Systemores provides enterprise‑grade Model Context Protocol (MCP) servers that run locally within a company’s infrastructure, enabling internal AI agents in IDEs, data pipelines, and operations dashboards to query real‑time behavioral vectors without exposing sensitive API keys. Their API‑first platform integrates a deterministic behavioral engine that delivers predictive operation signals, cohort alignment metrics, and habit‑vs‑cognitive‑drag detection, turning interaction data into measurable “behavioral capital” for high‑output environments.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises struggle to incorporate real-time behavioral insights into their existing AI and operational workflows because traditional analytics tools are siloed, require extensive data engineering, and cannot safely expose sensitive internal data to external services.
Solution
Systemores offers enterprise‑grade Model Context Protocol (MCP) servers that embed a deterministic behavioral engine directly into a company’s technology stack via an API‑first approach. The localized servers allow internal AI agents—whether in IDEs, data pipelines, or operational dashboards—to query real‑time behavioral vectors without exposing secret keys or data. By delivering predictive operation signals, cohort alignment metrics, and habit versus cognitive drag detection, the platform turns raw interaction data into quantifiable behavioral capital that can be fed into decision loops to reduce friction and improve performance.
Target Audience
Primary customers are large enterprises and high‑output organizations that run internal AI agents and need real‑time behavioral analytics to optimize operational decision‑making.
Features
- Deployable, on‑premise MCP servers that integrate securely with existing infrastructure
- API‑first interface enabling AI agents to retrieve deterministic behavioral vectors in real time
- Predictive operation signals including profiling, cohort metrics, and automated habit detection
- Behavioral capital conversion that isolates high‑fidelity signals from noisy interaction data
- Deterministic logic engine that replaces subjective interpretation with quantified metrics
- Diagnostic “Behavior OS” providing enterprise‑wide profiling and modeling capabilities