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Trusted by growing teams

0

Interviews conducted

0

Companies

60%

Faster time-to-hire

4.9/5

Average rating

Screen 10x more candidates,
without increasing headcount

AI Agent

SM

Candidate

AI Agent

"Tell me about your experience with distributed systems..."

02:34
Sarah Mitchell

"We migrated to microservices with event-driven architecture and used Kafka for async communication..."

03:12
AI Agent

"How did you handle data consistency challenges across services?"

05:18
Sarah Mitchell

"We implemented the saga pattern with compensating transactions and used eventual consistency..."

06:04

AI interviews
that feel natural,
evaluate instantly

AI Evaluation
Strong Hire
0.0OVERALL
Technical Skills0.0
Communication0.0
Problem Solving0.0
Culture Fit0.0
Experience Match0.0

Sentiment

Positive

Experience

Senior

Enthusiasm

Very High

Top Strengths

System DesignClear CommunicationProblem Decomposition

Flags

Minor: Limited cloud experience

AI Verdict

"Exceptional system design thinking. Recommend advancing to final round with focus on cloud architecture."

We don't just evaluate candidates.
We evaluate your interviewers too.

SM
Candidate

Technical depth

9.2

Communication

8.5

Problem solving

8.8

Culture fit

9.0

9.1

Strong Hire

Interviewer

Question quality

4.2

Leading questions

2

Bias detection

Low

Candidate experience

4.5

4.2/5

Good · 32% talk time

Interviewer evaluations visible to admins only

24/7. No scheduling conflicts.
AI interviews run while you sleep.

02:00 AM

Tokyo

YT

Yuki T.

Backend Dev

Completed

09:30 AM

London

OS

Oliver S.

Full-Stack

In Progress

02:00 PM

New York

MG

Maria G.

Frontend Dev

In Progress

06:00 PM

São Paulo

LR

Lucas R.

DevOps Eng

Scheduled

Every second recorded, transcribed, and analyzed.

See who spoke when, how long, and what they said. Every interview becomes a searchable, replayable record with AI-powered insights.

Speaker Timeline
12:47 / 32:14
AI InterviewerAI
34%10m 58s
Sarah MitchellCandidate
66%21m 16s
Avg response: 2.1sFastest: 0.8sLongest: 12.3sPauses >10s: 1

Live Transcript at 12:47

"How would you handle a situation where two microservices need to share state?"

S

"I'd use an event-driven approach with a shared event bus — probably Kafka or Redis Streams..."

SDK, webhooks, MCP.
Build your hiring stack on Boooply.

create-interview.ts
01import { BoooplyClient } from '@boooply/sdk'
02
03const client = new BoooplyClient({ apiKey: "bply_..." })
04
05const interview = await client.interviews.create({
06 type: "AI_ONLY",
07 jobRole: "Senior Full-Stack Developer",
08 candidate: { name: "Sarah Mitchell" },
09 scheduling: "CANDIDATE_PICKS",
10});
11
12// Candidate picks a slot → AI interviews → webhook fires
13
14interview.on("evaluation", (result) => {
15 console.log(result.score) // 9.1
16 console.log(result.verdict) // "Strong Hire"
17})
REST APIWebhooks (HMAC-SHA256)MCP ServerJavaScript SDKGoogle CalendarCustom ATS Integration