Our vision
Create a future where every business can build a healthy, inclusive, and high-performing workplace using secure, responsible, and explainable HR intelligence — to strengthen organisational culture, create meaningful opportunities for people, support sustainable business prosperity, and scale with confidence through better human-led decisions.
Screen, calculate, trigger, deep dive, monitor
We do not ask every company for everything. We collect a small universal diagnostic dataset, run the core analysis, and request additional evidence only when the first stage gives a reason to ask.
Screen
Collect the core dataset only: roster, structure, role expectations, performance, commitment, attendance, relationships, workload and company metrics.
Calculate
Run the deterministic formula engine — performance, commitment, engagement, attendance, workload, structure and preliminary risk.
Trigger
Identify which issue genuinely needs more evidence, rather than collecting data speculatively.
Deep dive
Request only the relevant additional category: incidents, training, promotion, compensation, engagement or recruitment.
Diagnose
Validate the hypothesis against evidence, contradictory information and the employee's own account before it becomes a finding.
Monitor
Create the plan, KPIs, alerts and review timeline, then measure at day 30, 60, 90 and 180 whether the issue actually improved.
Sixteen categories, one connected picture
Every data point is documented: why it is needed, what it can and cannot tell you, and the governance caution that goes with it.
Core — for every company
- Company profile & company metrics
- Employee master & organisational structure
- Role expectations and KPIs
- Performance, commitment and attendance
- Relationships, engagement and workload
- Data quality and evidence
Case-by-case — when triggered
- Incidents, grievances and feedback
- Training and development
- Promotion and career movement
- Compensation and rewards
- Full engagement survey
- Recruitment and onboarding
A scenario is a hypothesis, not a verdict
The platform can tell you that an employee's performance and commitment have both fallen while incidents recur. It will not tell you what to do about that person. It states the hypothesis, names the evidence that would confirm or contradict it, and refuses to let the case advance until a human has checked the evidence, recorded the employee's response, and written a conclusion of their own.
Evidence before conclusion
Approved leave, health context, workload transfer and tooling gaps are shown next to the score that they explain.
Confidence, stated plainly
One person's opinion on stale data is labelled low confidence, and low-confidence evidence cannot drive a high-stakes conclusion.
Fairness checked first
Aggregate outcome differences pause the process for human review. They are never applied to an individual.
Let's talk about your workforce
Explore the platform, book a demonstration, or discuss what your organisation needs.
Get in touch