AI agents
Letting non-technical users query steering metrics, with lineage
AI assistant
Natural-language questions over the validated ontology, with the definition and origin of every KPI on demand.
The engagement: existing, as built, in production
Existing
The challenge
After the portfolio steering rollout, users needed a self-service way through complex portfolio metrics, financial KPIs and documentation. Dashboards demanded manual filtering and a knowledge of data lineage, slowing decisions and leaving non-technical users dependent on others.
As built
What we built
- An ontology-driven assistant integrated with the validated enterprise ontology, so answers follow the governed data structures
- Natural-language querying for portfolio figures, on-the-fly calculations and trend insights
- An embedded guide explaining KPI definitions, data origins and documentation, for auditability
In production
The impact
- Managers check the origin and logic of a KPI conversationally, with no manual lineage tracking
- From static reports to dynamic, ad-hoc analysis
- Support overhead reduced through automated onboarding and documentation navigation
Plain language
over the validated ontology
Existing
The challenge
After the portfolio steering rollout, users needed a self-service way through complex portfolio metrics, financial KPIs and documentation. Dashboards demanded manual filtering and a knowledge of data lineage, slowing decisions and leaving non-technical users dependent on others.
As built
What we built
- An ontology-driven assistant integrated with the validated enterprise ontology, so answers follow the governed data structures
- Natural-language querying for portfolio figures, on-the-fly calculations and trend insights
- An embedded guide explaining KPI definitions, data origins and documentation, for auditability
In production
The impact
- Managers check the origin and logic of a KPI conversationally, with no manual lineage tracking
- From static reports to dynamic, ad-hoc analysis
- Support overhead reduced through automated onboarding and documentation navigation
Plain language
over the validated ontology
The same problem elsewhere
The same assistant sits on any governed set of operational metrics: plant KPIs, network performance, service levels, clinical indicators.
- Insurance & reinsurance
- Portfolio and performance metrics queried in plain language, with the definitions to hand.
- Manufacturing & engineering
- Plant and supply KPIs asked for in plain language by people who never open the dashboards.
- Healthcare & life sciences
- Operational indicators queried by clinical and management staff without a report request.
- Public sector
- Service and performance metrics answered for policy teams, with the source behind each number.
More in AI agents
Bring us the version of this you are living
Every engagement here started as somebody’s stuck programme. Tell us where yours stands.
contact@ainurinsights.com