AI-Native People Intelligence

Know what your workforce can actually do. Then act on it.

AI interviews your employees and managers — separately, about the same roles. Compares what they say. Turns every finding into a concrete action: hire, develop, transfer, regrade. Works from week one. No big project required.

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Interview → Synthesis → Action

Not a concept. Here's what happens in the product, step by step.

1. AI Interviews (Separately)
Ik
You mentioned data pipelines. What tools do you use? How complex are they?
LS
Mostly Python and SQL. Some Airflow. I built the real-time scoring pipeline last quarter.
Ik
Tell me about that scoring pipeline — how many data sources? What happens when it breaks?

Employee: 15-30 min about their work, goals, interests.

Manager: 20-30 min about team roles, needs, strategy.

Both about the same roles — independently.

2. Compare Both Perspectives
Employee says
"I build and maintain data pipelines — it's engineering work"
Manager says
"She handles our analytics — reports and dashboards"
AI Finding
Role mismatch. Employee does engineering, classified as analytics. Grading, development plan, and team capacity are all wrong.

Where they agree = confirmation. Where they disagree = the most valuable finding in the system.

3. Concrete Actions (1 Click Each)
REGRADEReclassify: Analytics P3 → Data Eng. P4 (justification generated)
DEVELOPNew career path: cloud engineering (matches stated goal)
BACKFILLAnalytics gap created → job req auto-generated

Every finding links to actions. Click and it generates the job req, development plan, or regrading justification.

Value from week one — no big project required

Each phase works independently. Start with what you need, expand when you're ready.

Phase 1

"Who do we have?"

AI interviews employees + managers. You get: rich profiles, role descriptions, skill maps, and — most importantly — misalignment findings between what employees say and what managers think.

Results in 2-3 weeks
Works standalone. No strategy input needed.
Phase 2

"Where are the gaps?"

Add corporate strategy as context. CEO or CHRO chats about direction. Managers describe departmental plans. System shows which capabilities are missing, when, and why.

Add in week 3-5
Strategy makes it powerful. But Phase 1 is already useful.
Phase 3

"What do we do about it?"

Every gap links to an action: hire, develop, transfer, promote. Scenario simulations with costs and timelines. Proactive reminders based on lead times. Dynamic updates as new data comes in.

Ongoing, continuously improving

See what happens end-to-end

Four scenarios. From AI interviews to findings to actions.

Sales Scaling
Career Pivot
Grading & Compliance
Cloud Transformation

VP Sales needs 5 AEs. The AI catches a problem.

Works from employee + manager interviews alone — no strategy input needed.

Manager Interview
VP Sales: "I need 5 senior AEs with enterprise SaaS experience, fluent German/English, 50% travel, 500K+ ARR track record."
AI follow-up: "Which of these requirements actually predict success? What does a typical week look like?"
Reality Check
AI Finding: This profile = ~120 candidates in DACH. ~30 reachable at your salary band. Meanwhile, your top AE (Julia Meier) doesn't match 3 of these 5 "must-haves" — she came from B2C with no SaaS background. Your requirements describe a wish list, not your success profile.
Employee Data
Interviews with current AEs: actual travel is 20% (not 50%), SaaS matters less than consultative selling, and 2 people on the Customer Success team expressed interest in sales — both have strong product knowledge and client relationships.
Source: 8 employee + 2 CS team interviews
Actions
TRANSFER Move 2 from CS to Sales (87% and 79% match, both expressed interest)
HIRE Open 3 AE positions with adjusted requirements (pool: ~30 → ~450)
DEVELOP 4-week sales methodology onboarding for internal transfers

Result: 2 filled internally (faster, cheaper). 3 external hires with realistic requirements = faster pipeline, better fit.

Marketing analyst wants to move into data. The system finds the path.

Employee-driven. No manager or strategy input required.

Employee Interview
Sarah builds campaign dashboards in SQL, automates reports in Python, analyzes customer segments. She says: "I want to build the systems underneath, not just the reports."
AI: "Tell me about the Python scripts — what data? How did you learn? What would your ideal next role look like?"
Matches Found
Junior Data Engineer — Data Platform (78% match)
"Your SQL and Python transfer directly. Gap: Airflow + cloud data services — closable in 3-4 months."

Analytics Engineer — Product (72% match)
"Strong data modeling overlap. Gap: dbt + warehouse architecture — 4-5 months."

Each match explains: why it fits, what's missing, how long to close the gap.
Qualifying Chat
When Sarah clicks "Express Interest", the AI doesn't just submit an application — it asks deeper questions specific to that role: "You mentioned Python — have you worked with data quality frameworks? How do you handle schema changes in your pipelines?" This deepens her profile for that specific match.
Actions
MATCH Sarah sees both roles with one-click application (auto-generated from profile)
DEVELOP Development plan: Airflow (4 wk) + dbt (3 wk) + cloud services (6 wk)
BACKFILL Marketing team flagged: reporting capacity gap if Sarah transfers

Result: Sarah stays at the company instead of leaving for an external data role. Marketing gets advance notice. Hiring manager gets a candidate who already knows the data.

EU Pay Transparency compliance. 4 weeks, not 12 months.

Replaces a 6-12 month consulting engagement.

Data Collection
AI interviews employees and managers about every role. Both describe what the role does — separately. 252 employees, ~3 weeks.
No consultants scheduling workshops. No forms. No managers struggling with HR terminology.
AI Generates
Complete job architecture: 6 function families, 6 levels each (P1-P6), salary bands, and — critically — an audit-ready justification for every single grading, based on EU criteria: Competencies, Effort, Responsibility, Working Conditions.
Findings
4 pay equity issues caught automatically:
1. Female engineers at P4 earn 8.2% less than male peers with equivalent criteria
2. Two sales roles perform identical work but are banded 15K apart
3. One engineer above band ceiling — reclassify or adjust
4. Sales P4 has 30% salary spread — may need sub-levels
Each flag: data source, affected employees, correction suggestion.
Actions
CORRECT Adjust 2 salaries: +4,800 and +6,200 EUR (closes gap to <2%)
UNIFY Merge two equivalent sales functions into one consistent banding
REVIEW 4 flags in HR queue, prioritized, each with one-click resolution

Result: Full compliance in 4 weeks. Auditable justification per role. Pay equity issues fixed. Typical consulting: 6-12 months, 150K+ fees, and a PDF.

CEO says "cloud-native by 2027." What does that mean for people?

With strategy as input, the system connects goals to gaps — quarter by quarter.

CEO Interview
"Migrate all infrastructure to cloud-native by Q4 2027."
Source: CEO AI interview, Jan 2026
Manager Interview
"My team can handle the application layer, but we have zero Kubernetes experience."
Source: Engineering Lead — confirms the gap
Employee Data
2 of 14 have Docker experience. 1 used Terraform before. 3 expressed interest in cloud/DevOps.
Gap confirmed from all three sides.
Actions
DEVELOP Q2: Cloud training for 3 internal candidates (L&D matched)
HIRE Q2: 2 Senior Cloud Engineers (job reqs generated)
HIRE Q3: 3 mid-level (briefing ready)
SCENARIO "All internal" = +5 months, -375K. "All external" = -5 months, +225K, market risk.

The AI becomes every manager's strategic partner

Managers don't just see dashboards — they interact with an AI that knows their team, their gaps, and their goals. Here's what that looks like across different challenges.

Recruiting
Transformation
Team Development
Project Staffing

Manager runs recruiting end-to-end

No more waiting for recruiters to coordinate. The manager handles briefing, reviewing, interviewing, and deciding — with AI support at every step.

1
AI Briefing: 20-min chat. AI asks structured questions, gives reality checks on requirements ("this combo = 120 candidates in DACH").
2
Internal First: System surfaces internal candidates before posting — including people who'd fit with training.
3
Interview Prep: Per candidate: AI generates a briefing with key questions, strengths to probe, and conversation guide.
4
Post-Interview: AI captures structured feedback. Candidate ranking updates dynamically after every conversation.
5
Decision: Candidates ranked by fit with all data aggregated. Manager decides with full picture.

What the manager gets

Realistic job requirements (no more unicorn wishlists)
Internal candidates surfaced before external search
Prepared for every interview — candidate-specific questions
Dynamic ranking that updates with each new data point
Self-sufficient — recruiter shifts from coordination to strategy

Manager navigates a transformation

Department restructuring, new technology adoption, market expansion — the AI helps the manager understand what their team can handle and what they need.

1
Strategy Chat: Manager describes the transformation goal. AI maps it to required capabilities.
2
Team Assessment: System shows which team members have relevant skills (from their interviews) and who's interested in the direction.
3
Gap Timeline: Visual: which capabilities are missing, when they become critical, and what the sources of each gap are.
4
Action Plan: Per gap: develop internally, hire, or borrow from another team. With costs and timelines for each option.
5
Scenario Simulation: "What if we develop all internally?" vs. "What if we hire?" — side-by-side comparison.

What the manager gets

Clear picture of team readiness for the change
Gaps traced back to specific strategic goals
Quarterly action plan — not a one-time slide deck
Cost and timeline comparison for every option
Data to justify headcount requests to leadership

Manager develops their team strategically

Not generic training catalogs — personalized development plans tied to team goals and individual career aspirations.

1
Team Overview: Manager sees each team member's profile: skills, career goals, development progress, and — where perspectives differ — what the employee thinks their role is vs. what the manager expects.
2
Gap Identification: Per person: where are they relative to their current role requirements? Relative to their career goal?
3
Development Plans: AI generates personalized plans with L&D matched to specific gaps. Quarterly milestones.
4
Progress Tracking: Completed training updates skills automatically. Manager sees who's on track and who needs support.

What the manager gets

Knows each team member's actual capabilities and ambitions
Spots where employee and manager see the role differently
Personalized development plans — not one-size-fits-all
L&D tied to business need: "this training closes that gap"
Retention signal: employees who see a path are less likely to leave

Manager staffs a project with the right people

Need specific skills for a 3-month project? The system finds them across the organization — including people you didn't know existed.

1
Define Need: Manager describes the project and required capabilities in a chat.
2
Cross-Team Search: AI searches across all departments for matching skills — based on deep interview data, not job titles.
3
Availability Check: Shows each candidate's current workload and their manager's contact info for loan discussions.
4
Temporary Assignment: System tracks the project loan. Skills stay with the person; both managers see the arrangement.

What the manager gets

Find talent in departments you've never talked to
Skill-based matching, not "who do I know" networking
Internal freelancer market — borrow before you hire
Cross-department collaboration that wouldn't happen otherwise

Less consulting. More clarity. Faster.

4 weeks

Full job architecture

AI-generated from interviews. Audit-ready for EU Pay Transparency. Replaces 6-12 month consulting projects.

15 min

Per employee interview

Richer profile than any form, survey, or CV parse. Async, pausable, no scheduling needed.

3x

Fewer mis-hires

Reality-checked requirements. Internal candidates first. AI-prepared interview guides for managers.

Always

Up to date

Proactive triggers: post-interview feedback, post-training updates, strategy refreshes, new hire onboarding. No manual maintenance.

A living system that keeps itself current

The AI proactively triggers the right conversation with the right person at the right time. Your data stays alive without anyone maintaining it.

New employee joins

Onboarding interview automatically sent. Profile built from conversation.

Interview completed

AI asks manager for structured feedback. Candidate ranking updates.

Training finished

Employee gives feedback. Skills update automatically in profile.

Strategy update due

Quarterly reminder to CEO/managers. Gap timeline refreshes.

Profile incomplete

HR dashboard shows gaps. One-click reminder via Teams/Slack/Email.

Reorganization detected

Affected role descriptions flagged for re-interview. Grading rechecked.

Six capabilities. One data foundation.

Start with one. The rest activate from the same interview data. Click any card for the full breakdown.

Strategic Workforce Planning

Connect goals to capabilities — with gap timelines and scenario simulations.
See full breakdown ↓

Internal Talent Marketplace

Show employees where they can go — before they look externally.
See full breakdown ↓

Learning & Development

Connect every training to a business gap. Measure ROI in avoided hires.
See full breakdown ↓

Compensation & Grading

Auditable job architecture in weeks. EU Pay Transparency ready.
See full breakdown ↓

Smart Recruiting

Managers run recruiting themselves. Recruiters become strategic.
See full breakdown ↓

People Analytics

Workforce KPIs as rigorous as financial ones.
See full breakdown ↓

Strategic Workforce Planning

Problem

CEOs decide on transformation and growth without knowing which capabilities exist. HR reports headcount but can't answer "can we execute this strategy?" Workforce planning happens in Excel, disconnected from actual skills, without timelines or action plans.

Solution

CEO defines strategy in an AI interview. Managers describe departmental needs. Employees describe their skills. The AI synthesizes all three into: skill landscape, gap analysis with sources, quarterly gap timeline, and concrete action plans — hire, develop, transfer, promote.

Key Features

  • Gap Timeline: which gaps emerge when, traced to which strategic goal
  • Scenario Simulation: "develop internally vs. hire externally" with costs and timelines
  • Workforce Alignment Score: strategy vs. current capability, tracked over time
  • Automatic position creation from identified gaps
  • Headcount projection: plan vs. reality over quarters

Business Case

Replaces: Quarterly Excel planning + strategy consulting engagements.
Value: Proactive gap closure instead of reactive firefighting. HR delivers measurable KPIs to the board for the first time. Transformation projects succeed because capability gaps are identified before they stall progress.

Process

1CEO/CHRO strategy interview
2Manager dept. interviews
3AI derives gaps over time
4Actions + scenarios generated

Example View

Gap Timeline showing Q2-Q4 with gaps traced to strategy goals, recommended actions per quarter, and scenario comparison.

Try the Prototype →

Internal Talent Marketplace

Problem

Internal job postings exist on intranets nobody checks. Employees don't know which roles fit them. Managers don't know which talent exists in other departments. High performers leave because they don't see internal paths. Project staffing is "who do I know" networking.

Solution

Employees see personalized internal matches with AI-generated explanations: "This fits because..." with strengths, gaps, and timeline to readiness. When interested, a qualifying chat deepens their profile for that specific match. Managers see cross-department talent for permanent moves or temporary project loans.

Key Features

  • Personalized match explanations: why this role fits, what gaps exist, time to readiness
  • Qualifying chat: deeper questions when an employee expresses interest
  • One-click internal application: auto-generated from profile data
  • Cross-team project staffing: temporary skill loans between departments
  • Mobility analytics for HR: blocked talent, transfer candidates, attrition risks

Business Case

Replaces: Intranet job boards + word-of-mouth transfers.
Value: Internal mobility up, attrition down. Each internal fill saves ~120K vs. external hire. Employees who see a career path stay. Cross-team project staffing unlocks hidden capacity.

Process

1Employee browses matches
2Qualifying chat deepens profile
3Application auto-generated
4Manager notified with match data

Example View

Employee sees 3 matched positions with strengths/gaps analysis, timeline to readiness, and one-click application.

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Learning & Development

Problem

Training catalogs exist but nobody knows which course closes which gap. L&D budgets are spent without connection to strategic goals. Development plans exist on paper or not at all. Managers don't know what development their team members need. No way to measure whether training actually reduced hiring needs.

Solution

Two modes: Employee-driven (explore interests, get matched courses) and strategy-driven (AI connects training to business gaps). Every development plan has quarterly milestones, matched L&D modules, and progress tracking. L&D Manager sees catalog gaps and demand patterns.

Key Features

  • Personalized development plans with quarterly milestones
  • L&D matching: courses matched to specific skill gaps
  • Post-training feedback: employees rate courses, skills update automatically
  • Strategic L&D view: "this learning path avoids 3 external hires (360K)"
  • Catalog gap analysis: where is demand but no course available?

Business Case

Replaces: Disconnected training catalogs + gut-feel development planning.
Value: L&D budget tied to measurable outcomes. "This path avoided 3 hires worth 360K" is a sentence you can take to a budget meeting. Employees develop towards real business needs, not random courses.

Process

1Employee/manager identifies goal
2AI matches L&D to gaps
3Plan with milestones created
4Progress tracked, skills updated

Example View

Employee development plan with skill bars (current vs. target), quarterly timeline, and L&D course recommendations with gap-closure reasoning.

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Compensation & Grading

Problem

Job architecture lives in spreadsheets or doesn't exist. Salary bands are intransparent. Equivalent roles are graded differently. Pay equity is checked manually or not at all. EU Pay Transparency Directive (2026) requires auditable criteria — most companies aren't ready.

Solution

AI interviews employees and managers about every role. From this data, the system generates a complete job architecture: function families, levels, salary bands. Every grading includes an audit-ready justification based on EU criteria. Pay equity is checked automatically — gender pay gap, band violations, anomalies flagged.

Key Features

  • AI-generated job architecture from interview data
  • Audit-ready justification per role (EU criteria: competencies, effort, responsibility, conditions)
  • Interactive org chart: functions x levels, click for detail
  • Pay equity dashboard with automatic flags and correction suggestions
  • HR drag-and-drop refinement of AI-generated structure

Business Case

Replaces: 6-12 month Mercer/Korn Ferry projects at 150K+ fees.
Value: Full EU Pay Transparency compliance in 4 weeks. Pay equity issues caught before they become legal risk. Consistent, defensible job architecture. Employees trust the system because it's transparent and justified.

Process

1Managers describe functions
2Employees describe roles
3AI generates architecture
4HR reviews + refines

Example View

Org chart by function and level with salary bands. Click any cell for employees, grading justification, and pay equity flags.

Try the Prototype →

Smart Recruiting

Problem

Job descriptions are wishlists disconnected from reality. Managers and recruiters understand the role differently. Internal candidates aren't checked before posting externally. Managers are unprepared for interviews. Decisions are subjective. The recruiter is a bottleneck for coordination, not a strategic partner.

Solution

AI briefs the manager with structured questions and reality checks ("this skill combo = 120 candidates in DACH — prioritize?"). Internal candidates surfaced automatically before external posting. Per candidate: AI-generated interview guide. Post-interview: structured feedback capture with dynamic candidate re-ranking. Manager becomes self-sufficient.

Key Features

  • AI job briefing with reality checks on market availability
  • Internal-first matching including upskilling scenarios
  • Candidate-specific interview guides with golden rules
  • Post-interview feedback → dynamic candidate ranking
  • Smart Apply: candidates chat instead of filling forms

Business Case

Replaces: Recruiter-bottlenecked pipelines + unrealistic job descriptions.
Value: Higher quality of hire. Shorter time-to-hire. Managers handle their own pipeline — recruiters shift to strategy. Internal fills save ~120K each. Candidate pool grows 3-5x when requirements are reality-checked.

Process

1Manager briefs via AI chat
2Internal + external candidates matched
3Interviews with AI prep
4Feedback → ranking → decision

Example View

AI briefing chat with reality check, internal candidate alert, and generated job requirement with must-have/nice-to-have split.

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People Analytics

Problem

HR data in HRIS systems is master data — name, department, salary. No skill data, no satisfaction trends, no gap projections, no strategic linkage. HR reporting is backward-looking (headcount, attrition rates) not forward-looking (which gaps emerge in 6 months?).

Solution

The system generates analytics automatically from interview data — no manual data entry. Skill heatmaps, radar charts (current vs. target), gap projections over time, attrition risk signals, headcount forecasts, DEI metrics. What-if scenarios let you simulate hiring vs. development decisions.

Key Features

  • Skill Heatmap: proficiency per skill per department
  • Radar Charts: IST vs. SOLL per department
  • Gap Projection: monthly forecast — when do gaps emerge, how are they closing?
  • Scenario Simulation: cost/timeline/risk comparison for strategic decisions
  • Workforce Alignment Score: strategy execution readiness, tracked over time

Business Case

Replaces: Headcount-only reporting that doesn't answer capability questions.
Value: HR delivers real KPIs to the board — comparable to Finance and Sales. Risks identified proactively. Strategic decisions backed by data, not gut feel. "Our workforce is 64% aligned to strategy" is a sentence that changes the conversation.

Process

1Interviews generate data
2AI aggregates + analyzes
3Dashboards auto-populated
4Scenarios + projections live

Example View

Firm-wide dashboard with skill heatmap, radar chart, gap projection bars, and scenario simulation panel.

Try the Prototype →

Same data. Tailored for every role.

Employees

See your profile, career options, internal matches. Build development plans. Apply internally with one click.

"3 roles match you. For the Data Engineer position, you'd need 4 months of training — here's the path."

Managers

See your team's real capabilities. Create positions from gaps. Run recruiting yourself with AI support.

"Your requirements match 120 candidates. Drop the SaaS requirement and you reach 2,400."

HR

Firm-wide analytics. Compliant grading. L&D with ROI. Profile completeness tracking. Trigger management.

"This learning path avoids 3 external hires. Net savings: 360K."

Leadership

Define strategy in a conversation. See if the workforce can deliver. Simulate scenarios. Track alignment.

"Your AI strategy needs 12 capabilities you don't have. Here's the plan and cost of each option."

Interactive prototypes — click through the product

Each prototype shows a real use case with realistic data. Open in your browser.

Workforce Planning Learning & Dev Talent Marketplace Grading AI Recruiting People Analytics

We add the intelligence. You keep your stack.

Bidirectional. Import master data, export enriched profiles. Chat via Teams, Slack, or web.

WorkdaySAP SuccessFactorsPersonioBambooHRGreenhouseLeverTeamsSlackCustom API

See what your workforce actually looks like

30-minute demo. You'll experience the AI interview yourself, see the synthesis in action, and walk through concrete action chains. Bring your hardest workforce question.

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