7SG provides an integration and deployment platform that enables enterprises to move AI pilots into production while meeting strict security, cost, performance, and control requirements. The platform continuously optimizes runtime behavior to maintain SLAs and avoid vendor lock‑in, allowing developers to deploy AI in the most suitable environment for reliable, scalable operation.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises face difficulty deploying AI prototypes into production because existing AI tools prioritize rapid experimentation over the security, cost control, performance guarantees, and integration standards required for large‑scale operations. This mismatch leads to unpredictable behavior, vendor lock‑in, and limited business impact from AI pilots.
Solution
7SG offers an agentic integration and deployment platform that aligns AI workloads with enterprise requirements. The platform enforces security policies, cost budgets, and performance SLAs across the organization’s existing infrastructure. It continuously monitors and optimizes runtime behavior to keep AI services within defined thresholds while scaling to real‑world demand. By abstracting deployment complexities, 7SG enables development teams to focus on innovation without sacrificing control or reliability. The solution also reduces dependency on single AI vendors, preserving flexibility for future technology choices.
Target Audience
Primary customers are large enterprises and technology teams that need to move AI prototypes into production while adhering to strict security, cost, and performance standards.
Features
- Agentic runtime that automatically enforces security, cost, and performance policies for AI workloads
- Continuous performance monitoring and dynamic optimization to maintain SLA compliance
- Seamless integration with existing enterprise systems and orchestration tools
- Vendor‑agnostic deployment model that prevents lock‑in and supports multi‑cloud or on‑prem environments
- Centralized dashboard for visibility into AI resource usage, cost metrics, and compliance status