Government and school leaders are ready to use AI — but finance, IT, and management teams need confidence that the data is clean, classified, permission-aware, and supported by evidence. ThirdLine prepares the ERP data. Madison AI turns it into secure, useful answers.
Madison AI can respond using ERP data that ThirdLine has cleaned, classified, permissioned, and connected to source evidence — so finance and leadership teams can move faster without skipping controls.
Most public-sector AI conversations start with a chatbot. Finance and IT leaders know the harder question: should AI be allowed to answer from raw ERP data when vendors are duplicated, accounts are misclassified, permissions are unclear, and audit evidence is scattered?
The joint solution helps governments and schools create a controlled path from ERP data to AI answers — with preparation, classification, access rules, and source evidence built in before users start asking questions.
Duplicate vendors, inconsistent accounts, stale records, and weak classifications can lead to confusing or misleading AI outputs.
Department heads, AP staff, auditors, IT, and executives should not all see the same finance data.
Finance teams need answers tied back to source ERP records, classifications, approvals, and documentation.
Policies alone are not enough. Data needs to be cleaned, tagged, monitored, permissioned, and refreshed.
This version of the partnership story is designed to resonate across finance, IT, and executive management — because successful AI adoption has to satisfy all three.
Get faster answers from budget, accounting, procurement, AP, contracts, and audit data without losing control of the underlying numbers.
Give users AI access without connecting a general-purpose assistant directly to raw ERP exports or uncontrolled sensitive data.
Ask plain-English questions and get clearer visibility into the financial story behind operations, programs, departments, and priorities.
ThirdLine and Madison AI create a simple, practical operating model for government AI: prepare the data, control the access, then let AI help people ask better questions.
Budget, GL, AP, procurement, vendor master, requisitions, contracts, payroll, grants, projects, policies, and audit support.
Clean, classify, tag, permission, risk-score, monitor, and document ERP data before it becomes a source for AI.
Ask plain-English questions, generate summaries, draft reports, explain trends, and retrieve answers from approved government knowledge.
The easiest entry point is usually a practical finance use case — then expand into agents that use the same clean, classified ERP foundation.
Explain variances, compare funds and departments, generate narratives, and answer leadership questions.
Organize support, summarize exceptions, prepare auditor responses, and preserve source evidence.
Help finance teams gather support, draft schedules, explain changes, and reduce year-end reporting friction.
Connect requisitions, POs, vendors, contracts, thresholds, renewals, and compliance questions.
Instead of trying to launch every AI use case at once, start with one approved ERP data area — usually Budget-to-Actual, AP/Vendor, Procurement/Contracts, or Audit Readiness — and show leaders what trusted AI can look like.
Pick the finance workflow with the clearest pain and highest visibility.
ThirdLine cleans, tags, maps, permissions, and creates evidence around the data.
Madison AI enables users to ask questions and generate useful finance outputs.
Add procurement, audit, ACFR, close, AP, grants, payroll, or school finance use cases.
ThirdLine and Madison AI help governments and schools turn ERP data into secure, controlled, and audit-ready answers — without asking finance or IT teams to accept AI on faith.