Anjuri
Summary
You finish the interview, hang up the call, and have no idea whether you tanked the system design section or nailed it — because no one tells you. Anjuri records your side of the interview and returns a structured critique calibrated to the company, level, and round type you specified.
The workflow is three steps: you configure the target context (company, level, round type), record your microphone during the live interview, and receive a written breakdown covering what landed and what didn't against the bar you named. The feedback engine flags clarity, filler words, and STAR-method completeness for behavioral rounds. It keeps a session history so you can track drift across multiple interviews. The ceiling appears quickly: Anjuri reads only what your microphone captured, so if your answer was technically correct but you drew a bad diagram on the virtual whiteboard, that gap never surfaces. The tool is India-only for now.
Bottom line: Pick Anjuri if you are an Indian engineer grinding through FAANG or SDE hiring loops and want written post-mortem feedback on your actual answers — not on a mock; skip it if your weak point is anything that doesn't show up in speech, like system design diagrams or coding speed.
Pricing Plans
Usage-Based- Price
- Packs start at ₹399
- Free Tier
- 2 credits on signup
Free credits
2 credits on signup for up to 60 minutes of analysis
- First interview free
- Credits never expire
Credit packs
Buy credits starting at ₹399 incl. GST
- Pay only for what you use
- No subscription
View full pricing on anjuri.ai →
Pricing may have changed since last verified. Check the official site for current plans.
Community Performance Report Card
No community ratings yet. Be the first to rate this tool!
Community Benchmarks Community
Sign in to submit a benchmarkNo community benchmarks yet. Be the first to share a real-world data point.
Pros
Sign in to edit- Context-configured analysis (company, level, round type set before recording) so the feedback you get is benchmarked against the actual bar you're targeting, not a generic rubric that treats an SDE-2 screen the same as a staff design round.
- Audio is transcribed and deleted within 60 seconds of processing, which means you are not leaving a recording of an interview — where you may have discussed confidential projects — sitting in a vendor's storage indefinitely.
- Session history across multiple interviews, so you can pull up feedback from three rounds ago and check whether you've actually stopped leading behavioral answers with context dumps or you've just convinced yourself you have.
- Credit-based pay-per-use with no subscription and credits that don't expire, so you are not paying a monthly fee during the six weeks between interview cycles when you are in heads-down preparation mode.
- STAR-completeness scoring on behavioral answers, which means you get a named flag — 'this answer had no Result' — rather than the vague 'be more structured' feedback that tells you nothing actionable.
Cons
Sign in to edit- Feedback is derived entirely from your speech, so performance gaps that live outside what you said — a disorganized system design diagram, slow coding on a shared editor, a solution that was verbally described correctly but implemented wrong — do not appear in any report. Candidates whose main weakness is in the hands-on execution layer, not the verbal explanation layer, will find the reports systematically miss the thing that's actually costing them offers.
- The tool is available in India only. Engineers who relocate, work for companies incorporated outside India, or interview with interviewers based in jurisdictions with two-party consent recording laws face a compliance gap the vendor explicitly places on the user to resolve — and at that point most teams switch to a mock interview platform or human coaching service that doesn't require candidates to self-manage recording law research.
- There is no API, no integration with calendar or ATS tools, and no self-hosting option. Teams or coaches who want to build Anjuri feedback into a structured prep pipeline for multiple candidates have no programmatic path — every session is manually configured and retrieved by the individual candidate.
Community Reviews
Sign in to write a reviewNo reviews yet. Be the first to share your experience.
About
- Platforms
- Web
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-06-19T08:41:44.782Z
Best For
Who it's for
- Indian engineers interviewing with global or local companies
- Professionals seeking level-specific interview critique
- Users wanting credit-based pay-per-use analysis
- Candidates focusing on clarity, structure, and delivery
What it does well
- Analyzing performance in real FAANG or SDE interviews
- Getting feedback on behavioral answers using STAR method
- Tracking improvement across multiple interview sessions
- Preparing for coding, system design, or product rounds
Discussion Community
Sign in to commentNo discussion yet. Sign in to start the conversation.
Compare Anjuri
Spotted incorrect or missing data? Join our community of contributors.
Sign Up to ContributeCommunity Notes & Tips Community
Sign in to contributeBe the first to contribute. General notes, observations, gotchas, and tips from people who use this tool day-to-day.
Frequently Asked Questions
- Is Anjuri free?
- Anjuri is a paid tool (Packs start at ₹399). No permanent free tier is offered.
- Is Anjuri open source?
- No — Anjuri is a closed-source tool. Source code is not publicly available.
- What platforms does Anjuri support?
- Anjuri is available on: Web.
Hours Saved & ROI Stories Community
Sign in to contributeBe the first to contribute. Concrete time/cost savings, with context. e.g. "Cut my code review backlog from 4h to 45m per week."
Curated lists that include this category
After most technical interviews, candidates walk away with nothing but a hiring decision and a vague memory of where they stumbled. Anjuri addresses that gap by recording the candidate’s microphone during a live interview session, transcribing the audio, and running the transcript against a scoring rubric tied to the company type, target level (SDE-2, senior, staff, engineering manager), and round format the candidate specified before starting. The output is a section-by-section written report: what went well, what to improve, and how the performance compared to the bar for that level.
The differentiating design choice is context-specificity before the interview starts. Rather than generic post-interview feedback, the vendor states the analysis is calibrated to the background and level the candidate declares upfront — so feedback on a staff-level system design round reads differently than feedback on an SDE-2 behavioral round at a product startup. Audio is transcribed and deleted within 60 seconds per the docs, and the vendor states the data is never used for model training, which addresses a common concern when candidates are discussing proprietary work or unreleased products during interviews.
The tool fits a specific workflow: post-interview forensics for candidates who interview frequently and want written evidence of where they regress. It does not fit as a mock interview platform, a real-time coaching layer, or a tool for roles where the work product is visual or code-based rather than spoken. Because only the candidate’s microphone is captured, any feedback gap tied to what the interviewer said, what the candidate typed, or what they drew is a structural blind spot — not a bug to wait out.