Interview automation for recruiting firms

Your hiring pipeline, run by AI you already pay for.

InterviewDashboard screens every resume against every open role, builds your interview rubric, and scores each answer with verbatim evidence — then files the finished feedback form for you. AI runs through your own Claude, ChatGPT, or Kimi subscription: no API keys, no per-call fees, no cloud.

  • No API keys
  • No per-call AI fees
  • Local-first — your data stays yours
  • Windows & macOS
InterviewDashboard — Dashboard
Dashboard
Your hiring pipeline at a glance.
6
Open roles
23
Active candidates
8
Scheduled interviews
3
Awaiting final review
Pipeline ALL ROLES
Applied9
Alex Morgan
Backend Engineer
Priya Nair
Data Scientist
Screening6
Sam Reyes
Backend Engineer
J. Okafor
Account Exec
Interviewing5
Dana Kim
Staff Engineer
L. Fischer
Data Scientist
Offer2
M. Haddad
Staff Engineer
Hired4
T. Alvarez
Account Exec
Recent AI activity PROMPT RUNS
CLAUDEResume fitment scan — 3 roles41s
KIMITranscript matching — T2 Dana Kim18s
CODEXInterview scoring — Backend Engineer2m 07s
CLAUDERubric generation — v31m 12s

Runs on the AI subscriptions you already have

CC Claude Code
Claude Pro / Max
CX Codex CLI
ChatGPT Plus / Pro / Team
KC Kimi Code
Kimi membership
How it works

Folders in. Feedback forms out.
Everything in between is automated.

InterviewDashboard turns your file system into the integration layer. No ATS migration, no uploads — drop files in the client's folder and the pipeline moves.

01

Drop a resume

A watched folder per client ingests every resume the moment it lands — PDF or Word, text extracted automatically.

Resumes/
02

AI scans the fit

Each resume is scored 0–100 against every open role for that client — verdict, summary, pros and cons, in seconds.

strong fit · 84
03

Interview & drop the transcript

Interview from your own script. The transcript auto-matches to the right candidate and round by filename.

T2_ Dana Kim - Staff Engineer.pdf
04

Review, finalize, file

AI scores every answer against your rubric with verbatim evidence. You edit, finalize, and export a formatted feedback form — auto-filed.

Interview Feedback Forms/
Features

Built for teams that interview
at enterprise volume.

Resume inbox

Every resume, ranked against every open role. Automatically.

The moment a resume hits a client's watched folder, InterviewDashboard extracts the text and runs a fitment scan across all of that client's open roles — a 0–100 fit score, a verdict, and the reasoning, before you've even opened the file.

  • Strong fit / good fit / weak fit / not a fit verdicts calibrated to your rubric language.
  • Pros & cons per role, plus a resume summary with experience, key skills, and gaps worth probing.
  • One click to candidate — promote a scan straight into the pipeline, no re-typing.
Inbox — Resumes, ranked against open roles
PDF
Alex Morgan
alex_morgan_resume.pdf · scanned 42s ago
Scanned
Senior Backend EngineerStrong fit84

8 yrs distributed systems; led payments platform rebuild at 40M req/day scale.

  • Deep Go / Kubernetes match
  • No fintech domain time
  • Team-lead experience
  • Contract-heavy last 2 yrs
Platform EngineerGood fit67
Engineering ManagerWeak fit41
AI rubric builder

Your interview script becomes a scoring rubric. Versioned.

Upload the script your interviewers already use. AI extracts weighted evaluation criteria and writes good / better / best reference answers for every question — so every interviewer scores against the same bar, and every score means the same thing.

  • 4–7 weighted criteria, weights summing to 100 — tuned to the role.
  • Tiered reference answers: what a 3, a 4, and a 5 look like, in your firm's own language.
  • Fully editable & versioned — refine the rubric, keep the history.
Rubric — Senior Backend Engineer · v3
System design30 / 100
Technical depth25 / 100
Communication20 / 100
Ownership & delivery15 / 100
Collaboration10 / 100
Q4Design a rate limiter for a public API serving 40M requests/day. Walk me through the trade-offs.
Good

Working token-bucket design, one datastore, basic trade-offs.

scores 3
Better

Distributed design, Redis vs in-memory, failure modes called out.

scores 4
Best

Adds fairness, burst policy, observability, and rollout plan unprompted.

scores 5
AI interview review

Every answer scored. Every score backed by the transcript.

A two-pass review maps each scripted question to the candidate's actual answer, then scores Quality and Accuracy 1–5 against your tiers — with a verbatim quote as evidence. You get a weighted overall score and a hire recommendation you can defend to the client.

  • Evidence-anchored scoring — no score without the quote that earned it.
  • Strengths, gaps & concerns, plus what a best answer would have covered.
  • Human-in-the-loop: edit any score before you finalize and export the .docx feedback form.
Interview review — Dana Kim · Technical, Round 2
4.2OUT OF 5
Strong Hire

Consistently strong, structured answers with real production depth. System design answers reached the best tier unprompted.

  • Rate-limiter design hit best tier
  • Shallow on testing strategy
  • Owned a migration end-to-end
  • No multi-region exposure
"We moved the rate limiter into Redis after the second outage — I wrote the failover path myself." Q4 · QUALITY 5 · ACCURACY 5 — VERBATIM FROM TRANSCRIPT
Clients & roles

Organized the way recruiting firms actually work.

Clients own roles; roles own candidates and interviews. Each client gets a clean folder tree on disk, and InterviewDashboard keeps it fed — resumes in, transcripts matched, feedback forms filed. Your files stay readable, portable, and yours.

  • Multi-client by design — run every account from one dashboard, cleanly separated.
  • Role pipeline: draft → open → on hold → closed; candidates flow applied → hired.
  • Finished feedback forms auto-filed to the client's folder, named and dated.
Client workspace — Meridian Health
Meridian Health/client folder
Resumes/watched — auto fit scan
Interview Transcripts/watched — auto match
Interview Scripts/rubric source
Interview Feedback Forms/dana_kim_t2_review.docx — filed just now
drop fileextract textAI scan / matchpipeline updated.docx filed back
Enterprise by default

Serious about cost. Serious about
candidate data.

InterviewDashboard is a desktop app, not another SaaS meter. The architecture choices that make it cheap to run are the same ones that make it safe to deploy.

Subscription-billed AI

AI work is driven through the Claude Code, Codex, or Kimi CLI already signed in on the machine. Usage bills to the subscription you already pay — InterviewDashboard never touches an API key.

per-call AI fees: $0.00, forever

Local-first privacy

Candidates, transcripts, scores, and reviews live in a local database and plain folders on your machine. Resume text goes only to the AI vendor you signed in with — never to us.

cloud accounts required: none

Per-task model routing

Route each of the seven AI task types to the provider, model, and effort level you choose — cheap models for matching, flagship models for scoring. Every run is logged with tokens and duration.

audit trail: every prompt run, on record

Human-in-the-loop

AI proposes; the interviewer disposes. Every score, summary, and recommendation is editable before finalize — and the exported feedback form credits the reviewer who signed it off.

final say: always the interviewer

Pricing

One license. One price.
No meter running.

You already pay for AI. InterviewDashboard makes that the only AI bill you'll ever see.

Perpetual license
$250/ license

One-time purchase. Yours to run, seat by seat.

  • Unlimited clients, roles, candidates & interviews
  • Resume inbox with automatic fit scans across every open role
  • AI rubric builder with good / better / best tiers
  • Evidence-scored interview reviews & .docx feedback forms
  • Per-task model routing + full prompt-run audit log
  • Windows & macOS desktop apps
Buy InterviewDashboard

Requires an active Claude Pro/Max, ChatGPT Plus/Pro/Team, or Kimi membership on the machine. That's the only ongoing cost.

The math your CFO will like.

01

No usage meter

Screen 10 candidates or 10,000 — AI runs on your flat-rate subscription, so heavy interview months cost the same as light ones.

02

No per-seat platform tax

$250 once per license. No monthly SaaS fee scaling with headcount, no candidate-volume tiers, no overage surprises.

03

Volume licensing for firms

Outfitting a whole recruiting team? Talk to us about firm-wide licenses.

FAQ

Questions, answered.

No. InterviewDashboard drives the Claude Code, Codex, or Kimi CLI already installed and signed in on your machine. There are no API keys to manage, no usage dashboard to watch, and no per-call charges — AI usage simply bills to your existing subscription.

Claude Pro/Max (via Claude Code), ChatGPT Plus/Pro/Team (via Codex CLI), and Kimi membership (via Kimi Code). You can use one or all three, and route different task types — resume scans, rubric generation, interview scoring — to different providers and models.

On your machine. Candidates, roles, transcripts, scores, and reviews are stored in a local database and plain folders you control. There are no InterviewDashboard cloud accounts. When AI runs, document text goes only to the AI vendor you're signed in with — never to us.

It's built to be the layer recruiters actually live in. Folder watching, candidate pipelines, and auto-filed feedback forms mean many firms run it instead of an ATS for interview operations — and because everything is plain files and folders, exporting into any system you keep is trivial.

InterviewDashboard is a native desktop app for Windows and macOS. It's fast, works offline between AI runs, and feels like part of the OS — because it is.

One license covers one installation of InterviewDashboard with unlimited clients, roles, candidates, and interviews. It's a one-time $250 purchase — no subscription for the software itself. Your AI subscription (Claude, ChatGPT, or Kimi) is the only ongoing cost.

Get started

Your next hire's feedback form
could file itself.

ONE-TIME LICENSE · NO API KEYS · WINDOWS & MACOS