About Beseekr Resume Suite

We make you look like the best version of yourself.Not someone else.

Most AI resume tools hallucinate. They see a Junior Developer resume, paste a Senior Architect JD, and spit out bullet points full of "architected enterprise-scale microservices" and "$10M cost savings". Recruiters see through it instantly. Offers don't follow.

Beseekr Resume Suite is built differently. We ground the AI in your real profile first, then optimize. The result is a resume that sounds polished, passes ATS, and holds up under interview scrutiny — because every bullet is believable.

0
Fabricated metrics added
Ever
3
Extraction steps before AI writes a word
Grounding pipeline
< 30s
Average tailor + ATS run time
Cached results reuse
100%
Resume data encrypted at rest
AES-256-GCM

What makes us different

Every design decision is made around one principle: recruiters can tell when a resume is fake.

Accurate, not hallucinated

Before touching a single bullet point, our AI extracts your actual years of experience, seniority tier, scope, and company sizes. It never adds a metric you didn't earn.

Context-aware optimization

Resume optimization happens in two LLM passes: one to profile you, one to optimize. The profiling pass enforces hard constraints that the writing pass cannot override.

ATS that actually checks things

Our ATS audit checks keyword density, XYZ-formula bullet compliance, formatting safety, and gives you line-level suggestions — not just a score.

Speed without quality loss

Results are cached server-side by JD + user context. Identical re-runs return instantly. New JDs run through the full pipeline in ~25 seconds.

Realistic metric scaling

If you have 2 years of experience, we won't suggest you 'led a $5M ARR initiative'. Metrics are scaled proportionally to your actual tenure and role scope.

The optimization pipeline

Three LLM steps, one coherent result.

  1. 01
    Upload & parse

    Your resume (PDF, DOCX, or TXT) is parsed into structured JSON — sections, bullets, dates, skills, companies.

  2. 02
    Context extraction

    A dedicated LLM pass reads your resume and computes: total years of experience, seniority tier, functional domain, scope, team size proxy, and hard metric bounds. This profile is passed as hard constraints to every downstream step.

  3. 03
    JD-aligned optimization

    The writing LLM receives: your parsed resume, the grounding profile (with bounds), and the job description. It rewrites bullets to match keywords, improve XYZ format, and strengthen impact language — without exceeding the bounds set in step 2.

  4. 04
    ATS scoring & audit

    Simultaneously, an ATS analyzer scores the optimized resume against the JD. Missing keywords, format issues, and bullet quality are surfaced as actionable suggestions.

  5. 05
    PDF / DOCX generation

    Your final resume is rendered to a clean, ATS-safe PDF or Word document — ready to send.

Ready to try it?

Upload your resume. Paste a JD. See the difference Agent's makes.

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