ServeusAI's Minerva platform uses domain‑trained AI agents to automatically locate, preprocess, and extract structured data from unstructured documents such as reports, disclosures, and referral letters. The system delivers regulatory‑grade accuracy through real‑time validation and a human‑in‑the‑loop review, outputting data marts that integrate with ERP, CRM, and BI tools for finance, sustainability, and healthcare organizations.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations in regulated industries spend extensive expert time manually extracting and structuring data from unstructured documents such as annual reports, sustainability disclosures, and patient referral letters, leading to high labor costs, error risk, and delays in compliance reporting and decision‑making.
Solution
ServeusAI delivers the Minerva platform, an agentic AI system that combines domain‑specific knowledge with advanced natural‑language processing to automate end‑to‑end data extraction. The platform identifies relevant source documents, preprocesses them, and extracts key fields into structured, analytics‑ready data marts. Built‑in validation and a human‑in‑the‑loop review step ensure regulatory‑grade accuracy, while the output can be integrated directly into internal systems or BI tools. By offloading repetitive extraction tasks, the solution reduces expert effort, minimizes errors, and accelerates reporting cycles across finance, sustainability, and healthcare use cases.
Target Audience
Primary customers are financial institutions, sustainability reporting teams, and healthcare/pharma organizations that need to transform large volumes of unstructured documents into reliable, regulatory‑compliant data sets.
Features
- Domain‑trained extraction agents that apply expert‑curated prompts to achieve high precision on industry‑specific data points.
- Automated source selection and document collection, enabling continuous ingestion of public and internal data feeds.
- Pre‑processing pipeline that normalizes varied file formats (PDF, scanned images, HTML) and applies OCR where needed.
- Structured output generation into configurable data warehouses or data marts, ready for downstream analytics.
- Real‑time validation engine with confidence scoring and automatic flagging of low‑certainty records for human review.
- Human‑in‑the‑loop verification interface that allows users to correct or confirm extracted values, feeding back into model refinement.
- Audit‑trail and compliance reporting features that log extraction decisions and validation actions to meet regulatory standards.
- Scalable cloud architecture with API‑based integration into ERP, CRM, and BI platforms, supporting both on‑premise and SaaS deployments.