Omnilogic Labs

CASE STUDY // CORPORATE TRAINING // BUILD

A diagnostic that ends in an enrollment.

A Latin-American corporate-training company sold courses, but the moment before the sale was a guess. We turned the front of its own funnel into a product: a two-surface MVP that runs AI-led skills interviews, assembles them into a gap analysis, and maps the gaps straight onto the company's course catalog — with a clear hire-versus-train recommendation falling out the other end. White-label and multilingual from the start. Roughly thirty days end to end.

SPEC_ID: WORK-05 // CAPABILITY: BUILD // TIMELINE: ~30 DAYS
FIG. INTERVIEW → INVENTORY → MAP
REF: WIM-00A signal pipeline: conversational interview at the source, structured skills inventory and gap analysis downstream

01 // The problem

The diagnosis was a guess — and the guess sat right in front of the sale.

The company sold courses. But the question that should precede every sale — which skills a workforce actually has, where the gaps are, and which courses would close them — was answered by slow manual interviews and intuition, when it was answered at all.

That is a noisy front end on an otherwise sharp catalog. The company wanted to replace it with an instrument: assess an organization's skills, identify the gaps, map them directly onto the course catalog, and hand a buyer a clear hire-versus-train recommendation. Turn the diagnostic from a cost of sales into the product itself.

REF: WIM-01 // BEFORE
// THE OLD FRONT END
  • Skills assessed by manual interview and intuition
  • No structured inventory across an organization
  • Gaps never mapped to specific courses
  • Hire-versus-train left to the buyer's gut

02 // The approach

Two surfaces, one signal path.

The design pairs the surface where signal is captured with the surface where it is acted on. An employee-facing interview produces structured signal; an executive dashboard aggregates that signal into a decision. Everything in between is a clean pipeline — capture, structure, analyze, map.

REF: SURFACE-A
record_voice_over

Employee surface — the interview

An AI-led skills conversation that feels natural to the employee while quietly producing structured, analyzable output. The interview is the sensor — it has to read as a conversation and write as data.

REF: SURFACE-B
dashboard

Executive surface — the dashboard

Campaigns, a skills library, reports, and cross-campaign analytics — the aggregate view a leader uses to act. The interview captures one person; the dashboard reads the whole organization.

WHITE-LABELMULTILINGUALAI INTERVIEWSEXECUTIVE ANALYTICS

03 // What we built

From a skills conversation to a course enrollment.

The MVP runs the full path: AI-led skills interviews, assembled into a skills inventory and gap analysis, mapped to the company's own catalog. The diagnostic doesn't end in a report — it ends in a recommended path to enrollment.

STEP 01forum

Interview

AI-led skills interviews with employees, in their own language.

STEP 02inventory_2

Inventory

Results assembled into a structured skills inventory across the org.

STEP 03query_stats

Gap analysis

Inventory read against need to surface where the gaps actually are.

STEP 04alt_route

Map + decide

Gaps mapped to specific courses, with a hire-versus-train call.

// SECTION: SCOPE — WHITE-LABEL + MULTILINGUAL FROM DAY ONE, SO THE CLIENT SHIPS UNDER ITS OWN BRAND

04 // What made it hard

FIG. CONVERSATION → STRUCTURED SIGNAL
REF: WIM-04A conversational waveform resolving into discrete structured signal

A conversation that has to write as data.

A thirty-day MVP forces ruthless scope discipline: enough product to be genuinely useful and demonstrable, and nothing built that the market hasn't yet asked for. The discipline isn't the hard part, though — knowing which knob to turn is.

The substantive challenge was the interview itself. An AI skills conversation has to feel natural to the person answering it and, at the same time, yield structured signal an analytics layer can trust. Then that signal has to become a gap analysis credible enough that an executive will act on it. The interview and the analytics had to be trustworthy on day one — get either wrong and the whole diagnostic falls down, because nothing downstream is better than the signal feeding it.

  • Natural conversation that still produces analyzable structure
  • Gap analysis credible enough for an executive to act on
  • Trustworthy on day one — no warm-up period to earn belief

05 // Outcome

A working two-surface MVP, on a thirty-day clock.

REF: WIM-05 // RESULT
TIMELINE: ~30 DAYS // SURFACES: 2 (INTERVIEW + DASHBOARD)

AI skills interviews feeding an executive analytics dashboard, with skill-gap findings mapped directly to the client's course catalog and a hire-versus-train recommendation — delivered as a demonstrable, white-label, multilingual product.

Directional outcome: the front of the funnel became a product surface in its own right — a diagnostic that hands the buyer a defensible path to enrollment instead of a guess.

WORKFORCE-INTELLIGENCESKILLS-GAP ANALYSISCOURSE MAPPING30-DAY MVP
// NEXT

Have a funnel whose front end is a guess?

We build diagnostics that end in a decision, not a deck — and we ship them on a clock. Tell us what the moment before your sale looks like, and we'll find the signal worth tuning to.

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