FEDERATED INTELLIGENCE

FEDERATED INTELLIGENCE

FEDERATED INTELLIGENCE

AHOY-AVML

Real-Time Agent-Based Graph Reasoning for Sovereign and Sensitive Data Environments.

Decentralized reasoning, cryptographic verification, and real-time decision intelligence without exposing raw data.

SANDBOX DEMO

ENCRYPTED STREAM

SYSTEM ACTIVE

Raw View

Federated Intel

RAW MEDIA LOCKED

Zero Trust Policy actively blocking raw stream access. No video or audio leaves the edge devices.

Edge Sources

ENCRYPTED

CAM-01 (Lobby)

Access Denied

MIC-04 (Secure)

Access Denied

CAM-05 (Server)

Access Denied

SYSTEM ACTIVE

Raw View

Federated Intel

RAW MEDIA LOCKED

Zero Trust Policy actively blocking raw stream access. No video or audio leaves the edge devices.

Edge Sources

ENCRYPTED

CAM-01 (Lobby)

Access Denied

MIC-04 (Secure)

Access Denied

CAM-05 (Server)

Access Denied

SYSTEM ACTIVE

Raw View

Federated Intel

RAW MEDIA LOCKED

Zero Trust Policy actively blocking raw stream access. No video or audio leaves the edge devices.

Edge Sources

ENCRYPTED

CAM-01 (Lobby)

Access Denied

MIC-04 (Secure)

Access Denied

CAM-05 (Server)

Access Denied

Representative simulation. No raw audio or video leaves the source.

Why Traditional Media AI Breaks in the Real World

Centralized Ingestion

Streaming petabytes of CCTV footage to the cloud is cost-prohibitive and introduces massive latency.

Sovereignty Violations

Sending facial or voice data across borders violates GDPR, CCPA, and national security protocols.

Single Points of Failure

If the central connection drops, all intelligence stops. Critical infra cannot rely on 100% uptime.

Bandwidth Constraints

Tactical edges (drones, oil rigs) often have kbps bandwidth, making cloud video analysis impossible.

Framework Definition

Framework Definition

Framework Definition

What AHOY-AVML Is

AHOY-AVML is a federated, AI-based audio and video processing framework designed to operate across decentralized, zero-trust environments.

Real-time Edge Inference

Federated Learning
(No Data Transfer)

Cryptographic Model Verification

Secure Aggregation

Real-time Edge Inference

Federated Learning
(No Data Transfer)

Cryptographic Model Verification

Secure Aggregation

Federated & Zero-Trust Architecture

Validating model updates without ever seeing the training data.

Edge Node A

Local Inference + Training

Edge Node A

Local Inference + Training

Edge Node A

Local Inference + Training

Edge Node B

Local Inference + Training

Edge Node B

Local Inference + Training

Edge Node B

Local Inference + Training

Encrypted Updates

Global Model

Federated Coordinator

Secure Aggregation

ZKP Validation

Outlier Rejection

Core Capabilities

Federated Audio & Video Learning

Models learn from local data patterns (e.g., specific facility acoustics or lighting) without that data leaving the premise. The global model gets smarter while data stays private.

Federated Audio & Video Learning

Models learn from local data patterns (e.g., specific facility acoustics or lighting) without that data leaving the premise. The global model gets smarter while data stays private.

Federated Audio & Video Learning

Models learn from local data patterns (e.g., specific facility acoustics or lighting) without that data leaving the premise. The global model gets smarter while data stays private.

Zero Trust Pipelines

Every stream is authenticated. Every model update is cryptographically signed. No implicit trust.

Zero Trust Pipelines

Every stream is authenticated. Every model update is cryptographically signed. No implicit trust.

Zero Trust Pipelines

Every stream is authenticated. Every model update is cryptographically signed. No implicit trust.

Zero-Knowledge Validation

Verify that a model update improves performance without seeing the test data it was evaluated on.

Zero-Knowledge Validation

Verify that a model update improves performance without seeing the test data it was evaluated on.

Zero-Knowledge Validation

Verify that a model update improves performance without seeing the test data it was evaluated on.

Multi-Modal Intelligence

Simultaneous processing of audio (gunshot detection, speech keywords) and video (person tracking, anomaly detection) for complete situational awareness.

Multi-Modal Intelligence

Simultaneous processing of audio (gunshot detection, speech keywords) and video (person tracking, anomaly detection) for complete situational awareness.

Multi-Modal Intelligence

Simultaneous processing of audio (gunshot detection, speech keywords) and video (person tracking, anomaly detection) for complete situational awareness.

Measured Performance, Not Claims

AHOY-AVML delivers state-of-the-art results on standard benchmarks while maintaining complete privacy preservation.

Benchmarks reflect internal testing on controlled datasets (LibriSpeech, VoxCeleb).

Comparative G-RAG Accuracy

vs. Standard RAG (76%)

Audio Enhancement SNR

+12dB Improvement

Fed. Learning Robustness

vs. Adversarial Attack

Benchmarks reflect internal testing on controlled datasets (LibriSpeech, VoxCeleb).

Comparative G-RAG Accuracy

vs. Standard RAG (76%)

Audio Enhancement SNR

+12dB Improvement

Fed. Learning Robustness

vs. Adversarial Attack

Benchmarks reflect internal testing on controlled datasets (LibriSpeech, VoxCeleb).

Comparative G-RAG Accuracy

vs. Standard RAG (76%)

Audio Enhancement SNR

+12dB Improvement

Fed. Learning Robustness

vs. Adversarial Attack

AI and Advanced Algorithms for Complex Problems.

Research-driven systems powering orchestration, logistics, and critical infrastructure.

AI and Advanced Algorithms for Complex Problems.

Research-driven systems powering orchestration, logistics, and critical infrastructure.

AI and Advanced Algorithms for Complex Problems.

Research-driven systems powering orchestration, logistics, and critical infrastructure.