echoloc

HavocAI Tech Stack

Multi-domain autonomous systems software for military and commercial operations

Defense and Space Manufacturing Providence, RI 51–200 employees Founded 2024 Privately Held

HavocAI builds software-defined autonomy platforms for coordinated unmanned systems across maritime, air, and ground domains. The tech stack—C++, Rust, PyTorch, TensorFlow, Vision Transformer, NVIDIA Triton, ROS 2—reflects deep investment in real-time perception and embedded inference, while active projects span sensor fusion, payload integration, and deployment monitoring. Engineering dominates the hiring mix (13 of 22 open roles, with 3 director-level positions), paired with finance and ops scaling efforts, indicating rapid infrastructure build-out alongside product development in a capital-intensive, regulated domain.

Tech Stack 54 technologies

Core StackC++ Python Rust SolidWorks PyTorch TensorFlow Go Docker Kubernetes gRPC Adobe Premiere Pro After Effects Salesforce NetSuite Slack Jira Zoom ROS 2 Vision Transformer CLIP NVIDIA Triton Inference Server Embedded Linux Protocol Buffers MQTT ROS SSH Final Cut Pro DaVinci Resolve macOS Cisco Meraki+23 more
AdoptingMarketo

What HavocAI Is Building

Challenges

  • Scaling accounting function
  • Internal control requirements
  • Scaling capabilities to broader use cases
  • Barriers to adoption
  • Regulatory constraints
  • Fragmented funding pathways
  • Tight timelines
  • Producing high-quality content quickly
  • Capturing autonomous systems in real-world conditions
  • Inconsistent forecasting accuracy

Active Projects

  • Build financial reporting processes
  • Conference and event logistics
  • Payload integration for uncrewed surface vessels
  • New system development for uncrewed surface vessels
  • Design, build, and deploy autonomy systems for unmanned ground vehicles
  • Develop monitoring and performance metrics for deployed systems
  • Real-time perception pipeline for autonomous surface vessels
  • Sensor fusion integration for multi-modal data
  • Embedded inference deployment using nvidia triton
  • Develop repeatable playbooks for pilots, deployments, and expansion

Hiring Activity

Accelerating20 roles · 10 in 30d

Department

Engineering
13
Finance
2
Executive
1
Marketing
1
Ops
1
Product
1
Sales
1
Security
1

Seniority

Mid
9
Senior
9
Director
3
Junior
1
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About HavocAI

HavocAI, founded in 2024 and based in Providence, Rhode Island, develops autonomy software for military-grade and commercial unmanned systems. The platform enables multi-asset coordination across sea, air, and land domains, with emphasis on real-time decision-making and resilience in contested or communication-denied environments. Current deployment focus includes uncrewed surface and ground vehicles; the company is actively building out financial controls, content production, and operational playbooks as it scales from prototype to field operations. Hiring is accelerating across engineering, finance, and executive functions in the US and UK.

HeadquartersProvidence, RI
Company Size51–200 employees
Founded2024
Hiring MarketsUnited States, United Kingdom

Frequently Asked Questions

What programming languages does HavocAI use?

Core stack includes C++, Python, and Rust for autonomy and embedded systems, with PyTorch and TensorFlow for perception models and NVIDIA Triton for inference deployment on edge hardware.

What is HavocAI working on?

Active projects include real-time perception pipelines for autonomous surface vessels, sensor fusion for multi-modal data, embedded inference deployment, payload integration for uncrewed systems, and deployment monitoring and playbook development.

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How this profile is built

HavocAI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.