More interviews.
More closed deals.
Deals close when your consultant convinces the end client in the room. The engine gets more of your people there: paste any brief, get who actually fits — with evidence the buyer can check. Your people are IP; this makes it sell.
Demo data — the people and briefs are illustrative; named institutions appear as market context, not client claims.
Not a score. A reason. Evidence, plain language.
Understanding deep enough
to retell, for anyone.
One consultant. One static CV — or three winning narratives. Pick a context, watch the right facts come forward.
The difference isn't prettier formatting. It's that the engine understands the substance of the work — so the same person reads as the obvious choice for three different bids. Each tailored to what the client is buying — ready the moment the RFP lands.
The difference between
'worked at a bank' and
what someone did there.
A skills list tells you the tools. The engine organizes what someone has actually done across three dimensions — the ones that decide whether they'll succeed at the case in front of you.
The customer's world
Industry, domain, what the work meant to the business. Was it core to revenue, safety-critical, regulatory? Whether your expert has operated under real stakes — and whose.
Stack, systems, depth
Not just which tools. The architecture decisions, the constraints designed around, the quality bar. What "senior at company X" actually means — and why two identical CVs are not interchangeable people.
The role someone actually plays
Who drove, who delivered, who kept it alive. The spectrum from completing tickets to forming the concept alone — the single dimension no CV captures, and the one that decides who leads at the client.
Thomas H.
Senior Cloud & Data Engineer
Eight keywords. No stakes, no role, no client world. Search finds the words — not the person. And it's been frozen since last spring.
A CV is a snapshot someone remembers to update. The model accrues — every project close, interview and reference adds evidence, week after week, year after year. Every claim names its source, and what isn't evidenced stays visibly empty — the engine doesn't guess.
A project is worth more than a logo. We capture the project.
Start from the CVs you
already have. The engine
reads more than they say.
No new process, no forms for your consultants on day one. The engine works from real documents — and is honest about what it read versus what it inferred.
Every claim keeps the exact sentence it came from. No citation, no claim.
The engine knows the Finnish market — what Kela procures, what runs inside a Nordic retail bank, what a paper-mill delivery implies — and adds what a CV leaves unsaid, always marked as inference.
Short conversations — via the Slack bot or in the app — fill in what documents can't say: who led, what it changed, what to lead with next time. A few minutes at project close, all year long.
Thomas H.
Senior Cloud & Data Engineer · Helsinki
Lead developer, core banking platform migration (2019–2021) — moved the bank's transaction core to a cloud-native architecture without a single day of downtime.
Set the team's data-modelling standard and mentored four engineers into it.
Earlier: analytics and reporting projects for retail and logistics clients.
Led a core banking migration end to end — zero downtime
"Lead developer, core banking platform migration (2019–2021) — moved the bank's transaction core to a cloud-native architecture without a single day of downtime."
cv_thomas_h.pdf · p. 2 · verbatim
Sets standards others adopt — mentored four engineers into his practice
"Set the team's data-modelling standard and mentored four engineers into it."
cv_thomas_h.pdf · p. 2 · verbatim
Knows EU payments regulation (PSD2) from hands-on work
A payments platform at a Nordic bank in 2019 ran under PSD2 and EU data-residency rules. The CV never says the word — so this card says "inferred", not "fact".
inference · always shown as inference
Project close: HealthCo data platform. The documents say the migration shipped — but not who ran the client steering group. Was that you or Aino?
asks because the documents leave the lead role unclearMe, from May on — weekly steering with their CTO and finance lead. Aino owned the FHIR mapping.
Got it. Anything from this project the next pitch should lead with?
We cut their month-end close from 5 days to 2 — finance noticed before IT did.
Two minutes at project close. This is the data a CV bank never has — because a CV bank never asks.
Fit is a qualitative description, not a number.
A percentage is false precision, however well explained. You will not find a score, a dial or a ranking anywhere in the engine — you'll find reasons.
"Thomas fits because he has built exactly this under the same regulatory stakes — and he's free from 1.10."
Three bands. And a no always comes with the reason.
Results arrive as strong fits, worth a conversation, and honest no. The no is a feature: it's what makes the yes believable.
No citation → no card.
Every claim is traceable to the sentence that produced it. If the engine can't point to the source, the claim doesn't exist.
no citation → no card.
That's what makes the shortlist defensible in front of a buyer — and in front of the consultant it describes.
One capture.
Three people win.
Finds people they didn't know — with evidence to sell them
Paste the brief, get a shortlist with reasons a buyer can read. Discover the consultant you'd never have thought to put forward — and the narrative is ready the moment the RFP lands.
Sees the shelf — and what's incoming
Match people to work by what they've actually done, not who's loudest in memory. The bigger the firm, the bigger the edge.
Their real work, finally legible
Seen for what they've done, not flattened to a keyword list. They see their own data, correct it, and get sold into work that actually fits.
Sits on top. Replaces nothing.
The engine reads from and enriches the CV and staffing systems you already run. Your consultants keep their tools; your data gets a brain.
Book a demo
on a real brief.
Thirty minutes. Paste a live brief — yours or ours — and watch the engine build the shortlist and the evidence-cited pitch in front of you.
Frequently asked questions
What is the Profile Engine?
An engine that ingests your existing consultant CVs, turns them into evidence-cited claims organized across Business × Technology × Agency, and lets sales paste a messy customer brief to get back who actually fits — with the reason why, in plain language. Never a score.
How is this different from our CV bank?
A CV bank stores what someone typed, once, and finds it by keyword. The engine understands what the work meant — so it surfaces the consultant whose past project fits the new one even when the CV never uses the words in the brief. And every answer carries its evidence.
What do we need to start?
The CVs you already have. Twenty of them and one live brief is enough for us to show the engine on your own people — the reading layer needs no new process from your consultants.
Why no match scores?
Because a percentage is false precision, however well it's explained. Fit is a qualitative judgment: results come in three bands — strong fits, worth a conversation, honest no — and every band placement carries cited reasons you can check and defend in front of a buyer.
What happens when a consultant leaves?
The captured knowledge stays with the firm — projects, evidence, context. Retention isn't the headline (sales and staffing leverage is), but it matters: what you've learned about your own delivery capability stops walking out the door.
How do engagements start?
With a 3–6 month pilot on a single practice, with monthly feedback from your sales and delivery experts and no lock-in. Pricing is agreed per engagement — bring your consultant count to the demo and we'll walk you through it.