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Kontakt.io

RTLS Platforms

HTMwire assessment

RTLS-as-a-service platform combining real-time location with AI agents for patient flow, equipment supply chain, and care operations optimization.

Key Features

  • AI-powered RTLS with fully managed IoT infrastructure
  • Patient Flow Agent predicts bed availability and discharge obstacles
  • Supply Chain Agent forecasts equipment demand and stages devices proactively
  • Access Agent optimizes exam room utilization and scheduling
  • Patient Journey Analytics creates a digital twin of hospital operations

What It Helps You Do

Reduced length of stay Higher bed capacity and faster turnover Lower equipment rental and search time Predictive equipment staging

What Sets Them Apart

Only RTLS vendor with agentic AI that predicts equipment demand and proactively stages devices — moves beyond tracking to operational orchestration.

How Kontakt.io Uses AI

Uses AI/ML

HTMwire's independent read on the technology — not the vendor's marketing claim.

Agentic AI suite includes Patient Flow Agent (predicts bed availability), Supply Chain Agent (forecasts equipment demand), and Access Agent (optimizes room utilization). Patient Journey Analytics fuses EHR and RTLS data to create a digital twin of hospital operations for demand forecasting.

  • Patient Flow Agent. Agentic AI that orchestrates patient flow from combined EHR and RTLS signals to reduce length of stay and discharge delays
  • Supply Chain Agent. Uses real-time demand signals to forecast equipment need and proactively stage devices at the bedside
  • Patient Journey Analytics. Fuses EHR and RTLS data into a digital twin of hospital operations for demand forecasting

Key Numbers

  • 4+ million IoT devices deployed since 2013 across hundreds of hospitals
  • Series C: $47.5M raised in 2024 (led by Goldman Sachs Asset Management)
  • Supply Chain Agent model (200-bed hospital): up to 89% less equipment search time, ~76% fewer device rentals

Integrations

Epic Cerner EHR systems

Tags

rtls ai-powered ble patient-flow agentic-ai

Trust Signals

Customers
Healthcare systems nationwide, millions of devices deployed
Certifications
HIPAA compliant
Investors / Funding
Goldman Sachs Asset Management (Series C, 2024); European Investment Bank (2022)
Case Studies
Named health-system customers include HCA Healthcare, U.S. Department of Veterans Affairs, Mercy Health, Trinity Health, and the NHS; published outcomes are modeled (e.g., 200-bed hospital) rather than attributed per-hospital metrics

Frequently Asked Questions

What location technology does Kontakt.io use in hospitals?

BLE (Bluetooth Low Energy) is the backbone of Kontakt.io's hospital RTLS, delivering room or zone-level accuracy at lower cost. It adds UWB for bed-level precision in areas like the OR and ICU, and can leverage existing Wi-Fi infrastructure plus RFID for supply-chain checkpoints.

What is Kontakt.io's agentic AI suite?

Kontakt.io markets a Care Orchestration suite of AI agents: Patient Journey Analytics (a digital twin fusing EHR and RTLS data), Patient Flow Agent (reduces length of stay, launched 2026), Supply Chain Agent (forecasts equipment demand and stages devices, launched 2026), and Access Agent (room utilization).

Which health systems use Kontakt.io?

Named customers include HCA Healthcare, the U.S. Department of Veterans Affairs, Mercy Health, North East Georgia Health System, Trinity Health, and the UK's NHS. Since 2013 Kontakt.io reports 4+ million IoT devices deployed across hundreds of hospitals serving 200,000+ caregivers.

Does Kontakt.io integrate with the EHR?

Yes. Fusing EHR with RTLS data is core to its platform: Patient Journey Analytics and the AI agents blend EHR and location signals, and an EMR integration can be added for richer demand signals. The official sources describe EHR/EMR integration generically and do not name Epic specifically.

Sources

  1. Kontakt.io Series C funding (Goldman Sachs)
  2. Kontakt.io Supply Chain Agent
  3. Kontakt.io healthcare asset tracking technologies

We cite a primary or named source for every claim on this page. How we evaluate →

Last updated: June 9, 2026