Zerg provides autonomous engineering platforms for teams building mission‑critical technical systems, covering hardware, simulations, data pipelines, vendor integrations, migrations, and production workflows. By creating a live, model‑driven map of codebases, APIs, hardware and operational rules, Zerg automatically generates integration code, internal tools, test harnesses, and operational applications, then continuously validates them against live services, simulators, devices and production signals to keep systems reliable as they evolve.
Funding
Funding not disclosed
Founders
Product
Problem
Developing and maintaining software that integrates with complex, mission‑critical systems—such as hardware devices, simulators, vendor APIs, and production workflows—requires extensive manual effort and constant monitoring for changes, leading to high risk of integration failures and costly downtime.
Solution
Zerg offers an autonomous engineering platform that first creates a comprehensive model of the target environment, ingesting codebases, APIs, documentation, hardware specifications, tests, and production rules. Using this model, Zerg automatically generates integration code, migration tools, test harnesses, and operational applications. The platform then validates the generated software against live services, simulators, devices, and real‑time production signals to ensure correctness beyond unit tests. After deployment, Zerg continuously monitors the environment for drift in requirements, APIs, or dependencies, detects changes, and automatically produces the necessary fixes, keeping the system reliable without manual intervention.
Target Audience
Primary customers are engineering teams that build and operate products reliant on complex hardware, simulation environments, vendor integrations, and production control planes, such as aerospace, industrial automation, and high‑frequency trading firms.
Features
- Environment modeling that consolidates code, APIs, documentation, hardware specs, and production rules into a unified, queryable map
- Automated code generation for integrations, internal tools, migration scripts, and test harnesses based on the environment model
- Validation pipeline that runs against live services, simulators, devices, and real‑time production signals to verify functional correctness
- Continuous drift detection that monitors changes in APIs, requirements, or dependencies and triggers automatic remediation
- End‑to‑end workflow covering modeling, building, proving, and running, reducing manual engineering effort throughout the software lifecycle