Saral Fit Score
Rankings you can check.
Every candidate tagged Excellent, Good, Partial or Weak fit on live proof of work, with the evidence linked to its source.
What is the Saral Fit Score?
Saral Fit Score is a fit rating (Excellent, Good, Partial or Weak fit) that ranks candidates on public signals of real work, with each signal linked to its source.
Your brief
Senior backend engineer in Bengaluru, Node.js + AWS, has scaled a payments system
Arjun Mehta
Senior Backend Engineer · TechFlow
- Maintains a Node.js payments librarySource
- Steady commits to production repos in the last 90 daysSource
- Two promotions in four yearsSource
Saral reads GitHub activity, LinkedIn trajectory and technical discussion on X and the open web.
Excellent
90–100
Shipped exactly this work, at this seniority, recently.
- · 3 comparable launches in the last 4 years
- · Scope matches the role, not the title
- · Tenure pattern suggests they would stay
Good
75–89
Most of the evidence is there; one dimension needs a conversation.
- · Strong shipped work in an adjacent domain
- · Slightly junior or senior on scope
- · One skill gap you can screen in 15 minutes
Partial
55–74
Right trajectory, wrong evidence for this brief today.
- · Adjacent stack or domain
- · Seniority mismatch is structural
- · Worth a call only if the pool is thin
Weak
Under 55
A keyword match, not a fit. Ranked low so you do not spend an hour here.
- · Title matches, work does not
- · No recent public evidence
- · Better suited to another brief
How it works
How does AI candidate ranking work in Saral?
- 001
Read public signals
Saral reads GitHub activity, LinkedIn trajectory and technical discussion on X and the open web.
- 002
Weigh them against your brief
Each signal is weighted by how much it matters for the role you described.
- 003
Show the evidence
The score arrives with the signals that earned it, each linked to its source.
Questions about Saral Fit Score.
Each candidate is tagged Excellent, Good, Partial or Weak fit. Open any card to see the signals behind the tag.
GitHub code activity, LinkedIn career history, and technical posts on X and the open web.
Yes. You can adjust what matters for a role and override any ranking. AI ranks. You decide.
No. Photos, gender, age, religion, caste and marital status are never used in scoring.
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Describe who you need, in English or Hinglish. Saral brings you the few who fit.