Since Labs
Since Labs designs and runs custom AI systems for medium and large enterprises, replacing manual data transfers, repetitive email writing, and status reporting with automated workflows. The company proves solutions on client data before commitment, then operates the systems with human-in-the-loop gates and monitoring. Real deployments reclaim between 12 and 26 hours per week per department.
- Artificial Intelligence
- AI Agents
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Organizations running multiple AI agents — whether custom-built, open-source, or off-the-shelf — struggle with fragmented memory, inconsistent access controls, and a lack of centralized oversight. Each agent operates in isolation, requiring separate integrations and credential management, which creates security risks and operational inefficiencies. Teams also lose significant time to manual data transfers between tools, repetitive email writing, and lengthy status reporting.
Solution
Since Labs is a command center for AI agents, consolidating memory, access, and mission control into one layer. The platform manages agent memory at nested scopes, from individual tasks to shared organizational knowledge. Access is handled by connecting any tool with an MCP server once at a central gateway, then assigning permissions by role across teams like sales, engineering, and marketing — credentials never leave the control layer. A live feed provides real-time visibility into agent activity, run status, spend, and tasks that require human approval. The company also operates as an AI-native lab, validating every tool on its own operations before releasing it to customers. The engagement model includes a discovery call to map bottlenecks, a feasibility test against real data, and a production build with validation and handover documentation.
Target Audience
Operations leaders, engineering teams, and security officers at medium and large enterprises that run multiple AI agents across departments and need centralized management, secure tool access, and auditable oversight. The company also serves enterprises seeking custom AI automation to eliminate repetitive manual work.
Features
- Unified memory layer with nested scopes, from agent-specific context to shared organizational knowledge
- Central access gateway for MCP-compatible tools (email, CRM, databases, repos, LLM APIs) with role-based distribution across departments
- Credential vault that keeps secrets at the control layer, preventing agents from directly accessing sensitive keys
- Live operations dashboard showing agents online, pending approvals, daily spend, and real-time activity feeds per department
- Support for heterogeneous agents: custom builds, open-source agents (OpenClaw, ZeroClaw, NanoClaw), and off-the-shelf assistants
- Mission-control features allowing human approval gates for sensitive actions like refunds and security compliance
- Feasibility testing against client data before production commitment, with strict output validation in production