tenurr.com

Tenurr stores your work logging entries and career files in an encrypted personal document vault, and the platform is positioned as a private, self-sovereign Career OS — meaning your career data is meant to stay under your control rather than being pooled or shared by the platform. This matters most if you're logging sensitive achievements (performance wins, compensation targets, internal project details) and don't want them exposed to employers or third parties.

What "private Career OS" actually covers

Tenurr describes itself as "your private Career OS" and "encrypted and self-sovereign." Those two words do different work:

• Encrypted — the Work Logging module stores career files in an encrypted storage layer, described as a "personal document vault."
• Self-sovereign — the framing is that you control the data, not the platform. Tenurr's own summary states the product is "one platform you control."

So the privacy claim isn't just about a login screen. It's about where your achievements and documents physically live and who can act on them.

Which parts of your career data are affected

Tenurr bundles three modules, and they don't all carry the same privacy weight:

The Work Logging module is where the encryption claim is most explicit — it's the one described as encrypted storage. If your concern is "I don't want my raw achievement log or performance evidence sitting in plaintext somewhere," that's the module to focus on.

Why the career loop makes privacy more important, not less

Tenurr's design intentionally connects the three modules: you log wins at work, turn those wins into interview stories, and track applications through to an offer. Each module feeds the next.

That's useful, but it also means a single platform accumulates a fairly complete picture of you — your real accomplishments, your compensation targets, and your active job search. A job search is exactly the kind of activity you may not want visible to a current employer. The self-sovereign positioning is Tenurr's answer to that: the data is yours, held in your vault, rather than something the platform treats as its own asset.

Who this setup suits

This privacy model fits you if:

• You log achievements that reference internal metrics, client names, or unreleased work.
• You're job hunting while employed and want your pipeline and compensation targets kept separate from your employer.
• You want a durable record of your impact — for review season or a future search — without handing that record to a third party.

It's less of a differentiator if your work log contains nothing sensitive and you're comfortable with any hosted tracker.

What to verify before relying on it

The page evidence confirms encrypted storage and the self-sovereign framing, but it doesn't spell out encryption specifics — key management, whether encryption is end-to-end or at-rest, or exactly which fields are covered. The pricing page exists but no pricing details or payment terms are given in the available material, so don't assume a free tier covers encrypted storage indefinitely.

If encryption architecture is the deciding factor for you, check Tenurr's own documentation or FAQ for the details on how keys are handled before you move sensitive career files into the vault.

Tenurr is a private Career OS that links three modules into one repeating cycle: Work Logging captures what you actually accomplish, Interview Prep turns those accomplishments into practiced answers, and Job Hunting tracks where those answers get used. The loop works because each stage produces the raw material for the next — you log a win today, rehearse it as a STAR story tomorrow, and attach it to a live application the day after. This explainer is for anyone deciding whether a connected system beats juggling separate notes, docs, and spreadsheets.

The three modules and what each one holds

The platform describes these as "three pillars, one platform," and the dashboard reflects that: a single view shows Tenurr Score, job pipeline, and logged wins side by side.

How the loop actually feeds itself

Step 1 — Log wins at work

You capture achievements as they happen, in seconds, rather than reconstructing them months later. The stated purpose is to avoid losing proof of impact before review season or a job search begins. Each entry becomes a stored fact about what you did.

Step 2 — Turn real wins into interview stories

Interview Prep draws on those logged wins instead of generic prompts. You rehearse behavioral, technical, and system design questions, and the AI mock interview returns scored feedback. The Tenurr Score readiness dashboard tracks whether you're ready — the site shows an example score of 92 alongside a "Ready" status. There's also a 2-minute free intro round for a first pass.

The connection matters here: a behavioral answer built from a logged achievement ("API latency −250ms") is specific and verifiable, not improvised.

Step 3 — Hunt with structure

Job Hunting tracks every application, referral, and interview loop. You can generate ReferMe links with read receipts and link expiry, and set compensation targets. The tracker shows phases — the example dashboard lists "Stripe — Staff Eng — Onsite" as active. An AI job hunt matcher is listed as coming soon.

Step 4 — The loop closes

Landing the role starts the cycle again: new work produces new wins, which become new stories, which support the next search. The site frames this as "a career loop that compounds."

What you gain from the connection

• No starting from zero. Because logging runs continuously, prep and applications pull from an existing record rather than a blank page.
• Consistency across stages. The same achievement appears in your brag document, your mock interview answer, and your application narrative.
• Visibility into readiness. Tenurr Score gives a single number for prep status, separate from pipeline activity.
• Privacy as a design choice. The platform describes itself as encrypted and self-sovereign, with an encrypted document vault for career files.

Where to start

If you want to test the loop before committing, the 2-minute free intro round is the lowest-friction entry point into Interview Prep. If your immediate need is organization, the visual job tracker and work logging are the modules that produce structure fastest. The three modules are presented as connected, so starting with any one still feeds the others over time.

Pricing details are not specified in the available page content, so check the Plans section on the site for current tiers before deciding.

Tenurr's AI mock interview is a practice tool that lets you rehearse behavioral, technical, and system design questions and get scored feedback afterward. The Tenurr Score is a readiness indicator that tracks how prepared you are across those practice sessions. Both sit inside Tenurr's "Career OS," which also handles job tracking and work logging. You can try a 2-minute free intro round before committing to longer sessions.

What the AI mock interview covers

Tenurr's interview prep module is built around three question types:

• Behavioral — the "tell me about a time when…" format
• Technical — role-specific problem questions
• System design — architecture and tradeoff questions

The idea is that you rehearse the same categories you'll face in a real interview loop, rather than only reading sample answers.

Session lengths

Two practice formats are described:

The 2-minute intro round is the lowest-commitment way to see how the scoring and feedback feel before you invest time in longer sessions.

How the feedback works

After a mock interview, Tenurr returns scored feedback. The platform's own example shows a "Mock interview — System design" marked as passed, alongside an "AI Mock Score: 92." That tells you two things about the output:

1. You get a numeric score for the session.
2. You get a pass/fail-style signal relative to the interview type.

The stated purpose of this feedback is to help you identify weak areas — so the useful move is to treat a low score as a pointer to which question type or topic to drill next, not as a verdict on your ability.

What Tenurr Score is

Tenurr Score is described as a readiness dashboard — a single number that aggregates your prep state. In the platform's example dashboard, it reads 87 with a "Ready" label.

Think of it as a gate before you start applying in earnest: the product's framing is "practice until Tenurr Score says you're ready." It's a progress metric tied to your mock interview performance, not a certification or an external assessment.

How the two connect

The loop works like this:

1. Practice — run a mock interview or a 5–15 minute drill.
2. Get scored — receive session feedback and a score.
3. Update readiness — your Tenurr Score reflects where you stand.
4. Repeat — drill the weak areas until the score indicates readiness.

This is also where Tenurr's broader "career loop" comes in: work achievements you log can be turned into interview stories, which you then practice in mock interviews. The prep module isn't isolated from the rest of the platform.

Practical notes before you start

• Start with the 2-minute round. It costs little and tells you whether the feedback style matches how you like to practice.
• Use short drills for volume, full mocks for realism. The 5–15 minute sessions are for repetition; a full mock is closer to an actual loop.
• Watch the score trend, not one number. A single session score is noisy; the readiness dashboard is the signal.
• Check pricing before relying on it long-term. Tenurr lists a Pricing page and a "Start free" entry point, but the available material doesn't specify what the free tier includes beyond the 2-minute intro round or what paid plans cost. Confirm current terms on the site.

If your goal is simply to get scored reps on behavioral, technical, and system design questions and to have one readiness number to track, Tenurr's prep module covers that. If you need human feedback or company-specific interview intel, this tool won't replace it.

Tenurr's own site frames its plans as "Plans for every career stage," and it offers a "Start free" entry point, so you can begin using the platform before committing to a paid tier. The one free element the page states explicitly is a 2-minute free intro round for AI interview prep. Beyond that, the site does not publish specific plan names, prices, or a feature-by-feature breakdown of each tier, so the most reliable way to choose is to match the plan to the module you actually need first: Prepare, Hunt, or Log.

What the page confirms about plans

Because the homepage does not list prices, tier names, or per-plan feature limits, treat any specific figure as unverified until you open the Pricing page yourself. The site also does not state whether the free tier requires a login or how long it lasts — so don't assume "free" means unlimited.

Match the plan to your career stage

Tenurr organizes itself around three modules that feed each other: Prepare (AI mock interviews and Tenurr Score), Hunt (application tracker and ReferMe referral links), and Log (encrypted work achievement logging and STAR brag documents). Your stage determines which module you'll lean on first.

If you're actively interviewing now

You need Prepare most. Look for a plan that covers AI mock interviews with scored feedback, quick 5–15 minute practice drills, and the Tenurr Score readiness dashboard. The free 2-minute intro round lets you test the interview experience before paying — use it to judge whether the feedback quality is useful to you.

If you're job hunting but not yet in loops

You need Hunt most. Prioritize a tier that includes the visual application tracker, interview-phase tracking, compensation targets, and ReferMe links with read receipts and link expiry. Note that the AI job hunt matcher is labeled "coming soon," so don't choose a plan on the promise of that feature alone.

If you're employed and building a record

You need Log most. The relevant features are fast-entry daily win logging, the STAR-method brag document compiler, and encrypted document storage. This stage is the lowest-urgency to upgrade, since the value compounds over time — logging wins daily is what later feeds your interview stories.

If you're between stages or just exploring

Start free. The career loop is designed so each module feeds the next — log wins, turn them into interview stories, track applications — so you can begin with whichever module matches today's need and expand later.

How to decide without published pricing

1. Open the Pricing page from the site navigation to see actual tiers, prices, and feature limits.
2. Use the free intro round to test the AI mock interview and see whether Tenurr Score feedback matches how you prepare.
3. Identify your dominant stage (Prepare, Hunt, or Log) and check whether the tier you're considering covers that module's full feature set.
4. Confirm what the free tier includes beyond the 2-minute round before assuming it covers tracking or logging.

The page does not disclose payment methods, refund terms, or whether higher tiers unlock all three modules together. Those are the specific things to verify on the Pricing page before you commit.

Tenurr is a private "Career OS" — a single platform that combines AI interview preparation, job application tracking, and encrypted work logging. It's aimed at people who want their career activity to compound instead of resetting every time they job hunt: you log achievements as they happen, turn them into interview stories, and track applications through to an offer. According to the site, it's encrypted and self-sovereign, meaning you control your data. You can start free and use it at app.tenurr.com.

The three modules

Tenurr is organized around three connected pillars. Each one feeds the next, which is the core of its pitch.

Prepare — Interview Prep

• AI mock interviews with scored feedback
• Quick practice drills of 5–15 minutes
• Behavioral, technical, and system design question rehearsal
• A "Tenurr Score" readiness dashboard that tracks how prepared you are
• A 2-minute free intro round to try it

Hunt — Job Hunting

• A visual job application tracker covering applications, interview phases, and compensation targets
• A "ReferMe" referral link hub that generates trackable links
• Read receipts and link expiry on referral requests
• An AI job hunt matcher is listed as coming soon

Log — Work Logging

• Fast-entry logs for daily work achievements
• A STAR-method brag document compiler (Situation, Task, Action, Result)
• Encrypted storage
• A personal document vault for career files
• A chronological record of your impact

How the loop works

The site describes a three-step cycle:

1. Log wins at work — capture achievements daily so nothing is lost before review season or a job search.
2. Prep with AI — turn those real wins into interview stories and practice until your Tenurr Score says you're ready.
3. Hunt with structure — track every application, referral, and interview loop so you always know where you stand.

The idea is that logging feeds preparation, and preparation feeds the job hunt — so you're never starting from zero.

Who it's for

Tenurr fits best if you want one place to hold your career history rather than scattering notes, spreadsheets, and prep tools across separate apps. The encrypted, self-sovereign positioning matters most if you're uncomfortable storing work achievements and job-search activity in a tool you don't control.

It's less useful if you only need a one-off mock interview or a simple application spreadsheet — the value comes from using the modules together over time.

What to check before committing

The site mentions "Plans for every career stage" and a pricing page, but no specific prices, tiers, or payment details are listed in the available material. If cost matters to you, check the pricing page directly rather than assuming the free tier covers everything. The AI job hunt matcher is also marked "coming soon," so don't count on it yet.