Soket AI Labs on October 7 launched Loop, an open-source harness for running AI agents on long-duration tasks, at Cypher 2026 in Bengaluru. The company has made Loop available as a developer preview, allowing them to test and build with the system.
“Agents are no longer a quick chat window. They're running for hours, days, weeks on real work,” Upperwal said.
Soket AI said Loop is designed to run multiple agents efficiently, with parallel tool execution and low CPU and memory requirements. It is built on Rust, which the company said helps keep the system lightweight and suitable for running agents locally.
Developers can connect different models through a base URL, while sessions can be forked and operated like Git.
The company also said a single goal can be split into a swarm of agents that share memory, with isolation options ranging from rootless containers to micro virtual machines. Loop also supports the Model Context Protocol (MCP), while skills and templates can be converted into slash commands.
In its initial benchmarking, Soket AI said Loop's total runtime was close to Pi, a minimalist agent harness, while its cost performance was ahead of OpenCode and Goose. It noted that Loop recorded the lowest median task time among the harnesses it compared, along with low peak memory and CPU use.
Upperwal said these characteristics could allow thousands of agents to run on a small system. A demonstration at Cypher showed Loop researching the day's conference schedule through multiple tools, before returning a list of talks and sessions it considered relevant.
Soket AI said Loop is being developed for cybersecurity, defence, banking, finance and legal workloads. The company said sovereign deployments in these sectors require capabilities such as air-gapped environments, zero-trust execution, auditability and support for long-running tasks.
The roadmap includes sandboxing personas, multi-agent systems, leveled memory, remote agents, trusted remote sandboxes and group chat for agents. Upperwal said these workloads require a high degree of determinism, particularly in defence.
The Loop launch is part of Soket AI's broader focus on Math Code Reasoning (MCR) agents. Upperwal said the company has aggregated close to 30 trillion training tokens, primarily focused on mathematics and code, along with nearly two billion reasoning traces.
The company said its MCR approach combines mathematical reasoning, natural-language reasoning and code execution to enable agents to interact with their environments and perform longer-running tasks.
Upperwal said Soket AI open-sourced Loop to encourage wider adoption and community contributions. He also announced that the company is training a 26-billion-parameter model that it plans to release as open source, along with the dataset and training stack.
Loop's codebase is available on GitHub as a developer preview, according to the company.
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