[ SonexAI / v1.0 ]Est. 2026

SONEX

AIThe first deep-learning agent that plays Valorant entirely on its own — perceiving, aiming, and calling shots in real time.

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COMPUTER VISION ✦REINFORCEMENT LEARNING ✦SUB-10MS REACTION ✦C++ INFERENCE ENGINE ✦TEAM COMMS ✦AUTONOMOUS PLAY ✦
[ Capabilities ]

What the agent does

A modular system uniting vision, reinforcement learning, and language into a single autonomous player.

01

Autonomous Gameplay

The agent perceives the game through computer vision, processes the full game state, and executes every action itself — movement, aim, ability usage, and agent selection — with zero human input.

PerceptionControlReal-time
02

Natural Language Comms

An integrated NLP module lets SonexAI talk with human teammates in real time — giving callouts, requesting utility, and coordinating executes through voice and text.

NLPVoiceCoordination
03

Computer Vision Pipeline

Frame-by-frame analysis at 144+ FPS using custom CNN architectures for enemy detection, spike awareness, and object recognition tuned specifically for Valorant.

CNN144 FPSDetection
04

Deep Reinforcement Learning

Trained with PPO and custom reward shaping over 1.2M+ match replays. The policy learns optimal behavior for gunfights, economy, and team play.

PPO1.2M matchesSelf-play
05

Strategic Decision Engine

Monte Carlo Tree Search fused with neural evaluation drives high-level strategy — site executes, rotations, ability timing, and economic reads.

MCTSStrategyPlanning
06

Low-Latency Execution

A custom C++ inference engine with SIMD and TensorRT optimizations reaches sub-10ms decision latency, executed with human-like mouse dynamics.

C++TensorRT<10ms
Architecture

Pure C++ Performance

SonexAI's inference engine is written entirely in C++ for maximum performance. The neural network runs on a custom framework optimized for real-time gaming, achieving sub-10ms decision latency.

Custom Tensor Library

Hand-optimized matrix operations with AVX-512 SIMD instructions for neural network inference

Vision Pipeline

GPU-accelerated frame capture and preprocessing at 144+ FPS with DirectX hooks

Action System

Smooth mouse movement interpolation and input timing that mimics human behavior

Memory Efficient

Entire model weights and inference fit within 512MB RAM footprint

valorant_agent.cpp
 1// SonexAI Neural Engine - Core Architecture
 2namespace sonex::neural {
 3
 4class ValorantAgent {
 5private:
 6    VisionEncoder vision_encoder_;
 7    PolicyNetwork policy_net_;
 8    ValueNetwork value_net_;
 9    ActionDecoder action_decoder_;
10    
11public:
12    Action step(const Frame& frame) {
13        // Extract visual features
14        auto features = vision_encoder_.encode(frame);
15        
16        // Get policy distribution
17        auto policy = policy_net_.forward(features);
18        
19        // Sample action from policy
20        auto action = action_decoder_.decode(policy);
21        
22        return action;
23    }
24};
25
26} // namespace sonex::neural
Neural Network

Model Architecture

A 47-layer deep neural network combining convolutional vision encoders with transformer-based decision making.

Input Layer

Game Frame (1920x1080 RGB)

Vision Encoder

ResNet-50 Backbone

Feature Extraction

Multi-head Attention

Policy Head

Action Distribution

Value Head

State Evaluation

Output Layer

Action + Confidence

1.2M+
Training Data
Match replays from Iron to Radiant
127M
Model Parameters
Optimized for real-time inference
2,400
Training Time
GPU hours on A100 cluster
73%
Win Rate
Against human opponents

Training Pipeline

01

Data Collection

Gather match replays from all skill levels with full game state

02

Preprocessing

Extract frames, actions, rewards, and game state features

03

Training

PPO with custom reward shaping on distributed GPU cluster

04

Evaluation

Test against human players and benchmark performance

[ 05 ] — Access & Pricing

Get access to SonexAI

Access is gated by an invite key. Purchase a key first to unlock the forum and the ability to buy the AI, then choose the plan that fits you.

Step 01 — Required

Access Key

A one-time invite key that verifies your account, unlocks every forum section, and grants the ability to purchase a SonexAI plan. Without a key, registration is rejected as invalid.

49€one-time
Step 02 — Choose your plan

Monthly

Flexible
39€/month

Full access to SonexAI v1. Billed monthly, cancel anytime.

  • Autonomous aim & movement engine
  • Real-time teammate voice comms
  • All 24 agent strategy profiles
  • Sub-10ms reaction pipeline
  • Standard priority updates
Most popular

Yearly

Save 25%
349€/year

Everything in Monthly at the equivalent of €29/mo. Billed once per year.

  • Everything in Monthly
  • 2 months free vs. monthly
  • Early-access experimental builds
  • Priority inference nodes
  • Priority support queue

Lifetime

Best value
1499€one-time

Pay once, own SonexAI forever. All current and future v1 updates included.

  • Everything in Yearly
  • Lifetime licence — no renewals
  • All future v1.x model updates
  • Dedicated inference allocation
  • Direct line to the research team

Prices in EUR. Access key required before any plan can be purchased. VAT included where applicable.

Frequently Asked

Questions about SonexAI

SonexAI is the first Valorant AI bot built in C++ and deep learning that plays fully autonomously. It sees the game, makes strategic decisions, aims, uses abilities, and even communicates with teammates — all on its own. Version 1.0 is out now.