AI Agent Deployment
Agents need reliable runtimes, tool access, and memory. OWSClaw packages the OpenClaw ecosystem as a managed service so teams ship assistants without operating raw GPU fleets.
What we deliver
- Managed runtime — Pre-integrated models, tool APIs, and scaling policies tuned for agent workloads.
- Memory & sessions — Persistent context patterns for long-running assistants and team workflows.
- Safety — Isolation, audit logs, and access policies suitable for internal enterprise use.
- Roadmap — Same backbone as OWS Forge for model choice and future self-hosted inference.
Typical engagement
- 1Discovery — workload profile, SLOs, data residency, and budget.
- 2Architecture — cluster topology, APIs, and integration points.
- 3Pilot — limited production or benchmark phase with clear exit criteria.
- 4Scale — hardening, FinOps, and continuous optimization.
Architecture & security
Designs are adapted per customer: VPC-style isolation, encryption in transit and at rest, secrets management, and least-privilege access to control planes. We document data flows for security review and support private connectivity options where required.
Success metrics
We align on measurable outcomes — training throughput (tokens or samples per dollar), inference p99 latency, cost per 1M tokens, job completion rates, and uptime against agreed SLOs. Dashboards and monthly reviews keep both teams honest.
Related products
This solution composes OWS products. Your team can start from any layer and expand.