Long-running autonomous task execution
A core design pillar for safer autonomous agent operations in production-like environments.
Upcoming platform
RNDLabs is developing an autonomous agent-swarm app and stack for long-running tasks where auditability, isolation, and operator trust matter.
A core design pillar for safer autonomous agent operations in production-like environments.
A core design pillar for safer autonomous agent operations in production-like environments.
A core design pillar for safer autonomous agent operations in production-like environments.
A core design pillar for safer autonomous agent operations in production-like environments.
Architecture
The planned stack separates operator intent, planning, specialist execution, sandboxed tools, and evidence capture so autonomous work can be inspected instead of treated as a black box.
Every meaningful task step should leave a trace: who or what requested it, which agent acted, what tools were used, what changed, and what evidence supports the result.
The product direction is designed around replayable audit trails, MicroVM-secured code execution, model and tool policy checks, and human review gates for critical decisions.
Autonomous systems need more than task decomposition. They need a verifiable operating model.
Agent-Swarm is positioned around long-horizon autonomy: agents coordinating research, implementation, analysis, marketing, and operations over extended periods. The product direction includes cryptographically secured audit trail logs and MicroVM-secured sandboxes for safer execution of code and tools.
For basic SME needs, the same ideas can start smaller: document RAG, internal chatbots, workflow assistants, reporting automation, and controlled agent tasks. Those capabilities can later become lanes inside Agent-Swarm when a customer needs stronger auditability and autonomy.