Twnstr provides agentic digital twins—AI software agents that continuously perceive, remember, and reason about physical assets such as buildings, industrial equipment, and energy systems. Integrated with sensors, control systems, and collaboration tools, these agents deliver real‑time insights, automate compliance, energy optimization, and maintenance tasks, and can be deployed on any cloud, edge, or on‑prem environment with enterprise‑grade traceability and explainability.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises that manage complex physical assets such as buildings, industrial equipment, or energy systems often rely on static digital models that cannot perceive real‑time conditions, remember past interactions, or autonomously act on issues, leading to delayed responses, high manual labor, and safety risks.
Solution
Twnstr creates agentic digital twins—AI‑driven software agents that continuously perceive, remember, and reason about physical assets. These agents integrate with existing sensors, control systems, and collaboration tools (e.g., Teams, Slack, Telegram) to surface actionable insights and execute tasks without human intervention. By combining episodic memory with tool access, each interaction refines the agent’s domain knowledge, enabling it to handle compliance, energy optimization, maintenance, and other operational functions. The platform is cloud‑agnostic and can be deployed on edge or on‑premises, providing model‑agnostic routing, traceability, and compliance reporting for regulated environments. Users interact with the agents through natural language, allowing rapid onboarding of assets and immediate deployment of AI‑powered workflows.
Target Audience
Primary customers are large enterprises and industrial operators that manage extensive physical infrastructure—such as facilities managers, energy providers, and manufacturing plants—seeking to automate monitoring, compliance, and maintenance tasks.
Features
- Agentic digital twins that maintain semantic and procedural memory across sessions, improving domain expertise over time
- Real‑time perception via integration with sensors, IoT devices, and existing asset management systems
- Natural‑language interface compatible with Teams, Slack, and Telegram for seamless employee interaction
- Built‑in toolset enabling agents to execute actions on connected equipment (e.g., adjust settings, trigger alerts, schedule maintenance)
- Enterprise‑grade deployment options across any cloud, edge, or on‑prem infrastructure with model routing, tracing, and explainability
- Pre‑configured specialist agents (e.g., compliance, energy, maintenance) that can be customized for specific asset types