ThirdLine and Madison AI are bringing clean, classified, permission-aware ERP data into a secure AI workspace so governments and schools can ask better questions, get faster answers, and trust the evidence behind every response.
Government finance, accounting, procurement, payroll, audit, and reporting teams live inside ERP data every day. But AI should not be connected directly to duplicated vendors, misclassified accounts, stale permissions, scattered audit support, or inconsistent reporting categories.
Madison AI brings a secure, purpose-built AI workspace for local government knowledge work. ThirdLine acts as the ERP AI Control Layer: cleaning, classifying, tagging, permissioning, risk-scoring, monitoring, and evidencing the ERP data before AI uses it.
Budget, general ledger, AP, vendors, procurement, contracts, payroll, roles, reports, and school finance data.
Clean up. Classify. Control. Provision. Risk-score. Monitor. Create evidence behind the AI answer.
Ask plain-English questions, search trusted knowledge, draft reports, prepare memos, and support faster government work.
Start with one high-value ERP domain, then expand as your data becomes cleaner, classified, governed, and ready for more AI agents.
Ask what changed, why it changed, which departments are driving variance, and what needs attention before month-end or council review.
Connect year-end reporting, indicators, supporting schedules, and narratives to the source data behind them.
Organize support, source references, review history, exception status, and evidence packages before auditors ask.
Surface duplicate payments, vendor risk, high-risk invoices, stale vendor records, and policy exceptions before AI explains spend.
Map spend to contracts, monitor thresholds, flag expiring terms, and answer procurement questions with data and policy context.
Translate ERP roles, funds, departments, accounts, and permissions into safer AI boundaries for each user group.
Track close items, unusual balances, reconciliations, journal entries, and outstanding work across accounting teams.
Support fund accounting, grants, payroll-sensitive questions, procurement, budget narratives, and board-ready reporting.
Forecasting, budget book, grant compliance, payroll controls, policy monitoring, continuous audit, FOIA, and more.
Your AI is only as trustworthy as the ERP data behind it.
Many governments can begin with a focused pilot around budget-to-actual, AP/vendor risk, procurement/contracts, ACFR support, or audit readiness. As the ERP data layer matures, new Madison AI agents can be powered by the same clean, classified, permission-aware foundation.
Identify data quality gaps, sensitive fields, classification needs, and permission boundaries before AI expands.
Activate one high-value model such as Budget-to-Actual, Procurement & Contracts, AP/Vendor Risk, or Audit Readiness.
Add agents across budget book, forecasting, ACFR, close, grants, procurement, contracts, payroll controls, and audit.
Schedule a joint Madison AI + ThirdLine conversation to explore your first government finance AI use case.
Suggested first pilots: Budget-to-Actual, AP & Vendor Risk, Procurement & Contracts, ACFR support, Audit Readiness, and AI Access Controls.
That is the point. ThirdLine prepares the ERP data first by cleaning, classifying, tagging, permissioning, and documenting it. Madison AI then uses that prepared data inside a secure AI workspace, so your government can start with trusted use cases without waiting for a perfect ERP cleanup project.
No. The starting point is identifying what needs to be cleaned, classified, tagged, permissioned, and monitored before AI relies on it.
Yes. Start with a focused pilot in one ERP domain, then expand to additional agents as value is proven.
Because ERP answers often involve sensitive data, audit evidence, budget classifications, fund/account restrictions, policy logic, and role-based access decisions.