CDSI

CDSI provides an applied agentic AI platform that enables teams to train their own AI agents or deploy ready‑made systems for complex workflows. Its multi‑agent development suite includes advanced memory architectures and human‑in‑the‑loop approval patterns, allowing organizations to build and manage AI‑driven processes with control and transparency.

Updated 1 month ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Organizations that need to automate complex, multi-step workflows often lack tools to create, coordinate, and govern AI agents with sufficient control, transparency, and scalability. Existing solutions typically require extensive custom development or provide limited oversight, leading to operational risk and difficulty in maintaining reliable AI-driven processes.

Solution

CDSI delivers an applied agentic AI platform that lets teams either train custom AI agents or deploy pre‑built systems for intricate workflows. The platform’s multi‑agent development suite incorporates advanced memory architectures that enable agents to retain and retrieve contextual information across interactions. Built‑in human‑in‑the‑loop approval patterns provide checkpoints for oversight, ensuring that critical decisions are reviewed before execution. Production‑grade governance primitives enforce policy compliance, auditability, and transparent operation of AI‑driven processes. By offering a library of over 50 modular tools, CDSI allows organizations to rapidly assemble, test, and manage AI agents while maintaining full control over their behavior.

Target Audience

Primary customers are enterprise AI teams, data science and machine‑learning departments, and product groups that need to build, deploy, and govern AI‑driven workflow automation at scale.

Features

Multi‑agent development environment with over 50 modular MCP tools for rapid workflow assembly
State‑of‑the‑art memory systems enabling persistent context and long‑term knowledge retention across agent interactions
Human‑in‑the‑loop approval workflows that insert manual review steps at configurable decision points
Production‑grade governance primitives for policy enforcement, audit trails, and transparent agent behavior
Capability to train custom agents or deploy ready‑made agents for a variety of complex business processes
Integrated monitoring and analytics dashboards for real‑time visibility into agent performance and outcomes