario to watch bizra in action.

Live AI conversation
Recording in progress
00:00
Listening...

Here's what bizra extracted:

Qual
Redesigned nav buried daily-use settings
"We reorganized the navigation and buried things people used daily."
Quant
NPS collapsed from +20 to -15 post-launch
Segment-level NPS swing of 35 points in one week.
Behavioral
Prior research existed but was never surfaced
"That study was in a Google Doc no one remembered existed."
Opportunity: Settings discoverability
Confidence
And here's where it would surface:
Slack thread
Linear ticket
Roadmap doc
Live AI conversation
Recording in progress
00:00
Listening...

Here's what bizra extracted:

Qual
Research exists but isn't findable at decision time
"We've done the research, it's just buried in old docs."
Quant
Teams spend 3+ hours/week searching for prior research
Average research retrieval time: 47 minutes per query.
Behavioral
Decisions ship without available evidence
"By the time I found the study, the feature was already in staging."
Opportunity: Research discoverability at decision points
Confidence
And here's where it would surface:
Slack thread
Linear ticket
Live AI conversation
Recording in progress
00:00
Listening...

Here's what bizra extracted:

Qual
Researchers bottleneck on scheduling, not analysis
"Half my week is logistics. The actual research takes a few hours."
Quant
Average study takes 6 weeks from brief to share-out
3 of those weeks are scheduling and transcription.
Behavioral
Studies are deprioritized when capacity is tight
"We just skip the research when things move fast."
Opportunity: Research throughput scalability
Confidence
And here's where it would surface:
Slack thread
Roadmap doc

The problem

The most expensive question in your org.

Current. Tuesday, 2:14 PM
PM
Sarah K.2:14 PM
Does anyone have research on the admin invite flow? We're redesigning it next sprint.
R
James L.2:31 PM
I think we did something last year. Let me dig through Dovetail and my Google Drive...
R
James L.3:47 PM
Found a deck from Q2 but it's from a different segment. Still looking for the enterprise interviews.
D
Priya M.4:15 PM
Sprint planning is tomorrow. I'm just going to go with my gut on this one.
With bizra. Tuesday, 2:14 PM
Searching knowledge layer...
PM
Sarah K.2:14 PM
Does anyone have research on the admin invite flow? We're redesigning it next sprint.
B
bizra2:14 PM
I found an active opportunity on this topic.
Admin invite flow friction
14 interviews
NPS -18
34% drop-off
"I tried three different places and none of them worked."

Most teams have scattered research and blind spots they don't know about. bizra closes data gaps fast. Run AI-moderated conversations in days, not weeks. Field surveys for quant signal. Import your existing research so nothing starts from zero. Every source feeds one knowledge layer that always knows what's covered, what's thin, and what's gone stale.

For researchers

You curate. bizra does the rest.

Run your studies. Refine the findings. Set the direction. bizra handles everything after that. It talks to your stakeholders for you, surfacing evidence in their Slack threads, their docs, their sprint planning. You stop chasing people to read your report. The research finds them where they operate.

Your onboarding finding was cited in #product-eng 14 times this quarter. You didn't post it once.
3 Linear tickets were updated with evidence from your mobile study before you shared the readout.
The pricing opportunity you flagged appeared in the Q3 roadmap doc. The PM didn't ask you for it.
Writing a PRD on checkout? bizra surfaces 3 studies and a confidence score before you finish the first section.
Reviewing a Figma prototype? Findings from user interviews are pinned to the frames that need them.
Planning a sprint? Linear tickets already carry evidence badges from the knowledge layer.

For product teams

Every decision backed by evidence. One ping away.

Whether you're writing a PRD, building a strategy doc, or reviewing a Figma prototype, bizra makes sure the evidence is already there. The entire org's research knowledge shows up where you work. No dashboard to open. No researcher to chase. No waiting.

How it works

Three things happen when you use bizra.

Evidence accumulates

Run AI-moderated conversations that probe, adapt, and follow up like an experienced researcher. Field surveys for quant signal. Import what you already have. Everything feeds one place.

Interviews Surveys Import

Knowledge sharpens

bizra maps findings to opportunities. You see what's well-covered, what's thin, and what's gone stale. Every new study makes the picture clearer.

• Qual   • Quant   • Behavioral

Research reaches

Evidence shows up in Slack threads, Google Docs, Linear tickets, and Figma frames the moment a related decision is on the table. No one has to remember to open a dashboard.

B
bizra found 3 studies related to this thread. Strongest signal: onboarding drop-off (87% confidence).

Your workflow

Evidence meets you where you already work.

Select your tools to see how bizra fits your stack.

Slack. #product-decisions
PM
Sarah K.2:14 PM
Should we simplify the admin invite flow or add more permissions?
B
bizra2:14 PM
Related evidence found:
Admin invite flow friction
14 interviews
34% drop-off at step 3
"I tried three places and none of them worked."
Google Docs. Q3 Roadmap
Admin & Permissions Revamp
Goal: Reduce time-to-first-invite below 2 minutes for enterprise admins.
bizra · Strong evidence
14 interviews cite invite flow confusion. NPS for admin segment is -18. 34% drop-off at permission step. Most recent study: 3 weeks ago.
Linear. NAV-142
Redesign admin invite flow
In Progress · Sprint 14 · Assigned to Priya M.
Strong
14 interviews, -18 NPS, 34% drop-off · Last updated 3 weeks ago

The difference

Same question. Different follow-up.

Typical AI interview tool
How would you rate the onboarding experience?
I gave up halfway through.
Thank you. Next question: How likely are you to recommend us to a colleague?
Moves to the next scripted question
bizra
Walk me through what happened when you tried to onboard.
I gave up halfway through.
What specifically made you stop? Was it a particular step, or more of an overall feeling?
The invite flow. I tried three different places and none of them worked.
What did you do instead?
I just shared my login. I know that's bad but it was faster.
Probes the answer, not the script

FAQ

Questions we hear most.

No. AI-moderated interview tools automate scripted questions. that's a thin slice of the problem. bizra runs adaptive AI conversations, fields surveys for quant signal, imports your existing research (qual transcripts, survey data, behavioral exports), and builds a persistent knowledge layer across everything. The interview is one input. the knowledge layer is the product.

It probes. If someone says "I gave up," bizra asks why, when, what they did instead. The conversation adapts to what was just said. not what comes next on a list. It reads between the lines the way an experienced researcher would.

No. bizra ingests from Dovetail, Mixpanel, Snowflake, SurveyMonkey, and more. You can import existing interview transcripts, survey results, and behavioral data. so the knowledge layer starts with everything you've already learned. The point isn't to replace your tools, it's to give the evidence in them somewhere to live together.

The knowledge layer maps opportunities and the evidence behind each one. As more studies, surveys, and behavioral data land, bizra learns which areas are well-covered, which are thin, and flags evidence older than 12 months that may need refreshing. It also gets better at routing new evidence to the right opportunity automatically.

Most never open it. They see evidence as inline Slack replies, Google Doc callouts, Linear ticket badges, and Figma annotations. Research reaches them where they already make decisions. no dashboard to remember to open.

Your research is too valuable to live in a doc no one opens.

Join teams where every conversation, survey, and data point compounds into evidence that reaches the right decision at the right time.

Book a demo

See how bizra can work for your team. We'll walk you through the platform and answer your questions.

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