Zivaro LogoZivaro

Give every technical candidate a thoughtful interview—automatically

Zivaro’s AI agents run contextual technical interviews around the clock, ask intelligent follow-ups, and deliver evidence your engineering team can trust.

Adaptive questioning across frontend, backend, data, DevOps, mobile, and infrastructure roles.
Audio-native models detect pauses, confidence, and clarity while evaluating technical accuracy.
Engineering leaders receive structured scorecards, highlight clips, and recommended next steps.
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Overview

Why teams start here

Quickly align stakeholders on the problems you solve and the gains you unlock.

Fewer screening bottlenecks

Stop pulling senior engineers away from sprint work to run repetitive first-round interviews.

Role-specific depth

Templates reflect the nuance of your stack—from REST vs. GraphQL trade-offs to Kubernetes rollout safety checks.

Transparent evaluation

Audio clips, transcripts, and reasoning give confidence that recommendations are grounded in what the candidate said.

Expectations

Match every pain point with a crisp solution

Show the before/after so execs see exactly what gets fixed and what still needs attention.

Zivaro mirrors your best technical interviewer

We capture the knowledge of your staff engineers and scale it through audio-native agents.

  • Craft prompts covering systems design, debugging, performance tuning, or tooling familiarity.
  • Upload sample answers or code snippets to steer the follow-up depth you expect.
  • Use competency weights to emphasize architecture, execution, communication, or security hygiene.
  • Flag risky statements automatically—like confusion around state management or production rollbacks.

Manual technical screens cause hiring drag

  • Hard-to-schedule engineers lead to week-long delays before candidates hear back.
  • Question quality varies by interviewer, making shortlists inconsistent.
  • Candidates repeating the same introduction multiple times causes fatigue and drop-off.
  • Managers see a score but lack the context needed to trust the decision.
Outcomes

Proof points that matter

10–12 minutes
Average technical screen

Enough time for candidates to explain trade-offs without slowing down the funnel.

30+
Technical templates

Prebuilt coverage for roles from junior frontend to senior ML engineer, customizable in minutes.

Confidence scores
Per competency

Engineers see how certain the agent is about each rating to decide when to dig deeper in live loops.

Implementation

How it fits your process

1

Capture your rubric

Define the technologies, depth, and evaluation criteria for each role. Include links to architecture diagrams or code samples if needed.

2

Launch interviews on demand

Invite candidates directly or let them self-serve time slots. Zivaro adapts the conversation based on the path they choose.

3

Review technical evidence

Engineering managers receive summaries with supporting audio clips, missteps, and suggested focus areas for onsite rounds.

4

Close the loop fast

Move qualified candidates forward immediately and provide coached feedback to those who aren’t ready yet.

Use Case

What you can evaluate automatically

Zivaro handles more than simple trivia. The agents are trained to ask why, how, and what-if questions.

  • Systems design trade-offs and scaling scenarios.
  • Debugging walk-throughs to understand investigation style.
  • Code architecture discussions, including event-driven flows and API shape.
  • DevOps readiness, including rollout plans and incident response habits.
  • Communication clarity—can the candidate explain complex topics simply?
Next steps

Resources and deep dives

Learn how Zivaro interviews work end to end

See the complete workflow from configuration to shortlist delivery.

See how tech companies adopt Zivaro

Understand the impact on engineering orgs balancing hiring with roadmap execution.

"The AI interviewer asks the same questions I would, but it never forgets to probe for failure scenarios. We now ship interview packs to managers that actually sound like the candidate."

Riley Chen
Director of Engineering, product-led SaaS company
Technical hiring demo

Experience an automated technical interview

We will configure a role from your stack and walk through the candidate and reviewer views side by side.

Schedule a technical hiring sessionExplore engineering use cases