You already employ
more capability
than you can see.
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
- Data pipelinesPriya Ramancovered
- Cloud infrastructureTom Whitfieldnear
- Machine learningnobody yetmissing
- Stakeholder reportingJack Mellorcovered
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.
4 in 5
SME hires are for skills someone inside could have grown into
Every claim
traces back to a verbatim line of evidence
Nothing auto-approved
a human confirms each skill before it counts
Requirements engine · live
Move the requirement. Watch the answer change.
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.
The role the board wants to advertise next quarter.
What the requirement asks for
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
This is a development plan, not a vacancy. Every remaining gap is within internal reach.
- Data pipelinesuse
Priya Raman already works at level 4, which meets the requirement.
- Cloud infrastructuredevelop
Priya Raman is at level 3 against a required level 4 — a 1-level step that is realistic to close internally.
- Analytical SQLuse
3 people already work at level 3 or above.
- Machine learningdevelop
Tom Whitfield is at level 2 against a required level 3 — a 1-level step that is realistic to close internally.
Closest people internally
- Priya Raman83%
- Tom Whitfield79%
- Noor Haddad56%
Pure arithmetic, no model in the loop — the same engine that runs inside the product.
See it on real evidenceHow it works
From the paperwork you already have, to a decision you can defend.
Bring the evidence
Paste or upload a CV, or write up a project someone delivered. No new HR process, no self-assessment surveys nobody fills in.
AI proposes, a human decides
Skills are extracted with a level, a confidence and the exact sentence they came from. A manager confirms, adjusts or rejects each one.
Compare against what you need
Define a role or project. ScoutWithIn shows who covers it, who is close, and what genuinely has to come from outside.
Evidence, not vibes
Every skill can be challenged — and answered.
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
Three honest answers, and it will only say “hire” when it means it.
Use
Someone already meets the level. ScoutWithIn names them, shows the evidence, and flags it if they are your only one.
Develop
Someone is within reach. You get the gap in levels, who is closest, and a simulated view of readiness once they grow.
Hire
Nobody is close enough. The recommendation arrives with the reasoning attached, so the budget conversation is short.
Skills Buddy, for the people being measured
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.