Six systems.
One operating model.
Nash is not a chatbot layered over a planning tool. It is six systems sharing one model, one set of dimensions and one audit trail.
Six systems.
One operating model.
Decision System
Understands the business — P&L, Balance Sheet, Cash Flow as one model with variance, drivers, and drill-down to source of truth.
Continuous Planning
Keeps it current — driver-based planning, scenarios, what-ifs and continuous recomputation across the model.
Agentic Execution
Turns intent into action. Ask in plain English; the system plans, drafts, confirms and commits.
Audit & Control
Every change trustworthy — before/after on every write, full history, traceability and role-based control.
Data Foundation
Holds it together — multi-entity, multi-currency, shared dimensions, consistent computation everywhere.
Integrations
Connects Nash to your data — APIs, SFTP, CSV, Excel, validated on every run with full run history.
Together, these systems operate as one — multi-entity, continuously computed, fully auditable. No handoffs. No sync issues. No rebuilds.
Try with your dataHow they fit
Six systems, one write path.
The Decision System holds P&L, Balance Sheet and Cash Flow as one model rather than three reports, so asking why a line moved returns an answer that traces to the transactions that moved it. Continuous Planning keeps that model current — change a headcount assumption and runway, burn and EBITDA update without a rebuild.
Agentic Execution turns intent into action, but it works through the same write path a person does. There is no side channel and no unlogged edit: whatever the agent does is staged, shown, and only then committed.
Audit & Control is what makes that safe to run. Every write stores its before value, after value, actor and timestamp, and nothing the agent proposes reaches the model until a user confirms it.
Underneath, the Data Foundation is multi-entity and multi-currency by construction, so an entity view and a consolidated view are two reads of the same numbers rather than two builds. Integrations connect it to your sources — REST, SFTP, CSV and Excel — validated on every run, with full run history so a bad load is visible before it reaches a report.
FAQ
About the agent
Can the AI change my numbers without me knowing?▾
No. Agent-initiated changes are staged as drafts. You see the before value, the after value and the reasoning before anything is written, and the commit is an explicit action. Every committed write is attributed and timestamped in the same audit trail as a manual edit.
What stops the agent from inventing a figure?▾
The agent reads and writes through the same computation path as the rest of the system rather than generating numbers itself. Figures it reports are drawn from the model and drill back to source rows.
Who can commit changes?▾
A change is only written when a user confirms it, and the audit trail records who confirmed it and when. Splitting that into separate draft and approve permissions — so an analyst prepares a change that only an approver can write — is on the near-term roadmap rather than shipped today.
Does it work across multiple entities and currencies?▾
Yes — both are dimensions of the same model, so FX translation and entity roll-ups are applied consistently to planning, reporting and variance alike.
Watch the agent work on your model.
Fifteen minutes, your data, no slides. You'll see a draft raised and committed end to end.