ScoutWithIn reads the CVs and project history you already hold, turns them into skills you can trace back to a quote, and tells you honestly whether to use someone, develop them, or finally hire.
Requirement
Data Engineer (before we advertise)
72%
already internal
Recommendation: develop Tom to level 4 on cloud infrastructure and buy in machine learning for one quarter. A full-time hire is not justified yet.
Internal first
every gap is checked against your own people before a hire
Every claim
traces back to a verbatim line of evidence
Nothing auto-approved
a human confirms each skill before it counts
Requirements engine · live
This is the real engine, running in your browser on an anonymised six-person team. Raise a required level, simulate developing someone, and the use / develop / hire verdict recalculates with the reasoning attached — deterministic arithmetic, never a model guessing.
How it works
Paste or upload a CV, or write up a project someone delivered. No new HR process, no self-assessment surveys nobody fills in.
Skills are extracted with a level, a confidence and the exact sentence they came from. A manager confirms, adjusts or rejects each one.
Define a role or project. ScoutWithIn shows who covers it, who is close, and what genuinely has to come from outside.

Evidence, not vibes
Skills inventories fail because nobody trusts them. In ScoutWithIn, clicking any capability opens the line of evidence behind it: which document, which sentence, who confirmed it and when.
“Rebuilt the nightly ingestion in Airflow, cutting a six-hour batch to forty minutes across eleven client feeds.”
Internal-first by design
Someone already meets the level. ScoutWithIn names them, shows the evidence, and flags it if they are your only one.
Someone is within reach. You get the gap in levels, who is closest, and a simulated view of readiness once they grow.
Nobody is close enough. The recommendation arrives with the reasoning attached, so the budget conversation is short.
Employees get their own grounded assistant: what their evidence says they are strong at, which internal opportunity they are closest to, and a realistic plan to close the gap. Managers never see their chats.
The role the board wants to advertise next quarter — one person has to cover all of it.
What-if: invest in someone
Toggle a development step and the engine recalculates instantly — the same simulation managers run before signing off a vacancy.
Deterministic recommendation
Develop internally
Priya Raman is within 2 levels on every capability that matters: 2 capabilities to develop, 3 levels to climb in total.
Priya already works at level 4.
Priya is 1 level short — realistic to develop.
Priya already works at level 4.
Priya is 2 levels short — realistic to develop.
Closest to the whole role
Pure arithmetic, no model in the loop — the same engine that runs inside the product.
See it on real evidence