XHawk
Multiplayer platform where fleets of AI agents and humans collaborate over a shared knowledge graph to plan, build, and ship software 24/7.
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Product Overview
What is XHawk?
XHawk is a developer platform built for the era of human-agent teams, letting a small number of operators coordinate hundreds of background agents that work continuously instead of waiting on a keyboard. Rather than acting as a single interactive coding assistant, XHawk functions as a 'software factory' where specialized agents handle planning, coding, review, testing, and documentation across entire repositories. Every session, commit, and decision is captured into a living knowledge graph, so agents retain project context across tools like Claude, Cursor, and Copilot instead of starting from scratch each time. Teams can deploy XHawk in the cloud, in a hybrid setup, or fully within their own VPC for maximum data control.
Key Features
24x7 Background Agents
Autonomous agents triggered by events, schedules, or fleet coordination execute engineering tasks continuously, without a human actively driving each prompt.
Multi-Model Orchestration
Automatically routes each task to the best-fit frontier, open-source, or private model instead of locking teams into a single provider.
Company-Wide Knowledge Graph
Connects code, commits, tickets, documents, and conversations into a searchable context layer that keeps agents aligned with real project history.
Multiplayer Workspace
A shared interface across Slack, Kanban boards, MCPs, and APIs lets humans and dozens of agents collaborate like co-workers on the same queue of work.
Flexible Deployment Options
Supports fully managed cloud, hybrid control-plane, or complete on-premises deployment in AWS, GCP, or Azure to match security and compliance needs.
Full Execution Auditability
Every agent action is traced, reviewed, and stored, giving teams per-feature tracking and production-level visibility into how work gets done.
Use Cases
- Rapid Feature Shipping : Founders and lean startups can launch products and features faster by letting agent fleets handle implementation without growing headcount.
- Engineering Velocity at Scale : CTOs can automate testing, code review, and documentation workflows so teams ship confidently while staying small.
- Parallel Refactors and Migrations : Senior architects can offload repetitive implementation work to agents while focusing on system design and critical technical decisions.
- Cost and Efficiency Tracking : VP Engineering teams can monitor token usage, infrastructure spend, and execution efficiency per feature across the agent fleet.
- Batch Software Development : Teams can queue large volumes of work and execute tasks asynchronously in batch mode, cutting frontier model costs significantly.
FAQs
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