Designed to replace continuous streaming—not extend it.

The First Protocol forEvent-Driven Multimodal Context Injection.

The missing link between hardware sensors and AI reasoning. We make Wearables, Robotics, and Industrial AI physically viable.

Signal

Event-based inference

Replace continuous sensor streaming with contextual payloads and stateful updates.

Less Bandwidth vs. continuous streaming

81%

Battery Life

12h+

Context Injection

Instant

Why continuous video isn’t the future.

Current AI models demand continuous video streams to "see". This approach hits a physical wall.

The Old Way: Streaming

Energy & Heat

Drains wearable batteries in <1 hour. Physically unsustainable thermals.

Bandwidth & Cost

Chokes networks in smart cities. Unscalable cloud GPU bills for enterprise.

Privacy Nightmare

Continuous data exposure creates massive compliance risks (GDPR/Gov).

The New Way: ACPIP

Adaptive Context Perception Injection Protocol

Assist-AI delivers the efficiency layer required for mass-market AI adoption. We replace streaming with intelligent, asynchronous perception events.

99% Less Camera Energy (Edge-Capable)
81% Less Bandwidth vs. continuous video streaming (Zero-Stream)
Privacy by Design (Event-based only)
Stateful Memory Context Retention

Core stack

Core Technology

Protocol and production SDK available. Assist-AI establishes the ACPIP standard.

Protocol Layer

Enabling precise, context-aware digital experiences through rigorous event injection. The operating system for perception.

Lightweight by Design

Created for broad compatibility across devices (Edge), running on low-power chips while interfacing with modern AI platforms.

Integration-Friendly

The missing link for the global AI infrastructure stack. Plug-and-play middleware for robotics, wearables, and industrial IoT.

Patent-Pending (AT Utility Model / PCT)

SDK available for partners

Advanced Context Sources

Structured payload types: The protocol accepts image, location, sensor (key-value), and event payloads. Your application maps hardware or data sources (camera, GPS, wearables, environmental sensors) into these types and injects them—no continuous streaming.

Visual Input

Snapshot-based optical sensors (No continuous video stream).

Thermal & Env.

Temperature, light, and air quality context injection.

Motion & Spatial

Position, orientation, and movement recognition events.

Identification

Barcode, RFID tag, or object reference triggers.

Health & Bio

Physiological or diagnostic measurement streams.

Environmental

Ambient light, sound, and atmosphere data.

One idea — infinite applications.

ACPIP powers the interface between machine perception and human reasoning.

Advanced Manufacturing & Robotics

Real-time multimodal assistance for assembly, inspection, and maintenance.

Healthcare & Tele-Diagnostics

Device-level visual-audio support for diagnostics, triage, and remote care.

Aerospace & Defense Systems

Secure edge-AI communication for field operations and technical maintenance.

Energy & Smart Infrastructure

AI-driven monitoring and predictive maintenance for turbines and grids.

Automotive & Mobility

In-vehicle AI copilots combining sensory awareness with conversational intelligence.

Education & Technical Training

Immersive instruction and certification enhanced through multimodal interaction.

Assist-AI protocol scaling visualization

Intellectual Property (IP)

Status

Utility Model Registered

Austrian Patent Office (AT) · International (PCT) filing prepared

Scope

Covering the method and system for asynchronous event injection into continuous inference streams. Protecting the architecture of stateful context updates without session interruption.

Filed by Michael Labitzke, 2025.

CONFIDENTIAL

Business Model & Vision

  • Protocol Licensing

    Enabling OEMs (Wearables/Robotics) to use ACPIP to solve battery & latency constraints. Recurring revenue per device unit.

  • Enterprise API Platform

    Scalable access for large-scale industrial applications and smart city infrastructure (Sovereign Cloud deployments).

We aim to establish ACPIP as a foundational protocol layer for multimodal AI systems.

Capital + access

Investment Opportunity

Assist-AI is raising a strategic round to establish the ACPIP standard globally. A production-ready SDK and reference implementation already exist.

You can request: technical whitepaper (NDA), SDK or demo access for partners, or a strategic investment meeting.

We typically respond within 24–48 hours.

NOTE: DUE TO PENDING IP PROCESSES (PCT), DETAILED ARCHITECTURAL INSIGHTS ARE AVAILABLE ONLY AFTER NDA VERIFICATION.

Strategic Focus

Sovereign AI & Edge

Standardized protocols for regulated infrastructure

Roadmap

Scaling & Presence

Expansion and partnerships 2026

Why now

Sovereign AI mandates, edge deployment, and state-backed infrastructure initiatives are driving global demand for interoperable protocols—we focus on scaling and strategic partnerships.

Michael Labitzke, Founder & System Architect

Michael Labitzke

System Architect & Founder

Australian Native | Operating from Austria

Creator of ACPIP — pioneering efficient multimodal interaction between humans and intelligent systems.

Questions & Answers

Investors evaluating sovereign AI infrastructure; OEMs and hardware makers (wearables, robotics) who need to solve battery and bandwidth constraints; and enterprises building industrial or smart-city applications that require efficient, event-based perception.

Send an email to michael@acpip.io with your request. For the technical whitepaper we run a short NDA verification; for SDK or demo access we do the same for qualified partners. We typically respond within 24–48 hours.

We confirm receipt, then either start NDA verification (for whitepaper/technical details) or schedule a call. After NDA, you receive the requested materials or a demo link and briefing.

Our method and system are under patent protection (AT utility model registered, PCT filing prepared). Detailed architectural and implementation insights are shared only after NDA to protect IP during the process.

The defensibility is in the protocol design and IP: event-driven injection without interrupting the AI stream, plus AI-initiated perception, is a specific architecture—not a trivial feature. We have a registered utility model and PCT in progress; the SDK proves implementability. Large OEMs could build something similar, but standardizing a protocol layer creates network effects and reduces integration cost for the whole ecosystem; we are positioning for that layer.