Platform · AI × BI Flywheel™
Your BI already knows the business. Now let it think.
Most platforms give you a report. SplashBI gives you a loop. The same governed data that powers your dashboards grounds your AI. Every question you ask surfaces sharper next steps, so the loop gets more useful the more you use it, without the model ever training on your data.
Platform context
Where this fits in the platform
Without governed, aggregated data, the AI has nothing to reason over. Without AI, Cross-Domain Intelligence is a dashboard rather than a conversation.
The AI × BI Flywheel™ is Pillar 2. It connects the data foundation (Data Aggregation) to the decision layer (Cross-Domain Intelligence). All three pillars are available independently, but the value compounds when they run together.
Why this matters
Built to be trusted, transparent, and yours
01
Grounded in your governed data
Answers from your data, not approximations
SplashAI runs on your governed ERP and HCM data, the same model that powers your reports, so answers reflect your actual numbers, not a generic estimate or a guess pulled from outside your business. When the AI tells you AR is up, it is reading your AR, mapped through the same definitions your finance and HR teams already trust.
02
Every answer shows its SQL
Every answer shows its work
SplashAI doesn't ask you to take its word for it. Every response exposes the SQL behind it and drills through to the source transaction, so your team can see exactly how a number was reached. The AI explains; your people decide. That transparency is what makes the output safe to act on, and easy to defend when someone asks where a figure came from.
03
Never trains on your data
Your data stays yours
SplashAI never trains on your data. Your numbers are never used to improve a shared model and never leave your governed boundary. Role-based access controls apply at the AI layer, so users only see what their permissions allow, and PII is masked before anything reaches the model. The intelligence comes from the structure of your data, not from the model learning your secrets.
The problem
The gap between dashboards and decisions
You have invested in BI. You have reports, dashboards, and data warehouses. Your team still waits on analysts for answers. Anomalies surface at month-end, not when they can be acted on. Cross-functional questions - headcount versus budget, AP variance versus plan - take days to answer because the data lives in separate systems and separate people.
The problem is not the data. The problem is that BI was built to report what happened. Nobody told it to detect what is happening now, or predict what comes next.
Speed
Natural language queries against live ERP and HCM data. No tickets. No analyst queue. No SQL.
Detection
Proactive anomaly alerts across Finance and HCM before period close, not after.
Compounding value
Persistent memory of your business context. The longer you use it, the faster and more precise it gets.
What the flywheel does
BI provides the foundation. AI provides the leverage
Most AI tools fail in the enterprise because they are disconnected from the data that actually runs the business. They approximate. They hallucinate. They produce answers nobody can verify.
SplashAI works differently. It is grounded in your governed, aggregated ERP and HCM data from day one. Every answer it generates cites the source table, the time period, and the SQL behind the result. Your team decides. The AI explains.
The flywheel effect is real: each question builds organizational context. SplashAI learns your cost center hierarchy, your anomaly thresholds, your definitions. By month six, it is surfacing the questions you did not know to ask.
The agents
Finance and HCM agents, built for Oracle environments
Finance Agents
Accounts PayableAccounts ReceivableGeneral LedgerFP&A
Ask natural language questions against live ERP data. Surface GL variances before close. Detect duplicate payments and AP anomalies automatically. Run FP&A scenario modeling in a conversation rather than a spreadsheet.
HCM Agents
RecruitingTalent ManagementWorkforce PlanningTime and Attendance
Query headcount and attrition in plain English. Detect time and attendance anomalies before payroll runs. Identify talent gaps by department. Correlate workforce cost against Finance actuals without a data request.
Cross-Domain
Finance × HCM, on one governed layer
When Finance and HCM data share the same governed layer, SplashAI can answer the questions that span both. Headcount cost versus departmental budget. Attrition impact on project delivery. The answers that live between silos.
How it works
Three steps to your first AI answer
01
Connect
SplashAI connects to your existing SplashBI data layer. No new data warehouse. No replication. If your BI already runs on it, the AI can reason over it.
02
Ask
Your Finance or HCM team asks a question in plain English. SplashAI queries your governed data, shows the SQL, and returns the answer with a citation trail your auditors can follow.
03
Learn
Every interaction adds to the system's understanding of your business: your terminology, your thresholds, your preferred analysis patterns. The flywheel starts spinning from day one.
Objections
The questions every CDAO asks before signing
General LLMs do not know your chart of accounts, your cost center hierarchy, or your HCM data model. SplashAI is built on Oracle ERP and HCM schemas and grounded in your actual data. The difference is accuracy versus approximation.
Value over time
An asset that appreciates
Most AI tools are static. SplashAI improves.
Each interaction builds organizational context: your definitions, your anomaly thresholds, your preferred views of the business. By year two, the AI layer is an institutional asset, not a replaceable software subscription.
Capabilities
What powers the flywheel
Natural language query against live ERP and HCM data (Text2SQL with full transparency)
Proactive anomaly detection: AP, AR, GL, payroll, and workforce
FP&A scenario modeling via conversational interface
Cross-domain Finance and HCM correlation
Persistent conversational memory with org-specific context
RAG-grounded responses with source citation on every answer
Human-in-the-loop feedback that sharpens accuracy over time
Governance
Governance is not an add-on
RBAC at the AI layer
Role-based access controls enforced at the AI layer, not just the report layer.
PII masking
PII masking applied before data reaches the AI model.
Never trains on your data
SplashAI never trains on your data. Your data stays yours.
Tenant isolation
Tenant isolation on Oracle Cloud Infrastructure.
Full access logging
Full audit logging of every AI query and response.
These are not settings you configure. They are built into the platform by default.
Role cards
What it changes for your leadership team
SplashAI surfaces GL variances and AP anomalies before your team finds them in reconciliation. Ask the questions you used to wait three days to answer.
Customer evidence
Organizations running SplashBI today
Healthcare
3x ROI
A multi-hospital health system
Consolidated Finance reporting across five source systems. Their FP&A team moved from three-day variance analysis cycles to same-day anomaly detection. Achieved 3x ROI with 70%+ adoption across Finance users in the first year.
Fast path
If you are already on SplashBI, we can have SplashAI in front of your Finance team this week.
Never trains on your data · RBAC enforced
Start the flywheel
SplashAI is live with Finance and HCM agents today. If your team is still answering business questions manually, that is the gap we close.
Never trains on your data·RAG-grounded·RBAC enforced·SOC 1 / SOC 2