Explainable Forecasts
Every variance traceable to its specific driver. CRM shift, ERP delay, or macro pivot. No black boxes.
The problem
We spent 3 days prepping and still couldn't explain the Enterprise variance.
Forecast prep is dominated by reconciliation, not reasoning. The answer you need is buried in 14 tabs.
Finance and sales are running off different numbers again.
Shadow spreadsheets, stale ERP exports, and manual handoffs mean every team has a slightly different truth.
By the time we surface the insight, the pivot window has already closed.
Decision latency is the silent tax on FP&A. Insights that arrive a week late aren't insights. They're history.
I can't audit how the model got to that forecast.
Black-box outputs are trust killers in finance. If your CFO can't trace the logic, the number gets challenged every time.
InSightOS — The Decision OS for Finance
From raw data to
board-ready decisions.
In the same session.
InSightOS connects your ERP, warehouse, and CRM. Then it surfaces variance drivers, explains forecast shifts, and lets your team approve changes with full audit lineage.
Scenario Simulation
"What if headcount deferred 60 days?" answered in seconds, not a four-hour model rebuild.
Causal Variance Attribution
Agents separate structural and seasonal drivers so your team sees what moved, why it moved, and what needs action.
Decision Memory
Every approved change logged with full reasoning and audit-ready context for SOX, board reviews, and diligence.
What changes
Before and after
InSightOS.
✕Forecast reviews turn into spreadsheet debugging sessions
✕Hours lost chasing why EBITDA moved 200bps
✕Finance and sales running off different numbers
✕Analyst time: 70% reconciling, 30% thinking
✕Board asks for variance explanation — takes 2 days
After InSightOS
✓Variance explained before the meeting starts
✓Every number traceable to source in one click
✓One source of truth across ERP, CRM, and warehouse
✓Analysts own strategy, not data cleanup
✓Decisions move forward in the same session
The data backbone
Meet Loktak.
The layer InSightOS is built on.
Most AI gets the answer wrong because the data was wrong first. Loktak ingests, cleans, and structures your financial data before InSightOS reasons over it, so every answer arrives grounded, traceable, and ready to defend.
Deterministic before probabilistic
Same pipeline in, same canonical output, always.
Auditable before optimised
Every transformation writes to an immutable lineage ledger.
Finance trust over AI cleverness
A CFO needs to sign off on it. Explainability first.
Integrations
Connect to any API
in under a minute.
Pre-built connectors for every major ERP, CRM, and data warehouse. Custom API? Loktak maps it to the canonical finance schema with no engineering sprint required.
Why PhrasIQ
Not a dashboard. Not a co-pilot.
A decision layer.
Three things that separate InSightOS from every other AI finance tool, built into the architecture, not bolted on.
The Loktak data backbone
Deterministic, auditable, versioned before any agent runs. Every transformation rule-based. Every number traceable to source.
C-Score grounding engine
Every output verified against source data before it reaches you. No hallucinated numbers. Grounding scores above 0.99 as standard.
Decision memory + audit trail
Every approval logged with reasoning, data version, and confidence. SOX-ready export. Gets sharper with every decision cycle.