nForce AI provides a compliance‑first, explainable AI platform that detects financial fraud and operational anomalies across disparate public‑sector data sources. By integrating and normalizing data from multiple government systems and applying hybrid supervised/unsupervised models with a knowledge‑graph validation framework, it delivers real‑time, audit‑ready alerts with low false‑positive rates. The solution can be deployed on cloud, on‑premises, or hybrid environments and meets federal security standards such as FedRAMP, CMMC, and NIST.
Funding
Funding not disclosed
Founders
Product
Problem
Government agencies lose billions of taxpayer dollars each year to fraud, waste, abuse, and improper payments, while legacy audit tools generate high false‑positive rates, miss cross‑system anomalies, and lack the transparency required for statutory compliance.
Solution
nForce AI offers a compliance‑first, explainable AI platform that detects financial fraud and operational anomalies across disparate public‑sector data sources. The system aggregates and normalizes data from core state systems and external datasets, then applies a hybrid of supervised and unsupervised machine‑learning models enhanced by the Better Retrieval‑Augmented Generation (BRAG) framework to deliver hallucination‑free, real‑time alerts. Human‑in‑the‑loop validation ensures every flagged event is audit‑ready and traceable to its data origin. The platform can be deployed on cloud, on‑premises, or in hybrid environments and meets CMMC, FedRAMP, NIST, ISO, and other federal security standards. By automating detection and providing clear, explainable insights, agencies can move from manual reviews to actionable intelligence, reducing false positives, accelerating investigations, and protecting public funds.
Target Audience
Primary customers are federal, state, and local government agencies responsible for financial oversight, procurement, tax collection, and citizen services, as well as managed‑service providers supporting public‑sector compliance.
Features
- Scalable data integration and normalization across multiple government systems (MFMP, FLAIR/PALM, FACTS, VIP, STMS, SunBiz, PCard) and enrichment with federal, public, and commercial datasets
- Hybrid AI engine combining rule‑based business logic with supervised and unsupervised learning for fraud, tax evasion, money‑laundering, and procurement abuse detection
- BRAG framework that validates AI outputs against a verified knowledge graph, eliminating hallucinations and ensuring data‑driven alerts
- Real‑time anomaly detection with millisecond‑level alerting and dynamic risk scoring
- Explainable AI reports that provide traceable evidence for each flagged anomaly, supporting audit and regulatory review
- Human‑in‑the‑loop workflow that routes alerts to subject‑matter experts for validation and documentation
- Flexible deployment options (AWS GovCloud, on‑prem, hybrid) with FedRAMP‑ready, CMMC, ISO 27001, ISO 27701, and PCI DSS compliance
- Interactive dashboards and visualizations for investigators, including drill‑down views, trend analysis, and automated workflow integration