Connect your operational data
Start with the structured files you have. NaraOps can work with current-state data, repeated event histories or dated snapshots, then link related sources and approved document extractions where they add useful evidence.
Open-work snapshots
Multiple dated exports of the same open population over time. CSV and Excel (.xlsx) are supported.
Related data sources
Add analyst activity, quality results or another structured dataset. NaraOps checks how reliably each source joins to your work items before using it.
Snapshot mapping
NaraOps suggests how your columns map to its internal model. Check the required fields, then build the workspace.
| NaraOps field | Your column | Used for |
|---|
Related-source relationships
Choose what each source represents and confirm the field that links it to the work-item population. Match coverage is shown before the data influences analysis.
File guidance
Include the report date in each filename as YYYY-MM-DD or DD-MM-YYYY, e.g. Open_Work_2026-09-11.xlsx.
For .xlsx files with several sheets, NaraOps lets you choose the sheet to analyse. Old binary .xls files should be saved as .xlsx or CSV first.
CSV and Excel rows stay in your browser. Ask NaraOps receives compact verified analytical evidence rather than raw spreadsheet rows. A PDF, image or document leaves the browser only when you explicitly choose Extract, and its proposed values require review and approval before analysis.
What needs your attention
Build a workspace first.
Build a workspace to create your decision brief.
NaraOps will separate the main management problems and quantify the response where the data supports it.
Build a workspace to create your management brief.
NaraOps will turn the latest movement into a plain-English operational story.
What's going well
What isn't going well
Top risks
Prioritised by deterioration, materiality, ageing, SLA, priority/value exposure and linked evidence when available.
Interrogate the verified evidence
The AI receives a verified analytical summary — not your raw files.
Understand what is driving performance
Change the timeframe or focus on a client, team or work type. Every report recalculates from the local workspace.
Backlog & ageing trend
Arrivals vs likely cleared
Ageing composition
What is driving the movement?
Compare how the selected driver changed across the timeframe.
Selected evidence
Turn insight into action
Actions stay locally on this device. Use them to capture what you decided to do and compare the next period.
Recommended actions
Create action
Action register
Did it work?
Actions can now be tied to a specific priority population. When a newer snapshot is loaded, NaraOps compares that population with the baseline you acted on rather than only looking at the whole operation.
Prepare the conversation, not just the report
Generate a brief for leadership, the overall operation, a team, a 1:1 or a client. Each brief compares the selected reporting window with the full history, actions, targets and relevant comparison context.
Audience & scope
The selected subject stays identifiable. Comparison groups can be named, anonymised or reduced to a benchmark.
Tell NaraOps what represents people, teams and clients
NaraOps suggests these from your mapping, but you can change them for briefing purposes without changing the analytical model.
Is the evidence safe to brief from?
What are we trying to achieve?
Targets let NaraOps say whether the operation is on or off track rather than only describing movement.
Add context the data cannot know
Record events such as outages, holidays, onboarding, staffing changes or interventions so the next briefing has operational context.
Previous briefing cycles
Saving a cycle gives the next brief something to compare against: what changed, what actions existed and whether the operation moved in the intended direction.