Candice AI provides an enterprise-grade document intelligence platform designed to establish a trust layer for AI deployments. The platform ensures verifiable output through full traceability, precision in data extraction, and data sovereignty via on-premise or private cloud deployment options. This enables organizations to automate workflows and accelerate decision-making using reliable, auditable intelligence derived from complex document corpora.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying large language models (LLMs) often encounter unreliable outputs, fabricated facts, and a lack of traceability, which creates regulatory risk and hampers decision‑making. Additionally, many organizations cannot guarantee data sovereignty when processing sensitive documents in the cloud.
Solution
Candice AI delivers an enterprise‑grade document intelligence platform that acts as a trust layer for AI workflows. The system ingests entire document corpora, extracts structured information, and automatically attaches source citations and confidence scores to every datum. A built‑in verification engine generates a complete audit trail, enabling human oversight and compliance reporting. Deployments can run on‑premises or in a private cloud, ensuring that no data leaves the organization’s infrastructure. The platform exposes a RESTful API and a Model Context Protocol (MCP) so AI agents and downstream applications (BI, ERP, CRM) can consume verified intelligence in real time. By providing total recall, full traceability, and sovereign data control, Candice AI makes AI‑augmented decision‑making reliable at scale.
Target Audience
The platform targets large enterprises in finance, legal, procurement, healthcare, insurance, and other regulated sectors that need trustworthy AI‑driven document analysis and compliance‑ready auditability.
Features
- Ingestion engine that processes unlimited volumes of documents of any size, preserving full field coverage.
- Orchestrated processing pipeline with smart‑tuning and ML verification to detect and flag fabricated facts.
- Automatic source citation and confidence scoring for each extracted entity, supporting risk‑based decision frameworks.
- End‑to‑end audit trail that links every output back to its originating document fragment.
- On‑premise or private‑cloud deployment options guaranteeing data residency and regulatory compliance.
- RESTful API and Model Context Protocol (MCP) for seamless integration with AI agents, BI tools, ERP, CRM, and other downstream systems.
- Configurable rule engine allowing custom business logic and compliance policies to be applied during extraction.
- Enterprise‑grade security controls, including role‑based access, encryption at rest and in transit, and audit logging.